Everything changes with time. Some changes happen so rapidly — like 7 frames or more per second — that we perceive them as ...
Abstract: In recent years, object detection utilizing both visible (RGB) and thermal infrared (IR) imagery has garnered extensive attention and has been widely implemented across a diverse array of ...
This project showcases a sophisticated pipeline for object detection and segmentation using a Vision-Language Model (VLM) and the Segment Anything Model 2 (SAM2). The core idea is to leverage the ...
Abstract: Uncrewed aerial vehicle (UAV) aerial visible–infrared [RGB-thermal (RGBT)] object detection has been widely applied in fields such as military operations and rescue missions. However, ...
2 Methodology 2.1 Overall framework design YOLO11 (Khanam and Hussain, 2024, preprint) is a new generation of object detection algorithm developed by Ultralytics based on the YOLOv8 architecture. It ...
We use Python 3.8, PyTorch 1.13.1 (CUDA 11.7 build). The codebase is built on Detectron. conda create -n wsco python=3.8 Conda activate wsco conda install pytorch==1.12.1 torchvision==0.13.1 ...
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