When designing computer vision technology, there's a real fork in the road as to whether a company should use facial data for ...

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 ...

Sufi K Sulaiman Joins 1cPlatform as CTO, Taking the Helm to Shape the Company’s Next Era of Intelligent Automation and ...

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, ...