PATTERN RECOGNITION AND COMPUTER VISION IN THE NEW AI ERA

While traditional approaches in pattern recognition and computer vision have continued to evolve, along with the advances of artificial intelligence (AI), this unique compendium presents recent research activities in deep learning, graph-based and semantic-based approaches and applications.

The book covers the most recent advances as well as traditional topics in pattern recognition and computer vision in this new AI area in the first part. The second part presents emerging applications of deep learning and AI.

This useful reference text benefits academics, professionals, researchers and graduate students in pattern recognition, computer vision, image segmentation and artificial intelligence.

Contents:

• Theory and Applications:
  • Interpreted Graphs — A Formal Tool for Syntactic Pattern Recognition: Properties and Applications (Mariusz Flasiński)
  • 2D and 3D Detection of Counterfeit Coins (Mahsa Vahed, Ching Yee Suen, and Wei-Ping Zhu)
  • A Survey of RGB-D-Based Semantic Segmentation (Feng Zhou, Ju Dai, Shaoyan Xia, Paul L Rosin, and Yu-Kun Lai)
  • Quantum Computing for Remote Sensing Image Analysis (Edoardo Pasetto, Amer Delilbasic Morris Riedel, Gabriele Cavallaro, and Jón Atli Benediktsson)
  • Hopfield Neural Networks for Seismic Velocity Picking (Kou-Yuan Huang and Jia-Rong Yang)
  • Graph Neural Networks for Moving Objects Detection in Videos (Wieke Prummel, Jhony Giraldo, Anastasia Zakharova, and Thierry Bouwmans)
  • Graph Signal Processing and Markovian Modeling for Unsupervised SAR Image Segmentation (Marco Trombini, David Solarna, Gabriele Moser, and Silvana Dellepiane)
  • New Methods for New Space: Multi-Sensor Change Detection in Remote Sensing Imagery (Amanda Ziemann and Zigfried Hampel-Arias)
  • Differential Geometry in Graph-Based Data Analysis for Pattern Recognition (Alexandre L M Levada)
  • Reliable Multi-layer Segmentation of Breast Ultrasound (BUS) Images (Kuan Huang, Yingtao Zhang, Heng-Da Cheng, and Ping Xing)
  • Digital Twin in Healthcare and Medical Fields: A Review (Dengyi Liu, Honggang Wang, Xin Xiang, and Hua Fang)
  • PCA and Binary Particle Swarm Optimization (BPSO) in ANFIS for Rule-Based Reduction for Low-Dimensional Data (Uvais Qidwai and Afnan Al-Ali)
  • LinAlign: X-Ray Image Alignment Before and After Hip Arthroplasty (Cheng-Wei Lin, Alexander Yurusov, Hsiao-Ning Chen, and Chiou-Shann Fuh)
• Emerging Deep Learning and AI Applications:
  • Deep Learning in Hierarchical Models and Feature Representation (Bichuan Shen)
  • Performance Comparison of Recent Advances in Query-Based Video Instance Segmentation (Alain P Ndigande and Sedat Ozer)
  • Applications of Information Geometry Driven Deep Learning (Branko Brkljač and Marko Janev)
  • Efficient Deep Learning for Key Challenges in Person Re-identification (Arindam Sikdar and Ananda S Chowdhury)
  • Deep Learning for Action Spotting in Association Football Videos (Silvio Giancola, Anthony Cioppa, Bernard Ghanem, and Marc Van Droogenbroeck)
  • Local Change Detection From Video Scene: An End-to-End Encoder–Decoder-Type Deep Neural Network Architecture with Feature Pooling (Manoj Kumar Panda, Badri Narayan Subudhi, Thierry Bouwmans, T Veerakumar, and Vinit Jakheytiya)
  • Image Segmentation Using Deep Learning (Shervin Minaee, Yuri Boykov, Fatih Porikli, Antonio Plaza, Nasser Kehtarnavaz, and Demetri Terzopoulos)
  • ChatGPT vs Google Search on Drones (Hoi Kei Phoebe Chan and Ching Yee Suen)

Readership: Researchers, professionals, academics and graduate students in pattern recognition, computer vision and AI.