IEEE

Sports Image Classification Using Deep Learning Models

Abstract: This research explores a deep learning-based approach to sports image classification using four convolutional neural network (CNN) models: VGG-16, VGG-19, Xception, and EfficientNetB7. The ...
IEEE

Efficient Document Image Classification Using Deep Learning Enhance with CNN Architectures

Abstract: Document image classification has a significant difficulty for the retrieval of digital documents and systems management in recent years. The main goal of this study is to investigate the ...
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

YOLOv8-Seg: a deep learning approach for accurate classification of osteoporotic vertebral fractures

This study investigates the application of a deep learning model, YOLOv8-Seg, for the automated classification of osteoporotic vertebral fractures (OVFs) from computed tomography (CT) images. A ...
Scientific Research Publishing

Hem-CNN: An Efficient Intracranial Hemorrhage Detection Model Using Explainable Deep Learning in Head CT Scan Images ()

1 Department of Computer Science, American International University-Bangladesh (AIUB), Dhaka, Bangladesh. 2 Department of Electrical and Electronics Engineering, American International ...
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 ...
GitHub

Cone Detection Using Deep Learning for Formula Student Driverless

This project presents a complete workflow for cone detection in Formula Student Driverless scenarios using deep learning. It demonstrates how to use MATLAB® and Simulink® for data preparation and ...