IEEE

Removal Then Selection: A Coarse-to-Fine Fusion Perspective for RGB-Infrared Object Detection

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 ...
IEEE

Phrase Grounding-Based Style Transfer for Single-Domain Generalized Object Detection

Abstract: Single-domain generalized object detection aims to enhance a model’s generalization to multiple unseen target domains using only data from a single source domain during training. This is a ...
IEEE

Lightweight Multiscale Feature Fusion and Multireceptive Field Feature Enhancement for Small Object Detection in the Aerial Images

Abstract: Small uncrewed autonmous vehicles (UAVs) equipped with deep learning models are increasingly used to detect small objects both on the ground and in aerial environments. Since small objects ...
IEEE

A Patch-Based CNN Approach for Object Detection Using RGB and NIR Image Fusion

Abstract: This study explores the fusion of RGB and NearInfrared (NIR) images for object detection. Three fusion techniques, such as RedSwap, Heatmap, and the proposed NIRR Difference, were evaluated ...
IEEE

Spatial-Frequency Collaborative Learning for Camouflaged Object Detection

Abstract: Camouflaged object detection (COD) is a challenging task that struggles to accurately detect the objects concealed in the surrounding environment. This is largely attributed to the intrinsic ...
IEEE

Weakly Supervised Object Detection for Aerial Images with Instance-aware Label Assignment

Abstract: Weakly supervised object detection has emerged as a cost-effective and promising solution in remote sensing, as it requires only image-level labels and alleviates the burden of ...
IEEE

Ensemble of Fast R-CNN with Bi-LSTM for Object Detection

Abstract: Object detection is a critical task in computer vision, with applications ranging from autonomous driving to medical imaging. Traditional object detection models, such as Fast R-CNN, have ...
IEEE

A Comparative Evaluation of YOLOv7, Faster R-CNN and RetinaNet on MS COCO Dataset

Abstract: This paper presents an end-to-end approach to object detection using the YOLOv7 architecture, evaluated on the MS COCO dataset. MS COCO offers over 200,000 annotated images spanning 80 ...
IEEE

Adaptive Receptive Field Network for Small Objects Detection in Remote Sensing Images

Abstract: Small object detection in remote sensing images is severely hampered by the significant scale variation even among small objects. Conventional methods often rely on a static receptive field ...
IEEE

TRAM: Transformer-Based Mask R-CNN Framework for Underwater Object Detection in Side-Scan Sonar Data

Abstract: Accurate detection and segmentation of underwater objects in side-scan sonar (SSS) imagery remain challenging due to noise, cluttered backgrounds, and low-contrast conditions. In this paper, ...
IEEE

TCINet: Transformer–CNN Interaction Network for Space Noncooperative Object Saliency Detection

Abstract: Space noncooperative object detection (SNCOD) is an essential part of space situation awareness. The localization and segmentation capabilities of the salient object detection (SOD) method ...
IEEE

Mask R-CNN with HRNet Backbone for Person Detection Evaluation on COCO Using mIoU and Threshold Optimization

Abstract: A crucial computer vision problem is person detection, but real-world challenges including crowded backgrounds, inconsistent lighting, and object occlusion require accurate and robust models ...