Proposals
Audio
Field | Contact | Title | Thesis type | Description |
|---|---|---|---|---|
| 3D audio | Pezzoli, Miotello | Deep Learning-Based Upsampling of Higher Order Microphones | Full thesis | This thesis investigates the use of deep learning techniques to enhance the auditory experience in virtual and augmented reality (VR/AR) environments through upsampling higher order microphones acquisitions. By improving the spatial resolution of audio data, our aim is to enhance the realism and plausibility of virtual environments. The research objectives involve analyzing the current limitations, developing innovative upsampling models, and evaluating their effectiveness through adequate assessments. The findings of this study will contribute to advancing VR/AR technology and improving audio processing techniques for enhanced immersive experiences. |
| 3D audio | Olivieri, Pezzoli, Antonacci | Acoustic Virtual Reality evaluation system | Short thesis | Perceptual tests are very important to evaluate the quality of audio algorithms, especially for spatial audio applications. In this short thesis we are interested in developing virtual reality scenes integrated with a 3D Virtual Viewer and audio signals for immersive tests. |
| 3D audio | Olivieri, Pezzoli, Antonacci | Nearfield filter for spherical microphone array recordings | Full thesis | Spherical Microphone Arrays (SMA) are very suitable for binaural rendering and in general for spatial audio applications. In this thesis we are interested in developing new methods to filter the undesired signals in a nearfield region of the SMA. |
| Audio Signal Processing | Olivieri, Pezzoli, Antonacci | Development of acoustic simulation framework for GPU | Short thesis | Parallel implementations speed up the computation of acoustic simulations. In this short thesis it is required to develop a Room Impulse Response renderer for Spherical Microphone Arrays for GPUs. The software will be preferrabily developed with CUDA and Python. Required knowledge: computational acoustics (RIRs, Image Source Method, ...) and experience with practical coding. |
| Audio forensics | Bestagini, Antonacci | Detection of text-to-speech algorithms | Full thesis | Nowadays, text-to-speech and voice conversion algorithms are able to produce very realistic speech signals, which can easily trick human ear. Moreover, this technology is in rapid evolution and it is not possible to take in account all new synthesis methods. It is necessary to develop effective synthetic speech detection systems able to work in open-set scenarios. |
| Audio forensics/Audio signal processing | Mezza | Adversarial Attacks in Acoustic Scene Classification | Full thesis | Acoustic scene classification (ASC) is the task of recognizing an environment from the sound it produces, i.e., given an audio file, we would like to determine where it was recorded (airport, bus, park, etc.) The deployment of ASC systems in real-life security and surveillance applications entails significant issues concerning their accountability and reliability. However, the robustness and interpretability of these methods, which are typically based on deep neural networks, is still an open problem. This thesis aims to study the effects of adversarial attacks in the context of ASC. Namely, we will investigate how these methods would react to deliberate perturbations of the audio signal designed to be small enough to trick them into failing while not being detectable by the human ear. |
| Musical acoustics | Antonacci, Olivieri, Pezzoli | Nearfield Acoustic Holography solver based on Physics-Informed Neural Network | Full thesis | Physics-Informed Neural Networks (PINNs) are powerful optimizers that exploit the prior knowledge of physical laws as regularization agent also in unsupervised learning tasks. This thesis aims at extending the recent approaches of data-driven Nearfield Acoustic Holography (NAH) with solutions based on PINN. |
| Musical acoustics | Antonacci, Malvermi, Pezzoli | Physics informed neural network for simulation of vibroacoustic phenomena | Full thesis | Recently, deep learning strategies combined with a-priori knowledge given by partial differential equations proved to be effective in solving a wide range of physical problems. The goal of this thesis is to apply physics-informed paradigms to well-known vibroacoustic problems e.g., bending wave propagation, sound radiation etc. [Required knowledge: acoustics fundamentals, practical knowledge of neural networks] |
