Proposals
Audio
Field | Contact | Title | Thesis type | Description |
|---|---|---|---|---|
| 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] |
| Acoustic Scenes and Events | Sarti, Mezza | Detection of anomalous sounds in domestic environments | Full thesis | The objective is the development of intelligent systems capable of monitoring a domestic environment to detect acoustic anomalies. The idea is to learn a suitable "normal state" for the monitored soundscape and to track the deviations thereof with minimal or no supervision. |
| Audio Forensics | Bestagini | Analysis of MP3 audio files metadata and structure | Full thesis | Forensic analysis of multimedia objects can be performed by observing the way a file is structured and saved to disk, rather than analyzing the actual content. For instance, the analysis of MP4 video containers can provide valuable information related to video origin (https://arxiv.org/pdf/2101.10795v1.pdf). The goal of this work is to dig into the structure of an MP3 audio file to extract possible information related to the used encoder, device, or presence of tampering. |
| Audio signal processing | Bernardini, Giampiccolo | Virtual Analog Modeling, Audio Circuit Emulation, Physical Modeling Sound Synthesis through Wave Digital Filters | Full thesis | |
| Audio signal processing | Bernardini, Giampiccolo | Implementation of Wave Digital scattering matrices absorbing controlled sources | Full thesis | In the Wave Digital domain, topological scattering junctions can absorb certain nonreciprocal elements. The thesis concerns the derivation of formulas for the efficient computation of their scattering matrices, such that they can be exploited for Virtual Analog applications. |
| Audio signal processing | Bernardini, Giampiccolo | Virtual Bass Enhancement for Small-Size Transducers | Full thesis | In consumer electronics, the reduced dimensions of devices (e.g., laptops, smartphones, etc.) impair the acoustical response of audio transducers, especially at low frequency. In this context, Virtual Bass Enhancement (VBE) techniques can be employed to enhance the perception of low frequencies by exploiting the "missing fundamental" phenomenon. The thesis concerns the development of a VBE processing chain for the specific case of small-size transducers, such as piezoelectric and MEMS transducers. |
| Music informatics | Sarti, Mezza, Comanducci | Audio prediction for Networked Music Performance | Full thesis | In recent years, live music performances over the Internet have become a reality. However, the inevitable network packets loss is still affecting the experience in a significant way, causing abrupt interruptions and glitches in the audio stream. In this respect, we aim at developing new deep learning-based techniques that would tackle this issue by predicting the next few milliseconds of audio, while ensuring the high quality and seamlessness of the reconstructed music signal. |
| Musical acoustics | Olivieri, Antonacci | Towards white-box data-driven methods for Near-field Acoustic Holography | Full thesis | Near-field Acoustic Holography (NAH) is a powerful technique to study the velocity field on vibrating objects in a contactless way (e.g., without accelerometer sensors). Recently, we developed a fully data-driven approach for NAH with Convolutional Neural Networks which can increase the performances of previous state-of-the-art methods. The goal of this thesis is to investigate and understand what the networks learned, in order to transform the current black box methodology towards a white box one. |
| 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 | Evaluation of phase, gain, and misplacement errors on arbitrary geometry 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 developed arbitrary geometry DMAs represent a generalization of traditional DMAs, allowing to form spatial filters with any random microphone distribution. The aim of the Thesis is to model the effect of phase, gain and misplacement errors on the arbitrary geometry DMA performance, and develop a method to compensate such errors. Characterization of real sensors is a possibility. |
| Bernardini, Albertini | Antiderivative Antialiasing for multi-port elements in the Wave Digital domain | Full thesis | Antiderivative Antialiasing is a recently proposed technique for mitigating aliasing distortion in virtual analog applications. The technique has attracted considerable attention due to its ability to reduce aliasing artifacts without resorting to high oversampling factors in the physical emulation of audio circuits. The approach has recently been extended to Wave Digital Filters with up to one-port nonlinear element. The goal of this thesis is to extend Antiderivative Antialiasing to multi-port nonlinear elements. | |
| 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 | Gonzalez, Antonacci | Influence of thickness profile in archtop guitars | Full/short thesis | This thesis has two parts: modeling an archtop guitar parametrically in Fusion 360 and then realising simulations in COMSOL to study its acoustic response. Short and long thesis depend on the depth of the study. |
