M.Sc. Purbaditya Bhattacharya

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Raum:
117
Telefon:
+49-40-6541-2552
Fax:
+49-40-6541-2834
Besucheranschrift
Helmut-Schmidt-Universität
Gebäude H3
Holstenhofweg 85
22043 Hamburg
Postanschrift
Helmut-Schmidt-Universität
Fakultät für Elektrotechnik
Allgemeine Nachrichtentechnik
Postfach 70 08 22
22008 Hamburg

  • Faltungs Neurale Netze Anwendungen

 

cnnapp

  • Entrauschen
  • Superauflösungen

 

SRDN

 

  • Video Stabilisierung

 

stabilize

 

  • Objekt Detektion
  • Wal (Harbour Porpoise) Klassifizierung

Detektion

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

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.

HSU

Letzte Änderung: 10. Oktober 2020