| Audio Signal Processing | Mezza, Sarti | Deep Packet Loss Concealment for Speech | Full thesis | Voice communications over the Internet have become an integral part of everyday life. However, speed is often prioritized over reliability in order to respect strict real-time constraints. Consequently, short audio segments (packets) risk being severely delayed or lost. We recently developed a hybrid Packet Loss Concealment (PLC) method combining signal-processing and deep learning techniques in a synergistic way. The method, predicting future samples from a past audio context, proved to be state of the art for real-time networked music applications. In this thesis, we will explore its performance on speech signals and evaluate it against the latest deep PLC methods, such as those presented at INTERSPEECH2022. [Required knowledge: autoregressive (AR) models; practical experience with deep learning] |
| Audio signal processing | Antonacci, Pezzoli | Characterization and analysis of the directivity of sound sources | Full thesis, Short thesis | The directivity is an inherent property of every sound source (e.g., a musical instrument). The goal of this thesis is to define suitable descriptors for the directivity of sound sources which can be used when comparing different directivities. Long or short thesis depends on the depth and novelty of the analysis. [Required knowledge: basic knowledge of statistical signal processing, spherical harmonics decomposition of sound field]. |
| Audio signal processing | Antonacci, Pezzoli | Deep learning solution for localization of acoustic sources in the spherical harmonics domain | Full thesis | The spherical harmonics representation of the sound field is a widely adopted description of spatial sound. The goal of this thesis is to devise deep learning solutions that exploit the spherical harmonics representation for the analysis of the acoustic field e.g., localization of acoustic sources. [Required knowledge: spherical harmonics decomposition of sound field, theoretical knowledge and pratical experience with deep learning] |
| Audio signal processing | Bernardini, Giampiccolo | Virtual Analog Modeling, Audio Circuit Emulation, Physical Modeling Sound Synthesis through Wave Digital Filters | Full thesis | |
| Musical acoustics | Antonacci, Pezzoli, Malvermi | Prediction of new Frequency Response Functions through Convolutional Neural Networks | Full thesis, Short thesis | Recently we have successfully applied CNNs to perform interpolation of Frequency Response Functions in rectangular plates also when dealing with random measurement locations. The thesis has as first target (short version) the extension of the method for real case scenarios (few initial measurements, violin plates, reconstruction of both real and imaginary part), then a new formulation exploting physics can be planned (long version). |
| Differential Microphone Arrays | Bernardini, Albertini | Multistage Beamforming with Differential Microphone Arrays | Full thesis | Differential Microphone Arrays (DMAs) are small-sized microphone arrays known for their almost frequency-invariant beampatterns and superdirective responses. Recently, a two-stage spatial filtering (beamforming) using DMAs have been introduced. Multistage beamforming allows to obtain directivity patterns which are equal to the product of each spatial filtering stage beampattern. The aim of the Thesis is to develop a general N-stage beamformer and evaluate its properties in terms of directionality and robustness against noise. |
| Musical Acoustics | Antonacci, Olivieri, Pezzoli | The impact of reverberation for data-driven Nearfield Acoustic Holography | Full/short thesis | Recent Deep Learning techniques proved the ability to infer the vibrational behavior in plates starting from acoustic measurements. This thesis aims at quantifying the performance of the current data-driven methods for Nearfield Acoustic Holography in the presence of reverberation (short thesis) and extending the neural network model to work in reverberant scenarios (long thesis). |
| Musical Acoustics | Antonacci, Olivieri, Pezzoli | Transfer Learning techniques for Nearfield Acoustic Holography analysis | Full/short thesis | Recent data-driven based NAH methods can predict the vibrational behavior on sources from the acquisition of the radiated sound field. Nevertheless, these approaches are dependent on the training dataset used (i.e., acquisition setup and vibrational source). This thesis aims at extending the recent solutions with transfer learning strategies in order to tune the networks with different data and improving the model with specific physical priors to reconstruct the vibrational content with an unsupervised approach (long thesis). [knowledge of Deep Learning required] |
| Musical Acoustics | Gonzalez, Antonacci | Experimental measurement and construction of violin top plates | Full/short thesis | The aim of this thesis is twofold: measure the material properties of violin top plates and build violin top plates with certain material properties. For this the student will use a CNC router to build the plates and a experimental set up that measures the FRF of the plate to compute its material parameters. The goal is to be able to produce top plates with a defined mechanical response irrespective of the varying material parameters of the wood the top is made of. Experimental thesis in Cremona Campus, FEM modelling required, Fusion 360 optional. |
| Musical Acoustics | Gonzalez, Antonacci | Multiphysics simulation of free reeds | Long thesis | The bandoneon is fundamental part of the sound of Tango, yet there is very little scientific research on its sound. In this thesis we will study the multiphysics interaction of a free red by means of simulations, and hopefully compare the results with our experimental partners. |
| Musical Acoustics | Gonzalez, Antonacci | Role of f-hole design in stress distribution on the violin top plate | Long thesis | The role of the f-holes in violins is to let the sound vibrations leave the body of the instrument and reach the audience. However, cutting holes in the top plate weakens it. By cutting curves and circles, the instrument maker avoids creating the stress concentrations associated with sharp corners. The aim of this thesis is to study the stress behaviour in a violin soundboard for different f-hole designs. Comsol experience prefered. |
| Musical Acoustics | Gonzalez, Antonacci | Effect of tailpiece height in the acoustic response of a violin | Long thesis | Varying the height of the tailpiece is one of the ways luthiers can control the sound production of the violin. By changing the angle of the strings, there is a modification in the effective pressure that the bridge, and consequently the violin top plate, feels. This compression of the violin is believed to affect the sound production of the instrument. This thesis aims to study, by means of simulations, the effect the net static force in the bridge has in the dynamics of the instrument. If time allows the thesis could also include experimental measurements with the help of Amorim fine violins. |
| Musical Acoustics | Gonzalez, Antonacci | Experimental study of wooden metamaterials | Long thesis | Experimental realisation of metamaterials for instrument making: guitar top plates, violin top plates, archtop top plates. Studies of vibrational and stiffness behaviour. Needs to live in Cremona. |
Image and Video
Field | Contact | Title | Thesis type | Description |
|---|---|---|---|---|
| Image/video forensics | Bestagini, Mandelli, Cannas | Detect and localize image and video manipulations | Full | Images and videos can be manipulated in many different ways (e.g., object insertion and removal, local retouching, laundering operations, etc.). We are interested in developing methods to detect and localize possible editing operations on images and videos. |
| Image/video forensics | Bestagini, Mandelli, Cannas | Distinguish original videos from DeepFakes | Full | DeepFake videos can be maliciously spread online. We are interested in developing techniques to detect whether a video is a DeepFake or not, why a detector says a video is fake, and understand which DeepFake generation software has been used to create a video. |
| Image/video forensics | Bestagini, Mandelli, Cannas | Assess the authenticity of satellite images | Full | Satellites can acquire visual data with different sensors. We are interested in developing techniques that verify whether an overhead image has been edited or not. |
