Forschung
Deep Learning
- Faltungs Neurale Netze Anwendungen
Bild/Video Verbesserung
- Entrauschen
- Super-resolution
- Video Stabilisierung
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Wal Erkennung
- Objekt Detektion
- Wal (Harbour Porpoise) Klassifizierung
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Drohnendetektion von Bilder/Video im 5G-Netz
- Übertragung der Bilddaten via 5G-Campusnetz
- Drohnendetektion im Bilder (RGB/ Infrarot) mit deep learning
- Teilprojekt innerhalb des dtec.bw-Projektes – Digitale Sensor-2-Cloud Campus-Plattform
Betreute Abschlussarbeit
Mahesh Sulugodu Manjunatha – Semantic Segmentation using Convolutional Neural Networks, Masterarbeit
Chetan Mara – Ground Truth Data Generation for Image Segmentation with CNN, Studienarbeit
Shashikant Kulkarni – Preprocessing Methods for Image Segmentation with CNN, Studienarbeit
Savan Rangeggowda – Scene Segmentation with Convolutional Neural Networks, Masterarbeit
Carl Henning Cabos – Application of Convolutional Neural Networks for Pitch Detection, Masterarbeit
Chetan Mara – A Convolutional Neural Network for Video Stabilization, Masterarbeit
Shashikant Kulkarni – Convolutional Neural Networks for Image and Video Compression, Masterarbeit
Pascal Hampel – Classification of EMNIST Dataset with a Convolutional Neural Network, Bachelor Studienarbeit
Aswin Sampath Kumar – Neural Network Architectures for the Calculation of Psychoaccoustic Metrics, Masterarbeit
Pascal Hampel – Comparison of State-of-the-art Object Detectors for Airborne Use-cases, Bachelorarbeit
Subhashini Madhavan – Image Denoising using Deep Learning, Studienarbeit
Elif Göksügür – Individualization of HRTFs with CNNs Based on Anthropometric Features, Masterarbeit
Cem Aygün – Classification of Handwritten Numbers and Letters using Convolutional Neural Network, Studienarbeit
Praveen Krishna Murthy – Deep Learning based Pitch Detection, Masterarbeit
Prathima Krishna Subramanian – Noise Level Estimation in Images with Convolutional Neural Network, Studienarbeit
Arunachalam Thirunavukkarasu – Speech Denoising using Convolutional Neural Network, Studienarbeit
Lehre
Multimedia-Signalverarbeitung
Veröffentlichungen / Tagung
- P. Bhattacharya, P. Nowak: Drone Detection and Tracking with YOLO and a Rule-based Method, ArXiv, https://doi.org/10.48550/arXiv.2502.05292
- U. Zölzer, P. Nowak, P. Bhattacharya: MATLAB Competition : Audio Plug-In Development, 2024 AES Conference, Madrid, Spainien
- P. Bhattacharya, P. Nowak, D. Ahlers, U. Zölzer: A Dataset of Infrared Images for Deep Learning based Drone Detection, in 17th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), Bangkok, Thailand, 8-10 November, 2023
- D. Ahlers, P. Bhattacharya, P. Nowak, U. Zölzer: Shore Livecams: A Maritime Dataset for Deep Learning based Object Detection, in 17th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), Bangkok, Thailand, 8-10 November, 2023
- E. Gerat, P. Bhattacharya, U. Zölzer: A Differentiable Digital Moog Filter for Machine Learning Applications, in 26th International Conference on Digital Audio Effects (DAFx23), Kopenhagen, Dänemark, 4-7 September, 2023
- P. Bhattacharya, P. Nowak, D. Ahlers, M. Holters, U. Zölzer: CNN based Drone Detection in Infrared Images, in dtec. bw – Band 1, Hamburg, Deutschland, 2022
- U. Zölzer, P. Nowak, P. Bhattacharya, Room Simulation, Digital Audio Signal Processing, 3rd Edition, Ch. 7, J. Wiley & Sons, 2022
- U. Zölzer, P. Bhattacharya, Audio Coding, Digital Audio Signal Processing, 3rd Edition, Ch. 9, J. Wiley & Sons, 2022
- P. Bhattacharya, P. Nowak, U. Zölzer, Machine Learning for Audio, Digital Audio Signal Processing, 3rd Edition, Ch. 11, J. Wiley & Sons, 2022
- P. Bhattacharya: Deep Learning for Image Enhancement, Universitätsbibliothek der HSU/UniBwH, Hamburg, Deutschland, Mai, 2022
- P. Bhattacharya, U. Zölzer: Attentive Inception Module based Convolutional Neural Network for Image Enhancement, Digital Image Computing: Techniques and Applications (DICTA), Melbourne, Australien, 29. Nov – 2. Dez, 2020
- P. Bhattacharya, P. Nowak, U. Zölzer: Optimization of cascaded parametric peak and shelving filters with backpropagation algorithm, 23rd International Conference on Digital Audio Effects (DAFx), Wien, Österreich, 9-11 September, 2020.
- P. Bhattacharya, U. Zölzer: Convolutional Neural Network with Inception Blocks for Image Compression Artifact Reduction, International Joint Conference on Neural Networks (IJCNN-WCCI), Glasgow, Schottland, 19-24 Juli, 2020.
- P. Bhattacharya, U. Zölzer: A Convolutional Neural Network with Two-Channel Input for Image Super-Resolution, International Joint Conference on Neural Networks (IJCNN), Budapest, Ungarn, 14-19 Juli, 2019.
- P. Bhattacharya, S.Wulf, U. Zölzer: Detection of Harbour Porpoise with Low-level Feature Extraction and Deep Learning based Classification, 14th International Conference on Signal-Image Technology & Internet-Based Systems, SITIS, Las Palmas de Gran Canaria, Spanien, 26-29 November, 2018.
- P. Bhattacharya, J.Riechen, U. Zölzer: Infrared Image Enhancement in Maritime Environment with Convolutional Neural Networks, 13th International Conference on Computer Vision Theory and Applications, VISAPP (VISIGRAPP), Madeira, Portugal, 27-29 Januar, 2018.
- P. Bhattacharya, G. Simkus, C. de Obaldía, A. Kelm, U. Zölzer: Convolutional Neural Networks for Digital Signal Processing, (Poster), LSA2017 – Lübeck Summer Academy on Medical Technology, Juli 2017, Lübeck, Deutschland.
- P. Rivera Benois, P. Bhattacharya, U. Zölzer: Derivation Technique for Headphone Transfer Functions Based on Sine Sweeps and Least Squares Minimization, Proceedings of the 45th International Congress and Exposition on Noise Control Engineering, INTER-NOISE, Hamburg, Deutschland, 21-24 August, 2016.
Letzte Änderung: 4. März 2025