As manipulated videos become increasingly difficult to detect with the naked eye, a new study presents an artificial ...
Government-funded academic research on parallel computing, stream processing, real-time shading languages, and programmable ...
Deep learning is a subset of machine learning that uses multi-layer neural networks to find patterns in complex, unstructured data like images, text, and audio. What sets deep learning apart is its ...
Traditional machine learning (TML) algorithms remain indispensable tools for the analysis of biomedical images, offering significant advantages in multimodal data integration, interpretability, ...
Abstract: In recent years, deep learning (DL) systems have been applied in many areas, including image processing and autonomous driving. Software testing is an important way to ensure the quality of ...
IFAP generates adversarial perturbations using model gradients and then shapes them in the discrete cosine transform (DCT) domain. Unlike existing frequency-aware methods that apply a fixed frequency ...
ABSTRACT: Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management. Conventional asset pricing models, such as the Fama-French three-factor ...
Abstract: Image denoising is a key component of digital image processing systems. The latest advances in deep learning have led to significant improvements in denoising techniques, particularly ...
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