Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).

Dual-color live-cell super-resolution imaging of mitochondria (green) and endoplasmic reticulum (magenta). Compared to the standard SN2N method, the proposed Adaptive-SN2N (aSN2N) framework ...

Abstract: This paper presents an optimized lightweight Super-Resolution Convolutional Neural Network (SRCNN) capable of reconstructing high-quality images with strong fidelity. The proposed framework ...

Ultrasound guidance is widely used in lumbar regional anesthesia and chronic pain management because it provides radiation-free, portable, and real-time visualization. Among lumbar ultrasound views, ...

In recent years, breakthroughs in imaging have changed our ability to study the brain, providing a variety of modalities with varying resolution, penetration, and sensitivity. In neuropharmacology, ...

In a world of wild talk and fake news, help us stand up for the facts.

Abstract: We propose a deep learning method for single image super-resolution (SR). Our method directly learns an end-to-end mapping between the low/high-resolution images. The mapping is represented ...

Apple tends to keep most of its convenient features, like AirDrop, locked to its own hardware, but this is also what allows its products to offer some of the best security features in the space.

DeepSeek’s announced OCR (Optical Character Recognition) model compresses text-heavy data into images and reduces vision tokens per image by up to 20x while retaining 97% accuracy (10x compression) or ...

Cybersecurity professionals recognize that enterprise networks are prime targets for dark web risks such as ransomware, unauthorized insider activity, and data exfiltration. What’s less obvious is ...