| Image/video forensics | Bestagini, Mandelli, Cannas | Forensic analysis of scientific images | Full | Scientific publications in the life science area typically contain charcateristic kinds of images to showcase the achieved results (e.g., western blots, microscopy acquisitions, etc.). As these images differ from natural photographs, we are interested in developing novel techniques to detect possible scientific image forgery operations. |
| Image/video processing | Marcon | Analysis of hyperspectral X-ray images for food quality assessment | Full | X-ray acquisitions are beneficial in food contaminant analysis as they can detect both metallic and non-metallic objects. The goal of a thesis in this field is to develop processing techniques that help dealing with X-ray acquisition in food contaminant detection applications (e.g., denoising, detection, segmentation, etc.). |
Geophysics
Contact | Title | Thesis type | Description |
|---|---|---|---|
| Tubaro, Lipari | Improving Full Waveform Inversion with CNNs | Full/short | Full Waveform Inversion reconstructs the subsurface velocities from a set of measurements. It is very expensive, time-consuming and prone to a number of tips and tricks for avoiding local minima, numerical instability and optimization errors. |
| Tubaro, Lipari | Denoising and Interpolation of seismic data through CNNs | Full/short | The amount of data is constantly increasing and the areas of interest are more and more complex to analyze. Moreover, they require a subsurface mapping at increasingly higher resolution and higher fidelity. Can CNNs help this process? |
| Tubaro, Lipari | Machine Learning guided Seismic Interpretation | Full/short | Human experts visually inspects seismic images looking for subsurface features. On the other hand, Machine Learning techniques have proven to be effective in image segmentation (i.e., recognizing objects and targets from a set of pixels). Can we merge these two worlds? |
| Tubaro, Lipari | Physics-aware Transfer Learning | Full/short | Can a neural network learn Physics? |
| Tubaro, Lipari | Regularizing Traveltime Tomography via Machine Learning | Full/short | Traveltime Tomography is an important tool for localizing subsurface events, both in medical and geophysical imaging. The tomography problem is a ill-posed and ill-conditioned inverse problem, which suffers a lot from numberical instability, local minima, and noise. Here's where the machine learning comes into play! |
Currently on-going
Expand list
Field | Supervisor | Topic | Student(s) |
|---|---|---|---|
| Space-time audio | Antonacci, Pezzoli, Miotello, Olivieri | Real-time microphone array rendering framework for binaural reproduction | Paolo Ostan |
| Space-time audio | Antonacci, Pezzoli | Sound field separation in the spherical harmonics domain | Sagi Della-Torre |
| Space-time audio | Antonacci, Pezzoli | Analysis of the directivity of sound sources | Hou Hin Au-Yeung |
| Audio signal processing | Bernardini, Giampiccolo | Modeling of Nonlinear Piezoelectric Loudspeakers | Armando Boemio |
| Image forensics | Bestagini, Mandelli | Manipulation detection for scientific images | Giovanni Zanocco |
| Video processing | Bestagini, Redondi | Automatic video analysis of badminton matches | Ivan Motasov |
| Audio signal processing | Bernardini, Giampiccolo | Virtual Bass Enhancement for Small-Size Transducers | Fabio Spreafico |
| Space-time audio | Bernardini, Giampiccolo | Synthesis of Room Acoustics via Scattering Delay Networks using Automatic Differentiation | Francesco Boarino |
| Audio signal processing | Bernardini, Giampiccolo | Quasi newton methods in the Wave Digital Domain | Davide Marin Pasin |
| Musical Acoustics | Antonacci, Olivieri | Towards white-box data-driven methods for Near-field Acoustic Holography | Hagar Kafri |
| Video forensics | Bestagini, Cannas | Deepfake video detection through multi-look analysis | Adriano Bonfantini |
| Audio signal processing | Bernardini, Giampiccolo | Wave Digital Newton-Raphson Method for Virtual Analog Modeling | Luca Gobbato |
| Space-time audio | Antonacci, Pezzoli | Sound source localization in the spherical harmonics | Luca Cattaneo |
| Music informatics | Sarti, Mezza, Bernardini | Unsupervised selection of harmonic complexity metrics | Giorgio De Luca |
| Music informatics | Zanoni, Borrelli | Social interaction based music recommendation system | Carlo Pulvirenti |
