Abstract: The safe and reliable operation of power systems relies on the intelligent operation and maintenance (O&M) of substations. However, multi-robot collaborative inspection, an essential ...
Researchers at Osaka Metropolitan University have discovered a practical way to detect and fix common labeling errors in ...
Abstract: This research suggests a strong framework for automated malaria detection using a Convolutional Neural Network (CNN) model. The dataset, sourced from Kaggle, consists of 27,558 ...
Abstract: The computing power network(CPN), as a current research hotspot, aims to provide users with reliable, efficient, and secure computing capabilities. However, research on the routing algorithm ...
The BCTVNet neural network provides accurate and rapid target volume delineation for cervical cancer brachytherapy ...
Abstract: Orthogonal Frequency Division Multiplexing (OFDM) enables high-rate data transmission wards wirelss broadband connections. Accurate channel estimation continues to be an unsolved issue in ...
Abstract: Plant diseases have important consequences for livelihoods and economies, both on local and global scales, whereby the spread of plant pathogens can lead to high levels of damage to ...
Multimodal Learning, Deep Learning, Financial Statement Analysis, LSTM, FinBERT, Financial Text Mining, Automated Interpretation, Financial Analytics Share and Cite: Wandwi, G. and Mbekomize, C. (2025 ...
Tested across eight lettuce types, the system successfully visualizes pigment spatial distribution from individual leaves to full canopies, offering a ...
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 ...
Abstract: Brain tumors are among the deadliest diseases worldwide and require early and accurate diagnosis via Magnetic Resonance Imaging (MRI). Deep learning techniques, particularly convolutional ...