Scientific Research Publishing

Kumar, P., Singh, R. and Das, M. (2022) Energy-Efficient Sensor Networks for IoT-Based Livestock Monitoring: A Power Optimization Approach. Internet of Things in Agriculture, 9 ...

ABSTRACT: The rising global demand for livestock products requires innovative, data-driven approaches to enhance animal welfare and operational efficiency. Conventional livestock monitoring techniques ...
IEEE

RNGCNs: Robust Norm Graph Convolutional Networks in the Presence of Missing Data and Large Noises

Abstract: Graph Convolutional Networks (GCNs) have been widely studied for attribute graph data learning. In many applications, graph node attributes/features may contain various kinds of noises, such ...
pv magazine International

PV module fault diagnosis uses convolutional neural network

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...
Forbes

Security Graphs Explained: An Innovative Approach To Network Security

Imagine standing atop a mountain, gazing at the vast landscape below, trying to make sense of the world around you. For centuries, explorers relied on such vantage points to map their surroundings.
EurekAlert!

Real-time, large-scale graph neural network inference through BingoCGN

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...
IEEE

Graph Kolmogorov–Arnold Convolutional Network for Hyperspectral Image Classification

Abstract: The graph neural network (GNN) exhibits noteworthy performance in hyperspectral image classification (HSIC) due to its efficient message-passing structure, which employs the multilayer ...