AI That Shows Its Work: Explainable Deep Learning Spots Crop Pests in Real Time
Researchers have unveiled an explainable deep learning framework that detects insect crop pests in real time with up to 98 ...
Researchers have unveiled an explainable deep learning framework that detects insect crop pests in real time with up to 98 ...
Egyptian researchers have built a MATLAB simulation framework combining LSTM-based water demand prediction with solar energy management, achieving simulated water ...
Researchers have developed a trajectory-free, semi-supervised anomaly detection framework that monitors entire hen flocks through statistical activity and density cues, ...
A comprehensive review finds that AI, IoT sensors, remote sensing and precision fertilisation can dramatically raise nitrogen use efficiency, yield ...
A new Bentham Books reference volume examines how high-performance computing, artificial intelligence, cloud technologies and cybersecurity can converge to build ...
Researchers in Morocco have integrated federated learning with the OneM2M IoT service layer, showing faster, privacy-preserving machine learning at the ...
A new scientometric and BERTopic-based analysis of 3,262 publications reveals how artificial intelligence research has converged with the United Nations ...
A new collaborative perception framework pairs a lightweight detection network with a foundation segmentation model to help robotic harvesters locate ...
A new Data Trust Unit framework shows that degraded data credibility can silently consume up to 48 percent of a ...
Researchers at Anhui Agricultural University have developed DE-TabNet, a semi-supervised AI model that detects sensor faults in smart drip irrigation ...
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© 2025 Scienmag - Science Magazine