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 ...
Frontiers

Advancing standardized cattle behavior classification with a random forest model evaluated across diverse datasets

The lack of precise, autonomous tools for monitoring and classifying cattle behavior limits farmers’ ability to make proactive and informed decisions regarding grazing and herd management. Currently, ...
Princeton University

In the hallways of Princeton, a fascination with the human mind unlocked the power of deep learning

When Fei-Fei Li arrived in Princeton in January 2007 as an assistant professor, she was assigned an office on the second floor of the computer science building. Her neighbor was Christiane Fellbaum.
GitHub

A Benchmark Video Dataset for Retinal Detachment and Macular Status Classification in Ocular Ultrasound

Eye Retinal DEtachment UltraSound (ERDES) is a comprehensive, open-access video dataset designed to advance computer vision research in ocular ultrasonography. Ocular ultrasound is a fast, ...
Frontiers

Sustainable deep vision systems for date fruit quality assessment using attention-enhanced deep learning models

Accurate and automated fruit classification plays a vital role in modern agriculture but remains challenging due to the wide variability in fruit appearances. In this study, we propose a novel ...
News Medical

Scientists develop new system for classifying processed foods

Recent years have seen growing scrutiny and debate around processed foods, but researchers have struggled to pin down what aspects of food processing are most relevant to health. Now, scientists have ...
IEEE

Comparison of COVID-19 Classification via Imagenet-Based and RadImagenet-Based Transfer Learning Models with Random Frame Selection

Abstract: Transfer learning methods are used in lung ultrasound (US) video classification as the training data for learning is generally limited. However, transfer learning models trained on the ...