| Music informatics | Sarti, Borrelli | Connecting NN to bio-metric signals | Joep Rene Wulms |
| Musical Acoustics | Gonzalez, Antonacci | Random variation of guitar bracings | Mattia Vanessa |
| Musical acoustics | Gonzalez, Antonacci | Metamaterials for guitarmaking | Gabriele Marelli, Mattia Lercari |
| Musical acoustics / AI | Gonzalez, Antonacci | AI-powered pick up: making guitars sound great again | Emanuele Voltini |
| Space-time audio | Antonacci, Comanducci | Personalized Sound Zone Generation using Deep Learning | Roberto Alessandri |
| Musical Acoustics | Antonacci, Malvermi, Pezzoli | Prediction of new Frequency Response Functions through Convolutional Neural Networks | Jiayan Cui |
| Music Informatics | Zanoni, Comanducci | Procedural Music Generation For Video games | Francesco Zumerle |
Past (from 2017)
Expand list
Field | Supervisor | Title | Student(s) | Link |
|---|---|---|---|---|
| Musical Acoustics | Ripamonti, Malvermi, Gonzalez | Experimental Validation for data-driven Near-field Acoustic Holography | Alessio Lampis | |
| Musical Acoustics | Antonacci, Malvermi | Improved sensors for low-cost Vibrometric Kit | Fabio Guarnieri | |
| Musical Acoustics | Sarti, Paoletti, Adali, Malvermi | Acoustic Characterization of materials | Marco Donzelli | |
| Music Informatics | Zanoni, Comanducci | Deep Learning-based Timbre Transfer | Silvio Pol | https://www.politesi.polimi.it/handle/10589/189682 |
| Audio signal processing | Antonacci | A perceptual evaluation of sound field reconstruction algorithms | Miriam Papagno | https://www.politesi.polimi.it/handle/10589/186341 |
| Audio signal processing | Bernardini, Giampiccolo | Characterization of Small-Size Loudspeakers for Mobile Applications | Samuele Buonassisi | https://www.politesi.polimi.it/handle/10589/189746 |
| Image forensics | Bestagini, Cannas | Enhanced Amplitude SAR Imagery Splicing Localization through Land Cover Mapping Techniques | Emanuele Intagliata | |
| Geophysics | Bestagini, Lipari | Salt Segmentation of Geophysical Images through Explainable CNNs | Francesco Maffezzoli | |
| Audio forensics | Bestagini, Borrelli | A metric learning approach for splicing localization based on synthetic speech detection | Francesco Castelli | https://www.politesi.polimi.it/handle/10589/184332 |
| Audio forensics | Bestagini, Borrelli | Combining automatic speaker verification and prosody analysis for synthetic speech detection | Luigi Attorresi | https://www.politesi.polimi.it/handle/10589/187094 |
| Music informatics | Bestagini, Cuccovillo | Speech fingerprinting and matching for content retrieval | Laura Colzani | https://www.politesi.polimi.it/handle/10589/187212 |
| Video forensics | Bestagini | A CNN-based detector for video frame-rate interpolation | Simone Mariani | https://www.politesi.polimi.it/handle/10589/186433 |
| Image/video processing | Bestagini | Audio-video techniques for the analysis of players behaviour in Badminton matches | Samuele Bosi | https://www.politesi.polimi.it/handle/10589/186571 |
| Video forensics | Bestagini, Mandelli | Forensic detection of deepfakes generated through video-to-video translation | Carmelo Fascella | https://www.politesi.polimi.it/handle/10589/182988 |
| Audio signal processing | Bernardini, Mezza, Giampiccolo | Wave Digital Filter Modeling of Audio Circuits with Hysteresis Nonlinearities using Neural Networks | Oliviero Massi | https://www.politesi.polimi.it/handle/10589/186739 |
| Music informatics | Antonacci, Pezzoli, Comanducci | Deep Prior Audio Inpainting | Federico Miotello | |
| Audio signal processing | Bestagini, Buccoli | Low-latency speaker recognition | Francesco Salani | |
| Video forensics | Bestagini, Bonettini | A Data Driven Approach to Deepfake Detection via Feature Analysis Based on Limited Data | Bingyang Hu | |
| Space-time audio | Antonacci, Borrelli, Borra | Beamforming and Speaker Identification through Deep Neural Networks | Matteo Scerbo | https://www.politesi.polimi.it/handle/10589/176160 |
| Music informatics | Sarti, Borrelli | Harmonic complexity estimation of jazz music | Giovanni Agosti | |
| Audio forensics | Antonacci, Borrelli | A model selection method for room shape classification based on mono speech signals | Gabriele Antonacci | https://www.politesi.polimi.it/handle/10589/179887 |
