Bücher von Gagan Deep

This book introduces Relational Markov Networks (RMN¿s) for Collective Information Extraction. Also, an attempt has been made to improve the performance of Relational Markov Network using Approximate Inference Procedure such as Gibbs Sampling for Collective Information Extraction. Gibbs Sampling has been used for making the performance of LT-RMN¿s better than CRF¿s for Collective Information Extraction.

Dr. Gagandeep received his Bachelor¿s degree in Computer Science and Engineering from Punjab Technical University, Jalandhar, Punjab, India in 2002, M.E. degree in Computer Science and Engineering from PEC University of Technology, Chandigarh, India, in 2005 and Ph.D. degree in Computer Engineering from Panjabi university, Patiala, India, in 2017. Presently, he works in Department of Computer Science & Engineering, Chandigarh Engineering College (CEC), Landran, Mohali, India as faculty member and has several years work experience in the areas of teaching. He has published more than 40 research papers in leading journals, conference proceedings and books including Elsevier, IEEE, Taylor n Francis and Springer and also holds 23 patents. He is also life member of several societies, received prestigious Academia award from CSI consecutively in 2011 & 2012 and also received ISTE best teacher award in 2016. His current research interests include medical image processing, object detection, semantic retrieval, deep learning.