Learn what CNN is in deep learning, how they work, and why they power modern image recognition AI and computer vision ...
Abstract: This letter presents a novel convolutional neural network (CNN)-based methodology for robust and accurate open-circuit fault detection and submodule (SM) localization in modular multilevel ...
Abstract: Object detection in autonomous driving scenarios represents a significant research direction within artificial intelligence. Real-time and accurate object detection and recognition are ...
A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN integration. It improves dynamic lesion detection, temporal ...
We’re introducing SAM 3 and SAM 3D, the newest additions to our Segment Anything Collection, which advance AI understanding of the visual world. SAM 3 enables detection and tracking of objects in ...
Visualization examples of YOLOv10-N/S, YOLO11-N/S, YOLOv12-N/S, and YOLOv13-N/S. Representative visualization examples of adaptive hyperedges. The hyperedges in the first and second columns mainly ...
Researchers at Queen Mary University of London and University College London have found that humans can detect objects buried in sand without directly touching them. The discovery challenges the ...
Abstract: Camouflaged object detection (COD) is a challenging task that struggles to accurately detect the objects concealed in the surrounding environment. This is largely attributed to the intrinsic ...
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