Computer Vision and Image Analysis for Industry 4.0

Computer Vision and Image Analysis for Industry 4.0 portes grátis

Computer Vision and Image Analysis for Industry 4.0

Dewan, M. Ali Akber; Arefin, Mohammad Shamsul; Siddique, Nazmul; Ahad, Md Atiqur Rahman

Taylor & Francis Ltd

12/2024

197

Mole

Inglês

9781032187624

15 a 20 dias

Descrição não disponível.
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 CNN's 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.
automated image processing;medical image classification;document segmentation techniques;orchard fruit detection;skin cancer analysis;sign language recognition;advanced convolutional neural network applications