Abstract: The UC Merced (UCM) land use dataset is a widely adopted benchmark for evaluating aerial image classification algorithms. This paper presents a comparative performance analysis of prominent ...

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 ...

This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, and RandLA-Net— on a Flash Lidar dataset. The ...

Traditional machine learning (TML) algorithms remain indispensable tools for the analysis of biomedical images, offering significant advantages in multimodal data integration, interpretability, ...

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 ...

This repository contains Python notebooks demonstrating image classification using Azure AutoML for Images. These notebooks provide practical examples of building computer vision models for various ...

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

The significant contributions of this work are threefold. First, it leverages deep learning to extend in vivo imaging depth of two-photon excitation fluorescence microscopy, far beyond the depths ...