Radio waves enable energy-efficient AI on edge devices without heavy hardware

As drones survey forests, robots navigate warehouses and sensors monitor city streets, more of the world's decision-making is ...

A Visual Model Of Self-Attention: Transformers Work Differently Now

Early-2026 explainer reframes transformer attention: tokenized text becomes Q/K/V self-attention maps, not linear prediction.
IEEE

Enhancing Task-Incremental Learning via a Prompt-Based Hybrid Convolutional Neural Networks (CNNs)-Vision Transformer (ViT) Framework

Abstract: Artificial neural network (ANN) models are widely used in various fields such as image classification, multi-object detection, intent prediction, military applications, and natural language ...
IEEE

Transformer-Based Deep Learning for Mesoscale Eddy Detection in Sea Surface Temperature Maps

Abstract: Mesoscale eddies are dynamic oceanic phenomena significantly influencing marine ecosystems’ energy transfer, nutrients, and biogeochemical cycles. These eddies’ precise identification and ...