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Full Description
Computational Intelligence in Image and Video Processing presents introduction, state-of-the-art and adaptations of computational intelligence techniques and their usefulness in image and video enhancement, classification, retrieval, forensics and captioning. It covers an amalgamation of such techniques in diverse applications of image and video processing.
Features:
A systematic overview of state-of-the-art technology in computational intelligence techniques for image and video processing
Advanced evolutionary and nature-inspired approaches to solve optimization problems in the image and video processing domain
Outcomes of recent research and some pointers to future advancements in image and video processing and intelligent solutions using computational intelligence techniques
Code snippets of the computational intelligence algorithm/techniques used in image and video processing
This book is primarily aimed at advanced undergraduates, graduates and researchers in computer science and information technology. Engineers and industry professionals will also find this book useful.
Contents
1.Text Information Extraction from Digital Image Documents Using Optical Character Recognition. 2. Extracting the Pixel Edges on Leaves to Detect Type using Fuzzy Logic. 3. Water Surface Waste Object Detection and Classification. 4. A Novel Approach for Weakly Supervised Object Detection Using Deep Learning Technique. 5. Image Inpainting Using Deep Learning. 6. Watermarking in Frequency Domain Using Magic Transform. 7. An Efficient Lightweight LSB Steganography with Deep learning Steganalysis. 8. Rectum Cancer Magnetic Resonance Image Segmentation. 9. Detection of Tuberculosis in Microscopy Images using Mask Region Convolutional Neural Network. 10. Comparison of Deep Learning Methods for COVID-19 Detection Using Chest X-ray. 11. Video Segmentation and Compression. 12. A Novel DST-SBPMRM-Based Compressed Video Steganography Using Transform Coefficients of Motion Region. 13. Video Matting, Watermarking and Forensics. 14. Time Efficient Video Captioning Using GRU, Attention Mechanism and LSTM. 15. Nature-Inspired Computing for Feature Selection and Classification. 16. Optimized Modified K-Nearest Neighbor Classifier for Pattern Recognition. 17. Role of Multi-objective Optimization in Image Segmentation and Classification.