| Audio forensics | Bestagini | Audio splicing detection and localization based on recording device cues | Daniele Ugo Leonzio | https://www.politesi.polimi.it/handle/10589/179424 |
| Audio forensics | Bestagini | Speaker-Independent Microphone Identification via Blind Channel Estimation in Noisy Condition | Antonio Giganti | https://www.politesi.polimi.it/handle/10589/179420 |
| Audio forensics | Bestagini, Borrelli | Synthetic Speech Detection through Convolutional Neural Networks in Noisy Environments | Eleonora Landini | https://www.politesi.polimi.it/handle/10589/179458 |
| Audio forensics | Bestagini, Borrelli, Salvi | Synthetic speech detection based on sentiment analysis | Emanuele Conti | https://www.politesi.polimi.it/handle/10589/177968 |
| Multimedia forensics | Bestagini, Salvi, Borrelli | Audio-video deepfake detection through emotion recognition | Jacopo Gino | https://www.politesi.polimi.it/handle/10589/179037 |
| Audio signal processing | Sarti, Giampiccolo, Bernardini | Parallel Wave Digital Implementations of Nonlinear Audio Circuits | Natoli Antonino | https://www.politesi.polimi.it/handle/10589/178037 |
| Musical Acoustics | Antonacci, Malvermi | Data driven methods for frequency response functions interpolation | Matteo Acerbi | https://www.politesi.polimi.it/handle/10589/170179 |
| Audio forensics | Bestagini, Mandelli | Time-Scaling Detection in Audio Recordings | Michele Pilia | https://www.politesi.polimi.it/handle/10589/173711 |
| Audio forensics | Bestagini, Borrelli | Speech Intelligibility Parameters Estimation Through Convolutional Neural Networks | Mattia Papa | https://www.politesi.polimi.it/handle/10589/173756 |
| Audio forensics | Antonacci | Closed and open set classification of real and AI synthesised speech | Michelangelo Medori | https://www.politesi.polimi.it/handle/10589/170094 |
| Audio forensics | Antonacci | An approach to room volume estimation from single-channel speech signals based on neural networks | Castelnuovo Carlo | https://www.politesi.polimi.it/handle/10589/164749 |
| Audio forensics | Bestagini | Audio Splicing Detection and Localization Based on Acoustic Cues | Capoferri Davide | https://www.politesi.polimi.it/handle/10589/164950 |
| Audio processing | Sarti, Comanducci | Audio frame reconstruction from incomplete observations using Deep Learning techniques | Schils Minh Cédric | https://matheo.uliege.be/handle/2268.2/10138 |
| Audio processing | Sarti, Bernardini | Wave Digital Modeling and Simulation of Nonlinear Electromagnetic Circuits | Giampiccolo Riccardo | https://www.politesi.polimi.it/handle/10589/153994 |
| Audio processing | Sarti, Bernardini | Antiderivative Antialiasing in Nonlinear Wave Digital Filters | Albertini Davide | https://www.politesi.polimi.it/handle/10589/152934 |
| Audio processing | Sarti, Bernardini | Wave Digital Implementation of Nonlinear Audio Circuits based on the Scattering Iterative Method | Proverbio Alessandro | https://www.politesi.polimi.it/handle/10589/152323 |
| Audio processing | Antonacci | A system for super resolution vibrometric analysis through convolutional neural networks | Campagnoli Chiara | https://www.politesi.polimi.it/handle/10589/152613 |
| Audio processing | Antonacci | Development of a low-cost platform for acoustic and vibrometric analysis on lutherie products, with a special focus on the estimation of the elastic parameters of the tonewood | Villa Luca | https://www.politesi.polimi.it/handle/10589/150531 |
| Audio processing | Bestagini | DNN based post-filtering for quality improvement of AMR-WB decoded speech | Gupta Kishan | https://www.politesi.polimi.it/handle/10589/151000 |
| Audio processing | Sarti | Studio sull'implementazione degli algoritmi per il musical instruments ed il sound reinforcement basato su un processore multicore | Aretino Michele | https://www.politesi.polimi.it/handle/10589/139079 |
| Audio processing | Sarti, Bernardini | Modeling nonlinear 3-terminal devices in the wave digital domain | Vergani Alessio Emanuele | https://www.politesi.polimi.it/handle/10589/133184 |
| Forensics | Bestagini | Convolutional and recurrent neural networks for video tampering detection and localization | Cannas Edoardo Daniele | https://www.politesi.polimi.it/handle/10589/149900 |
| Forensics | Bestagini | A study on Bagging-Voronoi algorithm for tampering localization | Cereghetti Corinne Elena | https://www.politesi.polimi.it/handle/10589/141725 |
