DynIMTS replaces static graphs with instance-attention that updates edge weights on the fly, delivering SOTA imputation and P12 classification ...

Researchers developed an Ag/Sb2O3/Au memristor array that mimics brain-like computing, performing on-device image feature extraction with low power consumption, promising smarter and faster electric ...

This is the official PyTorch implementation of the paper "WaveDSNet: Wavelet Dynamic Convolution with Dual-Stream Synergistic Fusion Network for SAR Water Change Detection". This project proposes an ...

Abstract: Dilated convolution is a powerful technique for expanding the receptive field without increasing the convolution kernel size, making it highly valuable in image segmentation tasks. However, ...

New issue New issue Closed Closed Dynamic Convolution Support #2536 Core ML FrameworkAn issue related to the Core ML Framework ...

Consumers love a good deal. But what they don't like is when a price is different for each consumer, a concept known as surge, variable, or dynamic pricing. According to a new NerdWallet study, which ...

Forbes contributors publish independent expert analyses and insights. Neil Sahota is a globally sought after speaker and business advisor. In the digital economy, companies continuously seek ...

In modern machine learning and artificial intelligence frameworks, transformers are one of the most widely used components across various domains including GPT series, and BERT in Natural Language ...

In recent years, computer vision has made significant strides by leveraging advanced neural network architectures to tackle complex tasks such as image classification, object detection, and semantic ...

ABSTRACT: A lightweight malware detection and family classification system for the Internet of Things (IoT) was designed to solve the difficulty of deploying defense models caused by the limited ...