Computer Vision and Image Analysis for Industry 4.0 [Paperback]

1. A Benchmark Dataset for Document Level Offline Bangla Handwritten Text Recognition (HTR) and Line Segmentation. 2. A New Approach Using Convolutional Neural Network for Crops and Weeds Classification. 3. Lemon Fruits Detection and Instance Segmentation Under Orchard Environment Using Mask R-CNN and YOLOv5. 4. A Deep Learning Approach in Detailed Fingerprint Identification. 5. Probing Skin Lesions and Performing Classification of Skin Cancer Using Efficient Net while Resolving Class Imbalance Using SMOTE. 6. Advanced Grad CAM: Improved Visual Explanations of CNNs decision in Diabetic Retinopathy. 7. Bangla Sign Language Recognition Using Concatenated BDSL Network. 8. Chest Xray Net: A Multi-class Deep Convolutional Neural Networks for Detecting Abnormalities in Chest X-Ray Images. 9. Achieving Human Level Performance on the Original Omniglot Challenge. 10. A Real-Time Classification Model for Bengali Character Recognition in Air-Writing. 11. A Deep Learning Approach for Covid-19 Detection in Chest X-Rays. 12. Automatic Image Captioning Using Deep Learning. 13. A Convolutional Neural Network Based Approach to Recognize Bangla Handwritten Characters. 14. Flood Region Detection Based on K-Means Algorithm and Color Probability. 15. Fabrication of Smart Eye Controlled Wheelchair for Disabled Person.

Nazmul Siddique is with the School of Computing, Engineering and Intelligent Systems, Ulster University. He obtained Dipl.-Ing. degree in Cybernetics from the Dresden University of Technology, Germany, MSc in Computer Science from Bangladesh University of Engineering and Technology and PhD in Intelligent Control from the Department of Automatic Control and Systems Engineering, University of Sheffield, England. His research interests include: cybernetics, computational intelligence, nature-inspired computing, stochastic systems and vehicular communication. He has published over 170 research papers l'