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

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

Abstract: Landslides are among the most common natural disasters globally, posing significant threats to human society. In recent years, deep learning (DL) has been widely applied to rapid landslide ...

Bu proje, iki görüntü arasındaki değişiklikleri otomatik olarak tespit eden ve sınıflandıran bir derin öğrenme modelidir. Siamese U-Net mimarisi kullanılarak geliştirilmiştir ve PyTorch framework'ü ...

1 Ambam Computer Science and Application Laboratory & Department of Computer Engineering, Higher Institute of Transport, Logistics and Commerce, University of Ebolowa, Ebolowa, Cameroon. 2 Institut ...

Introduction: Fish keypoint detection is a prerequisite for accurate fish behavior analysis and biomass weight estimation, and is therefore crucial for efficient and intelligent offshore aquaculture.

Accurate and timely detection of diabetic retinopathy (DR) is crucial for managing its progression and improving patient outcomes. However, developing algorithms to analyze complex fundus images ...