Nature

Crop-weed classification using deep learning: a comparative study of CNNs, vision transformers, and interpretable models

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...
GitHub

kentaroy47/vision-transformers-cifar10

This is your go-to playground for training Vision Transformers (ViT) and its related models on CIFAR-10/CIFAR-100, a common benchmark dataset in computer vision. The whole codebase is implemented in ...
IEEE

Structural Approach to Convolutional Neural Network Trained With Novel Scaled Matrix Image for Pseudo Real-Time Power Quality Event Monitoring

Abstract: The trend of integrating different distributed generation sources into the existing grid have increased the probability of power quality disturbances to a threatening level. Eventually, ...

New framework renders AI more trustworthy for cancer subtyping

Medical artificial intelligence (AI) faces a fundamental challenge: uncertainty quantification. Artificial neural networks ...
IEEE

A Novel Multi-Branch Channel Expansion Network for Garbage Image Classification

Abstract: Due to the lack of data available for training, deep learning hardly performed well in the field of garbage image classification. We choose the TrashNet data set which is widely used in the ...