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 ...
Abstract: Slender objects in remote sensing, such as bridges and trains, represent a unique yet under-researched target because of their extreme aspect ratios. This characteristic presents challenges ...
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, ...
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 ...
Abstract: Existing robotic grasp detection methods often struggle with inaccurate predictions in complex scenarios involving multiple objects and textured backgrounds. Most existing methods attempt to ...
Abstract: A Convolutional Neural Network (CNN) are a class of artificial neural networks specifically designed to process data with a grid-like topology, such as images, making them well-suited for ...
Abstract: Camouflaged object detection (COD) is challenging for both human and computer vision, as targets often blend into the background by sharing similar color, texture, or shape. While many ...
Abstract: Small object detection in uncrewed aerial vehicle (UAV) images is one of the critical aspects for its widespread application. However, due to limited feature extraction for small objects and ...
Description Tensorflow Object Detection API is the easy to use framework for creating a custom deep learning model that solves object detection problems. If you already have your own dataset, you can ...
Abstract: Salient object detection (SOD) plays a crucial role in the intelligent interpretation of remote sensing tasks. Significant advancements have been made with SOD methods based on convolutional ...
Abstract: In the field of autonomous driving, 3-D object detection is a crucial technology. Visual sensors are essential in this area and are widely used for 3-D object detection tasks. Recent ...
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