- Gebundenes Buch
- Merkliste
- Auf die Merkliste
- Bewerten Bewerten
- Teilen
- Produkt teilen
- Produkterinnerung
- Produkterinnerung
This comprehensive text/ book presents a broad review of both traditional (i.e., conventional) and the deep learning aspects of object detection in various adversarial conditions of real-world in a clear, insightful, and highly comprehensive style.
Andere Kunden interessierten sich auch für
- Artificial Intelligence and Machine Learning for Smart Community132,99 €
- Computational Accelerator Physics 2003412,99 €
- The Role of Sustainability and Artificial Intelligence in Education Improvement153,99 €
- Innovation in the University 4.0 System Based on Smart Technologies175,99 €
- Optical Computing466,99 €
- Mathematical Optics263,99 €
- Soft Computing Principles and Integration for Real-Time Service-Oriented Computing220,99 €
-
-
-
This comprehensive text/ book presents a broad review of both traditional (i.e., conventional) and the deep learning aspects of object detection in various adversarial conditions of real-world in a clear, insightful, and highly comprehensive style.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 190
- Erscheinungstermin: 7. März 2024
- Englisch
- Abmessung: 234mm x 156mm x 13mm
- Gewicht: 500g
- ISBN-13: 9781032551807
- ISBN-10: 1032551801
- Artikelnr.: 69485495
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 190
- Erscheinungstermin: 7. März 2024
- Englisch
- Abmessung: 234mm x 156mm x 13mm
- Gewicht: 500g
- ISBN-13: 9781032551807
- ISBN-10: 1032551801
- Artikelnr.: 69485495
Mrinal Kanti Bhowmik earned a Bachelor of Engineering (BE) degree in Computer Science and Engineering from the Tripura Engineering College, Government of Tripura, in 2004, a Master of Technology (M.Tech) degree in Computer Science and Engineering from Tripura University (A Central University), India, in 2007, and a PhD in Engineering from Jadavpur University, Kolkata, India, in 2014. He has also spent the Fall 2022 session as a DST-SERB International Research Experience (SIRE) Scholar with SIRE Fellowship, sponsored by the Science and Engineering Research Board (SERB), Government of India at the NYU Center for Cybersecurity (CCS), Tandon School of Engineering, New York University, New York City. He has successfully completed two Department of Electronics and Information Technology (DeitY) (Now Ministry of Electronics and Information Technology [MeitY])-funded projects, one Department of Biotechnology (DBT)-Twinning project, one Society for Applied Microwave Electronics Engineering and Research (SAMEER)-funded project, one Indian Council of Medical Research (ICMR) project, and one Defence Research and Development Organisation (DRDO) project as the Principal Investigator. He is currently the Principal Investigator of one Department of Biotechnology (DBT)-funded project and Co-Principal Investigator of one Indian Council of Medical Research (ICMR) project in collaboration with All India Institute of Medical Sciences (AIIMS), New Delhi. Since July 2010, he has served with the Department of Computer Science and Engineering, Tripura University as an Assistant Professor and from 26th March, 2023 he has been serving with Department of Computer Science and Engineering, Tripura University as an Associate Professor. He was awarded the Short Term Indian Council of Medical Research (ICMR), Department of Health Research (DHR) International Fellowship from 2019 to 2020 as a Senior Indian Biomedical Scientist for bilateral cooperation in cross-disciplinary research area (i.e., biomedical diagnostic and inferencing systems). His research team has also designed two datasets for object detection in degraded vision named Extended Tripura University Video Dataset (E-TUVD) and Tripura University Video Dataset at Night time (TU-VDN) dataset for the research community in the proposed domain of object detection. His current research interests are in the fields of computer vision, security and surveillance, medical imaging, and image and video forensics.
1. Fundamentals of Object Detection 2. Background of Degradation 3. Imaging
Modalities for Object Detection 4. Real Time Benchmark Datasets for Object
Detection 5. 6. Visibility Enhancement of Images in Degraded Vision 7.
Object Detection in Degraded Vision 8. Hands-on Practical for Object
Detection Approaches in Degraded Vision
Modalities for Object Detection 4. Real Time Benchmark Datasets for Object
Detection 5. 6. Visibility Enhancement of Images in Degraded Vision 7.
Object Detection in Degraded Vision 8. Hands-on Practical for Object
Detection Approaches in Degraded Vision
1. Fundamentals of Object Detection 2. Background of Degradation 3. Imaging
Modalities for Object Detection 4. Real Time Benchmark Datasets for Object
Detection 5. 6. Visibility Enhancement of Images in Degraded Vision 7.
Object Detection in Degraded Vision 8. Hands-on Practical for Object
Detection Approaches in Degraded Vision
Modalities for Object Detection 4. Real Time Benchmark Datasets for Object
Detection 5. 6. Visibility Enhancement of Images in Degraded Vision 7.
Object Detection in Degraded Vision 8. Hands-on Practical for Object
Detection Approaches in Degraded Vision