Lightweight AI at the Network Edge Spots Attacks in Milliseconds
A new study combines a lightweight MobileNetV2 model with edge computing to detect network attacks with 94.6 percent accuracy in ...
A new study combines a lightweight MobileNetV2 model with edge computing to detect network attacks with 94.6 percent accuracy in ...
A new cross-modality knowledge distillation framework uses CT-derived feature supervision to boost chest X-ray classification of lung diseases by up ...
Researchers in Türkiye combined transfer learning with MobileNetV2, Xception, and classical classifiers to classify five rice varieties with up to ...
Researchers have developed a lightweight deep learning framework that grades early sugarcane pokkah boeng disease severity on a smartphone with ...
A standardized benchmark of six convolutional neural networks shows that the most accurate pneumonia-detecting models also produce the most faithful ...
A controlled comparison shows attention-enhanced DenseNet121 reaching 97.4 percent accuracy for deepfake detection while a lighter MobileNetV2 variant offers a ...
Researchers in India have developed a generative adversarial framework that synthesizes realistic radar micro-Doppler spectrograms, lifting human activity recognition accuracy ...
A new study combines transfer learning, quantitative explainable AI, and drone-based tile-grid spray mapping to target pesticide application in pepper, ...
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© 2025 Scienmag - Science Magazine