Publication of the 2nd Edition of From Human Attention to Computational Attention

This volume,edited by Matei Mancas, Vincent P. Ferrera, and Antoine Coutrot, ,offers a multidisciplinary overview of advances in attention modeling, blending psychological foundations, neuroscientific approaches, and innovations in artificial intelligence. The first edition established the basis for saliency models; this new edition addresses the integration of attentional mechanisms within deep neural networks (attention modules, transformers, Grad-CAM) and explores parallels between brain architectures and deep learning designs.

Interdisciplinary contributions feature experts in cognitive psychology, computational neuroscience, signal engineering, and computer science.

Highlights:

• Foundations of attention and signal-detection models
• Experimental validation and real-world applications (images, video, multimodal)
• Attention mechanisms within DNNs and biomimetic opportunities
• Future perspectives on neuroscience–AI convergence

Digital Access (PDF/EPUB)
Download the PDF or EPUB now via https://link.springer.com/book/10.1007/978-3-031-84300-6

Keywords:
Attention Modeling • Saliency Models • Neural Networks • Deep Learning • Computational Neuroscience • Biomimetics