arXiv:2410. 16089v2 Announce Type: replace Abstract: The unique cost, flexibility, speed, and efficiency of modern UAVs make them an attractive choice in many applications in contemporary society.
Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.
arXiv:2606. 11687v1 Announce Type: cross Abstract: Unmanned Aerial Vehicle (UAV) threats have emerged as a defining security challenge of the 21st century.
In this study, UAV multispectral imagery is used to segment the severity of bacterial leaf blight (BLB) in rice using convolutional neural networks (CNNs) and transformer-based models. The evaluated architectures include U-Net with a ResNet- 101 encoder, U-Net++ with EfficientNet-B3 and EfficientNetB7, DeepLabV3+, and SegFormer, all trained under a common pipeline with three input configurations (multispectral only, multispectral+NDVI, and multispectral+NDRE).
arXiv:2607. 03131v1 Announce Type: cross Abstract: Modern video surveillance systems generate far more video streams than human operators can effectively monitor, making automated analysis essential for timely detection of security events.
arXiv:2607. 16455v1 Announce Type: new Abstract: The increasing use of first-person-view drones in modern conflicts has created a demand for compact and reliable detection systems capable of operating in complex electromagnetic environments.
arXiv:2606. 27886v1 Announce Type: new Abstract: Recent advances in Human Activity Recognition (HAR) from wearable sensors have shown that multi-modal deep learning models consistently outperform their uni-modal counterparts.
arXiv:2606. 14963v1 Announce Type: cross Abstract: Timely and accurate disaster damage assessment is crucial for effective emergency response, resource allocation, and recovery.