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检索条件"机构=Liaoning Key Laboratory of Image Understanding and Computer Vision"

共 55 条记录，以下是21-30 订阅

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Combining Depth and Gray image for Fast 3D Object Recognition

Combining Depth and Gray Image for Fast 3D Object Recognitio...

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International Symposium on Optoelectronic Technology and Application 2016(OTA 2016)——Conf.5 Optical Measurement Technology and Instrument

作者： Wang Pan Feng Zhu Yingming Hao Optoelectronic Information Technology Laboratory Shenyang Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Chinese Academy of Sciences Key Laboratory of Optical-Electronics Information Processing Liaoning Key Laboratory of Image Understanding and Computer Vision

Reliable and stable visual perception systems are needed for humanoid robotic assistants to perform complex grasping and manipulation *** recognition of the object and its precise 6D pose are re

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94 GHz Three-Dimensional Imaging Radar for Environmental Detection 8

94 GHz Three-Dimensional Imaging Radar for Environmental Det...

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8th Asia-Pacific Conference on Antennas and Propagation, APCAP 2019

作者： Wu, HongMing Qi, Feng Wang, Jinkuan Northeastern University College of Information Science and Engineering Shenyang110819 China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang110016 China Key Lab of Image Understanding and Computer Vision Liaoning Province Shenyang110016 China

ISBN: (纸本)9781665400541

At present, With the development of technology, the high resolution of millimeter wave (terahertz) can be applied to environmental sensing imaging. In this paper, Using the frequency-modulated continuous-wave (FMCW) radar technique with a 1GHz bandwidth, we show experimentally that a high-resolution real time imaging radar operating at 93.5-94.5GHz is capable of detecting different car models at standoff ranges of 12 m. We also achieved 3D high-resolution imaging of the building. at 140 meters. © 2019 IEEE.

关键词： Millimeter waves

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Deep Learning Methods for Ship Classification: From Visible to Infrared images 5

Deep Learning Methods for Ship Classification: From Visible ...

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5th International Conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2023

作者： Liu, Tianci Qin, Hengjia Zhan, Zhuo Liu, Yunpeng Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Chinese Academy of Sciences Key Laboratory of Opto-Electronic Information Processing Shenyang110016 China Key Laboratory of Image Understanding and Computer Vision Liaoning Province Shenyang110016 China The Third Military Representative Office of the Air Force Equipment Department in Shenyang Region Liaoning Province Shenyang110027 China

ISBN: (纸本)9798350357950

Deep learning methods have achieved excellent performances on visual tasks of target recognition and classification. The rapid development of autonomous seafaring vessels comes up with the requirement to recognize other maritime ships day and night. However, the recognition of ships based on the deep neural networks may not always access the results as expectation when the ships are under the nighttime environment. To this issue, we consider the ship recognition task under the deep learning framework with paired visible images and infrared images. In this article, we propose an end-to-end convolutional network based on visible images and infrared images of the autonomous seafaring vessels. To demonstrate the effectiveness of our model, we choose the V AIS dataset to test the performance of classifying the maritime ships. Experimental results show that the proposed network outperforms the state-of-the-art methods based on the V AIS database. © 2023 IEEE.

关键词： deep learning infrared images neural network Ship recognition

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image saliency detection method based on multi-feature maps fusion 4

Image saliency detection method based on multi-feature maps ...

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4th International Conference on computer Graphics, image, and Virtualization, ICCGIV 2024

作者： Li, Xiaoli Liu, Yunpeng Zhao, Huaici Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Key Laboratory of Opto-Electronic Information Processing Shenyang China The Key Lab of Image Understanding and Computer Vision Shenyang China Shenyang Jianzhu University Shenyang China

ISBN: (纸本)9781510683242

In this research, we introduce an innovative saliency detection algorithm, comprising three essential steps. Firstly, leveraging fully convolutional networks with aggregation interaction modules, we generate an initial saliency map. Secondly, we extract hand-craft and deep features to express the image, then use manifold ranking method to construct saliency maps. Ultimately, by integrating the outcomes from preceding stages, we generate the final saliency map. Experimental findings demonstrate that our method surpasses twelve cutting-edge saliency detection techniques in terms of precision, recall, F-measure, and MAE value metrics." © 2024 SPIE.

关键词： Feature extraction

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Unsupervised Terahertz image Restoration Based on CycleGan 3

Unsupervised Terahertz Image Restoration Based on CycleGan

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3rd International Conference on Defence Technology, ICDT 2022

作者： Su, Zhipeng Zhang, Yixiong Qi, Feng Shi, Jianghong School of Informatics Xiamen University National Demonstrative Software School Xiamen361005 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Opto-Electronic Information Process Shenyang110016 China Key Laboratory of Image Understanding and Computer Vision Shenyang110016 China

Terahertz (THz) is considered as one of the key technologies for sixth generation communications, military, medical imaging and industrial inspection. THz images are susceptible to degradation due to system noise and point spread functions during transmission. The existing deep learning methods use ground truth and input images for supervised training that can recover THz images very well. But it's difficult to obtain labeled THz data in practical application. In this paper, we propose an attentional adversarial cycle generation network for THz image restoration (CycleTHz) based on CycleGan to address this problem. The CycleTHz generates clean images firstly by an attention-guided generation network and then discriminates the quality of the generators by an attention discriminator. In addition, RGB color loss is used for image channels for constraint. To the best of our knowledge, this is the first THz dataset to be trained using an unsupervised approach. