1st Edition
Object Detection with Deep Learning Models Principles and Applications
Object Detection with Deep Learning Models discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval.
The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks.
Features:
- A structured overview of deep learning in object detection
- A diversified collection of applications of object detection using deep neural networks
- Emphasize agriculture and remote sensing domains
- Exclusive discussion on moving object detection
Editors............................................................................................................................................. vii
List of Contributors.........................................................................................................................ix
1. Introduction: Deep Learning and Computer Vision......................................................1
A.S. Renugadevi
2. Object Detection Frameworks and Services in Computer Vision.............................23
Sachi Choudhary, Rashmi Sharma, and Gargeya Sharma
3. Real-Time Tracing and Alerting System for Vehicles and Children to Ensure
Safety and Security, Using LabVIEW..............................................................................49
R. Deepalakshmi and R. Vijayalakshmi
4. Mobile Application-based Assistive System for Visually Impaired People:
A Hassle-Free Shopping Support System......................................................................65
E. Ramanujam and M. Manikandakumar
5. Traffic Density and On-road Moving Object Detection Management, Using
Video Processing.................................................................................................................81
Ankit Shrivastava and S. Poonkuntran
6. Automated Vehicle Number Plate Recognition System, Using Convolution
Long Short-Term Memory Technique...........................................................................101
S. Srinivasan, D. Prabha, N. Mohammed Raffic, K. Ganesh Babu,
S. Thirumurugaveerakumar, and K. Sangeetha
7. Deep Learning-based Indian Vehicle Number Plate Detection and
Recognition......................................................................................................................... 117
M. Arun Anoop, S. Poonkuntran, and P. Karthikeyan
8. Smart Diabetes System Using CNN in Health Data Analytics................................137
P. Ravikumaran, K. Vimala Devi, and K. Valarmathi
9. Independent Automobile Intelligent Motion Controller and Redirection,
Using a Deep Learning System......................................................................................165
S. Aanjanadevi, V. Palanisamy, S. Aanjankumar, S. Poonkuntran, and P. Karthikeyan
10. Deep Learning Solutions for Pest Detection...............................................................179
C. Nandhini and M. Brindha
11. Deep Learning Solutions for Pest Identification in Agriculture..............................199
Monika Vyas, Amit Kumar, and Vivek Sharma
12. A Complete Framework for LULC Classification of Madurai Remote
Sensing Images with Deep Learning-based Fusion Technique...............................215
T. Gladima Nisia and S. Rajesh
13. Human Behavioral Identifiers: A Detailed Discussion.............................................237
T. Suba Nachiar, T. Shanmuga Priya, P.R. Hemalatha, and J.V. Anchitaalagammai
Index..............................................................................................................................................253
Biography
Poonkuntran Shanmugam earned a BE degree in Information Technology from Bharathidasan University, Tiruchirapalli, India; and MTech and PhD degrees in Computer and Information Technology from Manonmaniam Sundaranar University, Tirunelveli, India. He is presently with VIT Bhopal University, Madhya Pradesh, India as Professor & Dean for the School of Computing Science and Engineering. He has more than a decade of experience in teaching and research and successfully executed three funded research grant projects from the Indian Space Research Organization, Defense Research Development Organization, and Ministry of New and Renewable Energy, Government of India, to the tune of 1.10 Crores. He received two seminar grants from Anna University, Chennai, and the All India Council for Technical Education-Indian Society for Technical Education for the tune of 4 Lacs. He has published more than 80 technical publications, authored 6 books and 2 chapters. He is the recipient of Cognizant Best Faculty Award 2017–18 and served as a State Level Student Coordinator for Region VII, CSI, India in 2016–17. He is a lifetime member of IACSIT, Singapore, CSI, India, and ISTE, India. His research areas of interests include information security, computer vision, artificial intelligence, and machine learning.
Dr Rajesh Kumar Dhanraj is a Professor in the School of Computing Science and Engineering at Galgotias University, Greater Noida, India. He earned a BE degree in Computer Science and Engineering from the Anna University Chennai, India in 2007, then an MTech from the Anna University Coimbatore, India in 2010 and a PhD in Computer Science from Anna University, Chennai, India, in 2017. He has contributed to 30+ authored and edited books on various technologies, 21 Patents and 53 articles and papers in various refereed journals and international conferences and contributed chapters to books. His research interests include Machine Learning, Cyber-Physical Systems and Wireless Sensor Networks. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE), member of the Computer Science Teacher Association (CSTA), and the International Association of Engineers (IAENG). He is an associate editor and guest editor for reputed journals. He is an Expert Advisory Panel Member of Texas Instruments Inc., USA.
Balamurugan Balusamy is currently an Associate Dean Student in Shiv Nadar University, Delhi-NCR. Prior to this assignment he was Professor, School of Computing Sciences & Engineering and Director of International Relations at Galgotias University, Greater Noida, India. His contributions focus on Engineering Education, Block Chain and Data Sciences. His Academic degrees and twelve years of experience working as a faculty member in a global University like VIT University, Vellore, has made him more receptive and prominent in his domain. He has 200 plus high impact factor papers in Springer, Elsevier and IEEE. He has done more than 80 edited and authored books and collaborated with eminent professors across the world from top QS ranked universities. Prof. Balamurugan Balusamy has served up to the position of associate professor in his 12 years stint with VIT University, Vellore. He completed his Bachelors, Masters and PhD degrees at top premier institutions in India. His passion is teaching, and he adapts different design thinking principles while delivering his lectures. He has published 80+ books several top-notch conferences in his resume and has published over 200 quality journal articles, conferences and book chapters combined. He serves in the advisory committee for several start-ups and forums and does consultancy work for industry on Industrial IOT. He has given over 195 talks at various events and symposiums.
