IEEE

A Two-stage Faster R-CNN Approach for Road Surface Damage Detection

Abstract: Road surface damage detection is important for maintaining transportation infrastructure and ensuring public safety. Automated approaches help reduce labour-intensive manual inspections and ...
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

ActionSync Video Transformation: Automated Object Removal and Responsive Effects in Motion Videos Using Hybrid CNN and GRU

Abstract: Large data volumes, dynamic scenes, and intricate object motions make video analysis extremely difficult. Traditional methods depend on human-crafted features that are not scalable. This ...
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

An Object Detection Algorithm of Literatures’ Key Information Based on Optimized Cascade R-CNN

Abstract: To address the problems of relying on electronic repositories and being vulnerable to network influence in obtaining key information of literature in mainstream literature management ...
GitHub

A brand logo detection system using Tensorflow Object Detection API.

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 simply ...
IEEE

A Verilog based Approach for Object Detection using CNN

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 ...
IEEE

MonoICT: A Monocular 3-D Object Detection Model Integrating CNN and Transformer

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 ...
IEEE

A Scale-Aware Multidomain DETR for Small Object Detection in UAV Remote Sensing Imagery

Abstract: Object detection in unmanned aerial vehicle (UAV) remote sensing imagery is significantly challenged by small-scale objects, dense distributions, and complex backgrounds. Existing detection ...
IEEE

A Recurrent CNN for Online Object Detection on Raw Radar Frames

Abstract: Automotive radar sensors provide valuable information for advanced driving assistance systems (ADAS). Radars can reliably estimate the distance to an object and the relative velocity, ...