Attention-Boosted Neural Networks Face Off in the Hunt for Deepfakes
A controlled comparison shows attention-enhanced DenseNet121 reaching 97.4 percent accuracy for deepfake detection while a lighter MobileNetV2 variant offers a ...
A controlled comparison shows attention-enhanced DenseNet121 reaching 97.4 percent accuracy for deepfake detection while a lighter MobileNetV2 variant offers a ...
A multimodal AI model called ERF-BA-TFD+ detects and localizes audio-visual deepfakes by cross-reconstructing audio and video features and reasoning over ...
A new adversarial training method called MI-MKGC dynamically balances text, image, and structural information to predict missing facts in multimodal ...
Researchers in India have developed a generative adversarial framework that synthesizes realistic radar micro-Doppler spectrograms, lifting human activity recognition accuracy ...
A systematic review of 93 studies reveals eight attack types and nine defence types across six categories of unsupervised machine ...
Researchers have built Inklude, a two-stage AI framework that recognizes sketches drawn in mid-air and transforms them into stylized clay-like ...
A new scientometric review maps the rapid rise of research combining genetic algorithms with generative adversarial networks, revealing explosive growth ...
A comprehensive new survey documents how reinforcement learning has become a foundational tool for aligning image, video, and 3D generative ...
A comprehensive new survey in Multimedia Tools and Applications maps deepfake generation techniques from GANs to diffusion models and finds ...
A new survey maps the full landscape of instruction-based image editing, from GAN origins to diffusion and autoregressive systems, and ...
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© 2025 Scienmag - Science Magazine