A sine-guided Transformer–CNN network significantly outperformed 21 comparison methods on three benchmark datasets for salient-object detection in optical remote-sensing imagery.
A three-stage CNN and transformer pipeline identified satellite image types and detected oil with high reported accuracy, while a lightweight ...
A systematic review of 168 primary studies found that 57.14% did not examine the performance–faithfulness relationship, 41.07% reported synergy and ...
A new study demonstrates that AI-powered photomicroscopes can accurately identify invasive Agrilus beetles, enhancing EU phytosanitary surveillance and enabling rapid ...
A new PLOS One study reports a Harris Hawks-optimized bilateral segmentation deep learning network that detects wild animals with 99.8 ...
A new study in Scientific Reports introduces a hybrid framework using variable fuzzy sets and convolutional neural networks to assess ...
A neural architecture search framework called CMS-NAS automatically evolves hybrid convolutional, Mamba and spiking network designs for lightweight, accurate EEG-based ...
A controlled study of four frontier chatbots building helmet-detection models finds that the most detailed prompts can trigger catastrophic training ...
A systematic review of thirteen studies covering nearly six million patients finds that deep learning models can extract mortality and ...
A systematic review maps how deep learning architectures are transforming EEG analysis for neurological disease diagnosis, while warning that data ...
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