Special Issue

Computer Vision and Deep Learning: Trends and Applications

The aim of this Special Issue is to discuss the latest innovations in deep learning technologies applied to computer vision and image processing contexts also from a software development company perspective. The Special Issue will be focused on: No-Code Deep Learning—TinyDL—Full-stack Deep Learning—General Adversarial Networks (GAN)—Unsupervised and self-supervised DL—Reinforcement Learning Few Shot —One Shot, and Zero Shot Learning

Advances in Hyperspectral imaging, sensing and its Applications: Precision Agriculture and Fire Prevention

The goal of this Special Issue is to collect the latest developments in the application fields of precision agriculture and fire preventions. Both these two contexts were traditionally on-field tests for computer vision-based algorithms and methodologies. With the growing availability of hyperspectral sensors—that are more effective compared to multispectral remote ones—the approach to fire prevention and precision agriculture is quite different, providing an unexpected and powerful support to workers. Papers on the latest research challenges, case studies and on-field applications, limitations, and advantages of different platforms and sensors as well as future perspectives are welcomed.