Cervical cancer detection and diagnosis are undergoing a transformation with the integration of advanced deep learning (DL) technologies. Despite ...
The idea of these so-called perception-driven systems is to interpret raw sensor data and convert it into actionable understanding. So, they capture the images as traditional machine vision would, but ...
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: Visual recognition in low-light environments is a challenging problem since degraded images are the stacking of multiple degradations (noise, low light and blur, etc.). It has received ...
A deep learning system can accurately detect vision-threatening diabetic retinopathy. A dual-modality, deep learning system can accurately detect vision-threatening diabetic retinopathy (vtDR) using ...
This study introduces Popnet, a deep learning model for forecasting 1 km-gridded populations, integrating U-Net, ConvLSTM, a Spatial Autocorrelation module and deep ensemble methods. Using spatial ...
Researchers have developed a deep learning model called LSTM-SAM that predicts extreme water levels from tropical cyclones more efficiently and accurately, especially in data-scarce coastal regions, ...
Abstract: Functional and technical requirements for the interfaces between algorithms and learning frameworks (including the interfaces provided by training frameworks), and between algorithms and ...
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