Hardware fragmentation remains a persistent bottleneck for deep learning engineers seeking consistent performance.
A new study published in Big Earth Data demonstrates that integrating Twitter data with deep learning techniques can ...
(NASDAQ: NXXT ), a pioneer in AI-driven energy innovation transforming how energy is produced, managed, and delivered, today ...
Abstract: In industrial scenarios, the scarcity of labeled data for fault diagnosis of rotating machinery poses a significant challenge to the development of reliable data-driven models. This paper ...
CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...
The electrocardiogram (ECG) is an important tool for exploring the structure and function of the heart due to its low cost, ease of use, efficiency, and non-invasive nature. With the rapid development ...
Abstract: Beforehand and accurate error discovery of the power system is important to maintain system stability, help tool damage, and insure dependable performance ...
YOLOv8-Seg: a deep learning approach for accurate classification of osteoporotic vertebral fractures
1 Department of Orthopedics, Suzhou Ninth People’s Hospital, Suzhou, Jiangsu, China 2 Department of Orthopedics, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China ...
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 ...
A team of scientists in the United States has combined both spatial and temporal attention mechanisms to develop a new approach for PV inverter fault detection. Training the new method on a dataset ...
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