GitHub

PyTorch CNN Architecture Experimentation on Mini-ImageNet with Model Interpretability

This project presents a comprehensive deep learning study focused on Convolutional Neural Network (CNN) architecture experimentation and model interpretability using the Mini-ImageNet dataset. The ...
Fierce Healthcare

How Imagenet balances AI and human judgment in payer operations

Healthcare payers face mounting pressure to lower costs, manage complex claims and meet regulatory requirements without compromising service quality. In this video interview, Imagenet CEO Greg Carnes ...
GitHub

Question about training efficientvit classification model on imagenet-22k dataset

Thanks for your great work! I plan to train efficientvit classification model on imagenet-22k dataset for a better backbone initialization for open vocabulary object detection. I know that the ...
IEEE

Comprehensive Evaluation of ImageNet-Trained CNNs for Texture-Based Rock Classification

Abstract: Texture perception plays a vital role in various fields, from computer vision to geology, influencing object recognition, image segmentation, and rock classification. Despite advances in ...
Scientific Research Publishing

Krizhevsky, A., Sutskever, I. and Hinton, G.E. (2012) ImageNet Classification with Deep Convolutional Neural Networks. In: Advances in Neural Information Processing Systems ...

ABSTRACT: Breast cancer is a deadly disease and radiologists recommend mammography to detect it at the early stages. This paper presents two types of HanmanNets using the information set concept for ...
Scientific Research Publishing

Krizhevsky, A., Sutskever, I. and Hinton, G.E. (2017) Imagenet Classification with Deep Convolutional Neural Networks. Communications of the ACM, 60, 84-90.

ABSTRACT: The development of artificial intelligence (AI), particularly deep learning, has made it possible to accelerate and improve the processing of data collected in different fields (commerce, ...