| 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 | Antonacci,Malvermi | Enhanced feature-based representation for violin bridge admittances | Full/short thesis | Bridge Admittances are one of the cornerstones of experimental research in violins. Recent results on a set of measurements proved that a metric based on selected features (modal parameters in the low frequency range) leads to more informative and fair comparisons between different violins. The thesis aims at exploring new hand-crafted features for mid and high frequency ranges and apply data analysis principles to find optimal representation. |
| 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 | FEM simulation of cello bridges | Short thesis | The objective of this thesis is to study the structural and dynamical characteristics of different designs of Cello bridges. In particular, we will study the "classical" design and the "X" model created by Luthier L. Amorim. Knowledge of FEM is required, Fusion 360 would be a good extra. |
Image and Video
Field | Contact | Title | With Discussant | Description |
|---|---|---|---|---|
| Image/video forensics | Bestagini, Bonettini | Detect and localize image and video manipulations | yes | 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, Bonettini | Distinguish original videos from DeepFakes | yes | 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 | Assess the authenticity of satellite images | yes | 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 | Forensic analysis of scientific images | yes | 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, Bonettini | Analysis of hyperspectral X-ray images for food quality assessment | yes | 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, Picetti | 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, Picetti | 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, Picetti | 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, Picetti | Physics-aware Transfer Learning | Full/short | Can a neural network learn Physics? |
| Tubaro, Lipari, Picetti | 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) |
|---|---|---|---|
| Audio signal processing | Bernardini, Giampiccolo | Wave Digital Newton-Raphson Method for Virtual Analog Modeling | Luca Gobbato |
| Audio signal processing | Bernardini, Mezza, Giampiccolo | Wave Digital Filter Modeling of Audio Circuits with Hysteresis Nonlinearities using Neural Networks | Oliviero Massi |
| Image forensics | Bestagini, Cannas | Forensic analysis of overhead imagery | Emanuele Intagliata |
| Space-time audio | Antonacci | Perceptual evaluation of sound field reconstruction | Miriam Papagno |
| Video forensics | Bestagini, Bonettini | Deepfake video detection | Bingyang Hu |
| Audio forensics | Bestagini, Borrelli | Detection of splicing based on synthetic voice production | Francesco Castelli |
| Audio forensics | Bestagini, Borrelli | Combining speaker identification and prosody analysis for synthetic speech detection | Luigi Attorresi |
| Space-time audio | Antonacci, Comanducci | 3D audio with irregular microphone setups using deep learning | Davide Mori |
| Space-time audio | Antonacci, Bernardini, Borra | 3D sound field rendering with loudspeaker array. | Francesco Pino |
| Music informatics | Sarti, Mezza, Bernardini | Unsupervised selection of harmonic complexity metrics | Giorgio De Luca |
| Space-time audio | Sarti, Bernardini | Modeling Multichannel Room Impulse Responses using Banks of State-Space Filters | Agnese Pantaleone |
| 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 | 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 | Ripamonti, Malvermi | Source-aware Active Vibration Control on glass surfaces | Niccolo Botti, Tommaso Botti |
| Musical Acoustics | Antonacci, Gonzalez, Malvermi | Mechanical Parameter prediction from Frequency Response Function measurements | David Badiane |
| Musical Acoustics | Sarti, Paoletti, Adali, Malvermi | Acoustic Characterization of materials | Marco Donzelli |
| 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 |
| Geophysics | Bestagini, Lipari | Segmentation of salt bodies in migrated volumes for velocity model building | Francesco Maffezzoli |
| Image/video processing | Bestagini | Analysis of badminton match videos | Samuele Bosi |
| Music Informatics | Sarti, Turchet (UNITN), Comanducci | Adaptive Metronomes using Haptic Devices for Networked Music Performances | Paolo De Santis |
| Music Informatics | Zanoni, Comanducci | Deep Learning-based Timbre Transfer | Silvio Pol |
Past (from 2017)
Expand list
Field | Supervisor | Title | Student(s) | Link |
|---|---|---|---|---|
| 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 Mioltello | |
| Audio signal processing | Bestagini, Buccoli | Low-latency speaker recognition | Francesco Salani | |
| 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 | |
| Audio forensics | Bestagini | Speaker-Independent Microphone Identification via Blind Channel Estimation in Noisy Condition | Antonio Giganti | |
| 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 |
| Audio Processing | Sarti, Giampiccolo, Bernardini | Parallel Wave Digital Implementations of Nonlinear Audio Circuits | Natoli Antonino | |
| 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 |