Computer Vision and Machine Intelligence (eBook, PDF)

Proceedings of CVMI 2022
Redaktion: Tistarelli, Massimo; Jiang, Xiaoyi; Singh, Satish Kumar; Dubey, Shiv Ram

• Format: PDF

Produktbeschreibung

This book presents selected research papers on current developments in the fields of computer vision and machine intelligence from International Conference on Computer Vision and Machine Intelligence (CVMI 2022). The book covers topics in image processing, artificial intelligence, machine learning, deep learning, computer vision, machine intelligence, etc. The book is useful for researchers, postgraduate and undergraduate students, and professionals working in this domain.

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Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 777
• Erscheinungstermin: 5. Mai 2023
• Englisch
• ISBN-13: 9789811978678
• Artikelnr.: 67932925

Autorenporträt

Prof. Massimo Tistarelli received the Ph.D. in Computer Science and Robotics in 1991 from the University of Genoa. He is Full Professor in Computer Science and Director of the Computer Vision Laboratory at the University of Sassari, Italy. Since 1986, he has been involved as Project Coordinator and Task Manager in several projects on computer vision and biometrics funded by the European Community. Prof. Tistarelli is Founding Member of the Biosecure Foundation, which includes all major European research centers working in biometrics. His main research interests cover biological and artificial vision, pattern recognition, biometrics, visual sensors, robotic navigation, and visuo-motor coordination. He is one of the world-recognized leading researchers in the area of biometrics, especially in the field of face recognition and multimodal fusion. He is Co-author of more than 150 scientific papers in peer-reviewed books, conferences, and international journals. He is Principal Editor for the Springer books "Handbook of Remote Biometrics" and "Handbook of Biometrics for Forensic Science". Prof. Massimo organized and chaired several world-recognized several scientific events and conferences in the area of Computer Vision and Biometrics, and he has been Associate Editor for several scientific journals including IEEE Transactions on PAMI, IET Biometrics, Image and Vision Computing and Pattern Recognition Letters. Since 2003, he is Founding Director for the Int. Summer School on Biometrics (now at the 17th edition). He is Fellow Member of the IAPR, Senior Member of IEEE, and Vice President of the IEEE Biometrics Council. Dr. Shiv Ram Dubey has been with IIIT Allahabad since July 2021, where he is currently Assistant Professor of Information Technology. He was with the IIIT Sri City as Assistant Professor from December 2016 to July 2021 and Research Scientist from June 2016 to December 2016. He received the Ph.D. degree in IIIT Allahabad in 2016. Before that, from August 2012 to February 2013, he was Project Officer in the CSE at IIT Madras. Currently, Dr. Dubey is executing the research project funded by Global Innovation and Technology Alliance (GITA)-India-Taiwan project. He has also executed the projects funded by DRDO Young Scientist Lab in Artificial Intelligence (DYSL-AI) and Science and Engineering Research Board (SERB). He was Recipient of several awards including Best Ph.D. Award in Ph.D. Symposium, IEEE-CICT2017 at IIITM Gwalior, and NVIDIA GPU Grant Award Twice from NVIDIA. He received the Outstanding Certificate of Reviewing Award from Information Fusion, Elsevier, in 2018. He was also involved in the organization of Springer's CVIP conference in 2020 and 2021. He is serving as Associate Editor in SN Computer Science Journal. He is also involved in reviewing papers in top-notch journals, such as IEEE TNNLS, IEEE TIP, IEEE SPL, IEEE TAI, IEEE TMM, IEEE TGRS, MTAP, and SiVP and conferences such as WACV, ACMMM, ICME, ICVGIP, and CVIP. Hisresearch interest includes computer vision, deep learning, convolutional neural networks, generative adversarial networks, stochastic gradient descent optimizers, image retrieval, image-to-image transformation, etc. Dr. Satish Kumar Singh is with the Indian Institute of Information Technology Allahabad India, as Associate Professor at the Department of Information Technology from 2013 and heading the Computer Vision and Biometrics Lab (CVBL). Before joining the IIIT Allahabad, he served the Department of Electronics and Communication Engineering, Jaypee University of Engineering and Technology Guna, India, from 2005 to 2012. His areas of interest include image processing, computer vision, biometrics, deep learning, and pattern recognition. He is Senior Member of IEEE. Presently, Dr. Singh is Section Chair IEEE Uttar Pradesh Section. Dr. Singh has also been involved as Editor in several journals and conferences, including Springer's Neural Computing and Applications, Springer Nature Computer Science, IET-Image Processing, Springer's CVIP 2020, CICT 2018, UPCON 2015, etc. Dr. Singh is also Technical Committee Affiliate of IEEE SPS IVMSP and MMSP and presently Chairperson, IEEE Signal Processing Society Chapter of Uttar Pradesh Section. Prof. Xiaoyi Jiang received the Bachelor's degree from Peking University, Beijing, China, and the Ph.D. and Venia Docendi (Habilitation) degrees from the University of Bern, Bern, Switzerland, all in Computer Science. He was Associate Professor with the Technical University of Berlin, Berlin, Germany. Since 2002, he has been Full Professor with the University of Münster, Münster, Germany, where he is currently Dean of the Faculty of Mathematics and Computer Science. His current research interests include biomedical imaging, 3D image analysis, and structural pattern recognition. Dr. Jiang is Editor-in-Chief of the International Journal of Pattern Recognition and Artificial Intelligence. He also serves on the Advisory Board and the Editorial Board of several journals, including IEEE Transactions on Medical Imaging and International Journal of Neural Systems. He is Senior Member of IEEE and Fellow of IAPR.

Inhaltsangabe

Efficient Voluntary Contact-Tracing System & Network for COVID-19 Patients using Sound Waves and Predictive Analysis using K-Means.- Direct De Novo Molecule Generation using Probabilistic Diverse Variational Autoencoder.- Automated Molecular Subtyping of Breast Cancer Through Immunohistochemistry Image Analysis.