Methods and Applications of Deep and Machine Learning Models including GAN

This book offers a rich compilation of cutting-edge research showcasing the transformative power of deep learning and machine learning in addressing real-world challenges. From enhancing medical diagnostics and precision agriculture to improving image resolution and sentiment analysis, each chapter blends theoretical depth with practical relevance. Featuring advanced neural architectures-including GANs, transformers, attention modules, and hybrid models-the volume covers topics such as URGAN-based image enhancement, pneumonia detection using a fusion of EfficientNetV2, CBAM, BreastNet, and ViT, transformer-driven crop disease diagnosis, sentiment stratification, and geospectral weather forecasting via recursive networks. Authored by researchers from Kalinga Institute of Industrial Technology and partner institutions, this work serves as a valuable resource for scholars, practitioners, and students aiming to harness AI for impactful solutions.