| Forensics | Bestagini | JPEG-based forensics through convolutional neural networks | Bonettini Nicolò | https://www.politesi.polimi.it/handle/10589/133727 |
| Forensics | Bestagini | Analysis of different footprints for JPEG compression detection | Chen Ke | https://www.politesi.polimi.it/handle/10589/132721 |
| Geophysics | Bestagini | Landmine detection on GPR data employing convolutional autoencoder | Testa Giuseppe | https://www.politesi.polimi.it/handle/10589/142106 |
| Image and video | Marcon, Paracchini | A novel tomographic approach for an early detection of multiple myeloma progression | Andrea Leggio | |
| Image and video | Marcon, Paracchini | Limited angle computed tomography reconstruction with deep learning enhancement | Erbol Kasenov, Girolamo Gerace | |
| Image and video | Marcon | Upper body postural assessment for common dentistry visual aids | Trotta Emilio | https://www.politesi.polimi.it/handle/10589/145563 |
| Image and video | Tubaro | Real-time tracking of electrode during deep-brain surgery | Dilauro Valerio | https://www.politesi.polimi.it/handle/10589/144685 |
| Image and video | Marcon | Analytical estimation of the error on the radius of industrial pipes | Lazzarin Sara | https://www.politesi.polimi.it/handle/10589/144394 |
| Image and video | Marcon | 3D reconstruction from stereo video acquired from odontoiatric microscope | Spatafora Leonardo | https://www.politesi.polimi.it/handle/10589/143780 |
| Image and video | Marcon | Denoising and classification of hyperspectral X-ray images for food quality assessment | Re Marco | https://www.politesi.polimi.it/handle/10589/142922 |
| Image and video | Marcon | A computer vision approach for assessment of dental bracket removal | Behnami Arezoo | https://www.politesi.polimi.it/handle/10589/142362 |
| Image and video | Marcon | Sistema per il rilevamento automatico di contaminanti alimentari basato su immagini iperspettrali | Ramoni Francesco | https://www.politesi.polimi.it/handle/10589/135891 |
| Image and video | Marcon | Postural assessment in dentistry by computer vision | Pignatelli Nicola | https://www.politesi.polimi.it/handle/10589/135030 |
| Multimedia forensics | Bestagini, Mandelli | A Multi-Modal Approach to Forensic Audio-Visual Device Identification | Davide Dal Cortivo | https://www.politesi.polimi.it/handle/10589/175593 |
| Music informatics | Sarti, Bernardini, Borrelli, Mezza | Estimating Harmonic Complexity of Chord Sequences using Transformer Networks | Cecilia Morato | |
| Music informatics | Zanoni, Comanducci | Modeling Harmonic Complexity in Automatic Music Generation using Conditional Variational Autoencoders | Davide Gioiosa | |
| Music informatics | Sarti, Borrelli, Comanducci | Cellular music : a novel music-generation platform based on an evolutionary paradigm | Matteo Manzolini | https://www.politesi.polimi.it/handle/10589/167291 |
| Music informatics | Sarti, Borrelli | Music emotion detection. A framework based on electrodermal activities. | Gioele Pozzi | https://www.politesi.polimi.it/handle/10589/152931 |
| Music informatics | Sarti, Comanducci | Techniques for mitigating the impact of latency in Networked Music Performance (NMP) through adaptive metronomes | Battello Riccardo | https://www.politesi.polimi.it/handle/10589/152923 |
| Music information retrieval | Sarti | Musical instrument recognition: a transfer learning approach | Molgora Andrea | https://www.politesi.polimi.it/handle/10589/147383 |
| Music information retrieval | Sarti | Unsupervised domain adaptation for deep learning based acoustic scene classification | Mezza Alessandro Ilic | https://www.politesi.polimi.it/handle/10589/145573 |
| Music information retrieval | Antonacci | An investigation of piano transcription algorithm for jazz music | Marzorati Giorgio | https://www.politesi.polimi.it/handle/10589/144745 |
| Music information retrieval | Sarti | Automatic playlist generation using recurrent neural network | Irene Rosilde Tatiana | https://www.politesi.polimi.it/handle/10589/142101 |
| Music information retrieval | Sarti | A personalized metric for music similarity using Siamese deep neural networks | Sala Federico | https://www.politesi.polimi.it/handle/10589/139078 |
| Music information retrieval | Sarti | Learning a personalized similarity metric for musical content | Carloni Luca | https://www.politesi.polimi.it/handle/10589/139076 |
