eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
IEEE

Image Processing and Machine Learning for Hyperspectral Unmixing: An Overview and the HySUPP Python Package

Abstract: Spectral pixels are often a mixture of the pure spectra of the materials, called endmembers, due to the low spatial resolution of hyperspectral sensors, double scattering, and intimate ...

Image SEO for multimodal AI

Images are now parsed like language. OCR, visual context and pixel-level quality shape how AI systems interpret and surface ...
IEEE

AMT-Net: Adversarial Motion Transfer Network With Disentangled Shape and Pose for Realistic Image Animation

Abstract: Computer vision advancements allow motion transfer for animating static objects in images. However, current methods rely on manually collected motion labels and struggle with accurate shape ...