Abstract: This study investigates the use of lightweight deep learning models for classifying operational states of hydrocyclones in a copper mining process. A diverse data set was curated by ...

The training and validation scripts are based on timm's repository and have been adapted to work with our DiDiCM approach. The DiDiRN architecture is built upon the ResNet design for a fair comparison ...

Abstract: Text recognition in natural scene images is a challenging problem in computer vision. Different than the optical character recognition (OCR), text recognition in natural scene images is more ...

This repository aims at reproducing the results from "CBAM: Convolutional Block Attention Module". We use the module coinjointly with the ResNet CNN architecture. The module is tested on the CIFAR10 ...

Artificial intelligence can now generate images that are virtually indistinguishable from real ones. Researchers at the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation ...

A stunningly concentrated and hefty galaxy cluster, from a time in the universe's history when such massive structures aren't expected to have fully formed yet, is challenging cosmic evolution ...

A Supreme Court ruling on geofence warrants may influence legal challenges to Flock license plate readers over privacy ...

Researchers have produced the most detailed map yet of how stem cells in the growing tip of a plant begin their journey to form the many cell types that shape flowers and stems. They identified 18 ...

Deep learning has transformed remote sensing, driving state-of-the-art results in land use and land cover classification, ...

Conclusions The optimized ResNet-18 achieved accurate and stable MH staging using OCT images under a standardized training framework. Compared with deeper CNN and Transformer-based architectures, the ...