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.