Dr. Shri Prakash Dwivedi is an esteemed researcher and academic in the field of Computer Science and Engineering, specializing in pattern recognition, graph matching, and algorithms. He is currently serving as an Assistant Professor in the Department of Information Technology at G.B. Pant University of Agriculture & Technology, Pantnagar, where he has been actively involved in teaching and research. Dr. Dwivedi obtained his Ph.D. in Computer Science and Engineering from the Indian Institute of Technology (BHU), Varanasi, where he worked on graph matching algorithms for structural pattern recognition. Prior to that, he earned his M.E. in Computer Science from the Indian Institute of Science (IISc), Bangalore. Dr. Dwivedi has published extensively in leading journals and conferences, including Pattern Recognition Letters, Springer's Lecture Notes in Computer Science, Lecture Notes in Electrical Engineering, ACM and IEEE. His work primarily focuses on error-tolerant graph matching, similarity measure, approximate algorithms, and computational methods in structural pattern recognition. Beyond academia, Dr. Dwivedi has industry experience as a Software Engineer (R&D) at various software companies, where he worked on scientific computing, algorithm design, and software development. He has also contributed to research projects integrating IoT and cloud-based automation systems. A recipient of several accolades, Dr. Dwivedi secured All India Rank 1 in GATE 2006 and has been a holder of the MHRD Scholarship for his academic excellence. Dr. Ravi Shankar Singh is working as an Associate Professor in the Department of Computer Science and Engineering, Indian Institute of Technology (BHU) Varanasi, India and has an academic background of B.Tech.(CSE), M.Tech.(CSE) and Ph.D.(CSE). He has been a Senior Member of IEEE and ACM. More than 50 research papers have been included in his account. His research interests include high-performance and cloud computing.
Inhaltsangabe
1. Introduction 2. Structural Pattern Recognition 3. Graph Matching Algorithms: A Survey 4. Graph Matching using Extensions to Graph Edit Distance 5. Graph Matching using Centrality Measures 6. Geometric Graph Matching 7. Graph Kernels and Embedding 8. Graph Matching in Image Analysis 9. Graph Matching in Social Network Analysis 10. Recent Advances and Future Directions. A. Graph Matching Tools Bibliography Index
