Mitchell traces the evolution of AI from Alan Turing’s early ideas to modern systems. The book explores language, images, and ...

Cervical cancer detection and diagnosis are undergoing a transformation with the integration of advanced deep learning (DL) technologies. Despite ...

Abstract: Visual Convolutional Multi-head Attention (VCMA), a groundbreaking architecture within the realm of deep learning, ingeniously fuses the strengths of Convolutional Neural Networks (CNN) and ...

Overview AI systems use sensors and computer vision to detect pests and diseases early, reducing crop damage and yield losses.Real-time data analysis helps farm ...

February 13, 2026. This webinar describes how Deep Learning methods can be used for object detection and segmentation in high resolution drone imagery using ArcGIS Pro.

Abstract: In this study, a visualization teaching platform based on deep learning algorithms is designed and implemented to address the problems of abstract concepts and esoteric theories in linear ...

Abstract: The deep learning framework for facial emotion recognition (FER) using a convolutional neural network (CNN) architecture is described in this research. The model uses data augmentation and ...

Abstract: In unknown environments, achieving autonomous navigation for uncrewed aerial vehicles (UAVs) is a complex task. Ensuring that UAVs reach their destinations safely and efficiently remains a ...

Abstract: Change detection in remote sensing (RS) images typically involves processing and analyzing RS images of the same geographic location captured at different times to identify changes. In ...

Abstract: Cybersecurity risks have evolved in the linked digital terrain of today into more complex, frequent, and varied forms. Conventional intrusion detection systems sometimes find it difficult to ...