The increasing complexity of modern chemical engineering processes presents significant challenges for timely and accurate anomaly detection. Traditional ...

The autonomous station's integration of hardware and AI architecture offers a significant departure from static CCTV setups ...

The field of computer vision has witnessed significant advancements in recent years, driven by the development of deep learning models and the availability of large-scale datasets. However, despite ...

convolutional neural network based detectors have dramatically improved the detection performance, but enormous parameters make it difficult to realize model lightweighting. Recently, DETR and its ...

AlexNet revolutionized the use of neural networks for computer vision, creating one of the underpinnings of generative AI.

School of Information Science and Engineering, Hebei University of Science and Technology, 26 Yuxiang Street, Shijiazhuang, Hebei Province 050018, P. R. China ...

In this paper, we take a different perspective on feature aggregation, and propose a dynamic graph contrastive network (DGC-Net) for video object detection, including three improvements against ...

Abstract Remote sensing object detection (RSOD) faces formidable challenges in complex ... To address these challenges, we propose LEGNet, a lightweight network that incorporates a novel edge-Gaussian ...

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas ...