A Husqvarna researcher developed a fast, interpretable PV hotspot-detection method using IR thermography and Lab* color-space features instead of heavy neural networks, achieving up to 95.2% accuracy ...
Abstract: The unfolding global trajectory of COVID-19 has made it abundantly clear that scalable, accurate diagnostic solutions, especially in resource-limited healthcare settings, are urgently ...
A research team from Peking University has successfully developed a vanadium oxide (VO₂)-based “locally active memristive ...
WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning BEIJING, Jan. 05, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the ...
Investing.com -- WiMi Hologram Cloud Inc. (NASDAQ:WIMI) stock surged 11.3% on Monday after the company announced the launch of its independently developed Quantum Convolutional Neural Network for ...
Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...
Syntiant Corp., the recognized leader in ultra-low-power edge AI deployment, today announced two new package options for its NDP115 Neural Decision Processor(TM), extending the chip's reach into ...
Morning Overview on MSN
Tesla’s rear-braking system beats ultrasonic-equipped cars in a head-to-head
Tesla has spent years arguing that a camera‑centric approach to driver assistance can match or surpass the performance of ...
A hybrid model combining LM, GA, and BP neural networks improves TCM's diagnostic accuracy for IPF, achieving 81.22% ...
Graph neural networks in Alzheimer's disease diagnosis: a review of unimodal and multimodal advances
Alzheimer's Disease (AD), a leading neurodegenerative disorder, presents significant global health challenges. Advances in graph neural networks (GNNs) offer promising tools for analyzing multimodal ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
Introduction: Emotion recognition based on electroencephalogram (EEG) signals has shown increasing application potential in fields such as brain-computer interfaces and affective computing. However, ...
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