| Music information retrieval | Sarti | Beat tracking using recurrent neural network : a transfer learning approach | Fiocchi Davide | https://www.politesi.polimi.it/handle/10589/139073 |
| Music information retrieval | Sarti | Python-based framework for managing a base of complex data for music information retrieval | Avocone Giuseppe | https://www.politesi.polimi.it/handle/10589/138449 |
| Music information retrieval | Sarti | Individual semantic modeling for music information retrieval | Ansidei Pietro | https://www.politesi.polimi.it/handle/10589/137160 |
| Music information retrieval | Sarti | Chord sequences : evaluating the effect of complexity on preference | Foscarin Francesco | https://www.politesi.polimi.it/handle/10589/136448 |
| Music information retrieval | Sarti | Audio features compensation based on coding bitrate | Tavella Maria Stella | https://www.politesi.polimi.it/handle/10589/134607 |
| Musical Acoustics | Antonacci | Modal analysis and optimization of the top plate of string instruments through a parametric control of their shape | Salvi Davide | https://www.politesi.polimi.it/handle/10589/166557 |
| Musical Acoustics | Antonacci, Pezzoli, Malvermi | An approach for Near-field Acoustic Holography based on Convolutional Autoencoders | Olivieri Marco | https://www.politesi.polimi.it/handle/10589/167039 |
| Space-time audio | Antonacci, Borra | A parametric approach to virtual miking with distributed microphone arrays | Marco Langè | |
| Space-time audio | Antonacci, Pezzoli, Borra, Bernardini | A Deep Prior Approach to Room Impulse Response Interpolation | Davide Perini | https://www.politesi.polimi.it/handle/10589/175583 |
| Space-time audio | Antonacci, Comanducci | Interpreting Deep Neural Networks Models for Acoustic Source Localization using Layer-wise Relevance Propagation | Alessandro Montali | https://www.politesi.polimi.it/handle/10589/169239 |
| Space-time audio | Antonacci, Borra, Bernardini | Analysis of Uniform Linear Arrays of Differential Microphones | Bertuletti Ivan | https://www.politesi.polimi.it/handle/10589/154604 |
| Space-time audio | Sarti | A geometrical method of 3D sound spatialization for virtual reality applications | Iamele Jacopo | https://www.politesi.polimi.it/handle/10589/143770 |
| Space-time audio | Antonacci | Convolutional neural networks applied to space-time audio processing applications | Comanducci Luca | https://www.politesi.polimi.it/handle/10589/139077 |
| Space-time audio | Canclini | Denoising in the spherical harmonic domain of sound scenes acquired by compact arrays | Borrelli Clara | https://www.politesi.polimi.it/handle/10589/139075 |
| Space-time audio | Antonacci | Simulazione di sistemi complessi. Case study : l'altoparlante a tromba | Moscara Francesco | https://www.politesi.polimi.it/handle/10589/139074 |
| Space-time audio | Sarti, Bernardini | Steerable differential microphone arrays | Lovatello Jacopo | https://www.politesi.polimi.it/handle/10589/139072 |
| Space-time audio | Antonacci | A plenacoustic approach to sound scene manipulation | Picetti Francesco | https://www.politesi.polimi.it/handle/10589/138430 |
| Space-time audio | Antonacci | Reconstruction of the soundfield in arbitrary locations using the distributed ray space transform | Pezzoli Mirco | https://www.politesi.polimi.it/handle/10589/136447 |
| Space-time audio | Sarti | A method for HRTF personalization : weighted sparse representation synthesis of HRTFs | Zhu Mo | https://www.politesi.polimi.it/handle/10589/135952 |
| Space-time audio | Antonacci | Robust parametric spatial audio processing using beamforming techniques | Milano Guendalina | https://www.politesi.polimi.it/handle/10589/134609 |
| Space-time audio | Antonacci | Estimation of singing voice quality through microphone in air and contact microphone | Landini Roberta | https://www.politesi.polimi.it/handle/10589/134604 |
| Musical Acoustics | Antonacci, Malvermi | Mechanical parameter estimation for vibrometric analysis and development of a low-cost platform for violin making | Federico Simeon | https://www.politesi.polimi.it/handle/10589/170995 |
| Space-time audio | Antonacci, Comanducci | 3D audio with irregular microphone setups using deep learning | Davide Mori | https://www.politesi.polimi.it/handle/10589/175608 |