Deep learning detects foodborne bacteria within three hours by eliminating debris misclassifications

Researchers have significantly enhanced an artificial intelligence tool used to rapidly detect bacterial contamination in food by eliminating misclassifications of food debris that looks like bacteria ...
Frontiers

Deep learning–based approaches for weed detection in crops

Deep learning has become a transformative technology for modern weed detection, offering significant advantages over traditional machine vision in robustness, scalability, and recognition accuracy.
Beebom

What is CNN in Deep Learning? The AI Behind Computer Vision

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 ...
Frontiers

Automated predictive framework using AI and deep learning approaches for early detection and classification of liver cancer

1 Department of General Surgery, Shangyu People’s Hospital of Shaoxing, Shaoxing, Zhejiang, China 2 Center of Gallbladder Disease, Shanghai East Hospital, Institute of Gallstone Disease, School of ...
C&EN

Deep Learning-Based Shape Classification for Hyperspectral-Imaged Microplastics

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
IEEE

IMed-CNN: Ensemble Learning Approach With Systematic Model Dropout for Enhanced Medical Image Classification Using Image Channels and Pixel Intervals

Abstract: To obtain light ensemble model through clearly explained effective ensemble member selection and finding data representation in various valuable forms are major challenges in medical image ...
IEEE

Satellite Image Classification Using Deep Learning

Abstract: Satellite images have become a vital resource in a variety of fields, including environmental monitoring, urban planning, and disaster management. The adoption of deep learning algorithms ...