GAN-Based SteRGAN Hides Secret Images Inside Cover Images With High Fidelity
Researchers propose SteRGAN, a GAN-based image steganography framework that achieves PSNR values above 41 dB on ImageNet and Microsoft COCO.
Researchers propose SteRGAN, a GAN-based image steganography framework that achieves PSNR values above 41 dB on ImageNet and Microsoft COCO.
A systematic review finds that vision-based touchless gesture recognition systems, despite laboratory accuracies above 95%, lose 1 to 23 percentage ...
Researchers built a dual-stream deep learning framework that localizes and classifies facial emotions and binary gender labels together, achieving 94.56% ...
A multinational cohort study using temporal deep learning identified deteriorating walking time as the strongest predictor of dual cognitive-physical decline ...
A systematic review and meta-analysis finds pooled sensitivity of 85.4 percent and specificity of 83.5 percent for deep learning-assisted low-dose ...
A retrospective multicentre study reports that a deep learning model combining three time-point chest CT scans predicted MDR-TB treatment outcomes ...
A physics-informed TS-Mixer neural network predicted measured PEM fuel cell stack power with an R-squared of 0.969 on a 497-hour ...
A retrospective deep learning prototype called XceptionAttnV1 processes multiple data types for oral cavity squamous cell carcinoma but has not ...
A music-aware transformer framework combining multi-scale spectrogram learning and adaptive attention optimization reported accuracies of 93.5%, 99.2%, and 97.1% on ...
A transfer learning framework classified neonatal seizures from EEG topographic maps, with ResNet-18 reaching 97.1 percent subject-wise accuracy on unseen ...
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© 2025 Scienmag - Science Magazine