Results 1 to 10 of about 1,094,036 (234)
Survey of Adversarial Attack and Defense for RBG and Infrared Multimodal Object Detection [PDF]
Jisuanji kexueObject detection,as a fundamental classic task in the field of computer vision,has a wide range of applications.Deep learning based object detection algorithms have become the mainstream of current research due to their superior performance.However,most ...
ZHENG Haibin, LIN Xiuhao, CHEN Jingwen, CHEN Jinyin
doaj +1 more source
Auxiliary Detection Head for One-Stage Object Detection
IEEE Access, 2020 The auxiliary classifier can improve the performance of classification networks. However, the utility of the auxiliary detection head has not been explored in the object detection field.
Guozheng Jin +2 more
doaj +1 more source
A Survey of Zero-Shot Object Detection
Big Data Mining and AnalyticsZero-Shot object Detection (ZSD), one of the most challenging problems in the field of object detection, aims to accurately identify new categories that are not encountered during training. Recent advancements in deep learning and increased computational
Weipeng Cao +5 more
doaj +1 more source
UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Tracking
, 2020 In recent years, numerous effective multi-object tracking (MOT) methods are developed because of the wide range of applications. Existing performance evaluations of MOT methods usually separate the object tracking step from the object detection step by ...
Cai, Zhaowei +8 more
core +1 more source
Aerial Data Exploration: An in-Depth Study From Horizontal to Oriented Viewpoint
IEEE AccessThe development of technological devices, such as satellites and drones, has made it easier to collect images and videos from the air. From these vast data sources, the problem of detecting objects in aerial images is formed to serve situations: rescue ...
Nguyen D. Vo +10 more
doaj +1 more source
Review of One-Stage Universal Object Detection Algorithms in Deep Learning [PDF]
Jisuanji kexue yu tansuoIn recent years, object detection algorithms have gradually become a hot research direction as a core task in the field of computer vision. They enable computers to recognize and locate target objects in images or video frames, and are widely used in ...
WANG Ning, ZHI Min
doaj +1 more source
Centered Multi-Task Generative Adversarial Network for Small Object Detection
Sensors, 2021 Despite the breakthroughs in accuracy and efficiency of object detection using deep neural networks, the performance of small object detection is far from satisfactory. Gaze estimation has developed significantly due to the development of visual sensors.
Hongfeng Wang +3 more
doaj +1 more source
Soft-NMS -- Improving Object Detection With One Line of Code
, 2017 Non-maximum suppression is an integral part of the object detection pipeline. First, it sorts all detection boxes on the basis of their scores. The detection box M with the maximum score is selected and all other detection boxes with a significant ...
Bodla, Navaneeth +3 more
core +1 more source
Object detection model of coal mine rescue robot based on multi -scale feature fusio
Gong-kuang zidonghua, 2020 Traditional object detection model uses artificial object features, resulting in poor detection accuracy. Object detection model based on deep learning has high detection accuracy.
ZHAI Guodong +5 more
doaj +1 more source
Review on One-Stage Object Detection Based on Deep Learning
EAI Endorsed Transactions on e-Learning, 2022 As a popular research direction in computer vision, deep learning technology has promoted breakthroughs in the field of object detection. In recent years, the combination of object detection and the Internet of Things (IoT) has been widely used in the ...
Hang Zhang, Rayan S Cloutier
doaj +1 more source