Adaptive method helps light-based quantum processors act more like neural networks

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...
DMR News

Minkang Zhang Improves Medical Image Recognition Through RNN Optimization and Deep Learning Integration

The exponential increase in medical imaging data has intensified the need for accurate and efficient diagnostic analysis. Conventional methods often fail to ...
Nature

This AI combo could unlock human-level intelligence

Blending ‘old-fashioned’ logic systems with the neural networks that power large language models is one of the hottest trends ...
eLife

CNN-based learning of single-cell transcriptomes reveals a blood-detectable multi-cancer signature of brain metastasis

This important study describes a deep learning framework that analyzes single-cell RNA data to identify a tumor-agnostic gene signature associated with brain metastases. The identified signature ...
IEEE

DSNet: Dynamic Stitchable Neural Network for Hyperspectral Image Classification

Abstract: Hyperspectral image classification (HSIC) aims to identify land-cover categories by leveraging the spectral and spatial information contained in hyperspectral images (HSIs). Currently, many ...
IEEE

Binary Neural Networks With Feature Information Retention for Efficient Image Classification

Abstract: Although binary neural networks (BNNs) enjoy extreme compression ratios, there are significant accuracy gap compared with full-precision models. Previous works propose various strategies to ...
C&EN

A Reconfigurable Silicon Transistor for Noise-Resilient Stochastic Spiking Neural Networks

School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea Graduate School of Semiconductor Technology, ...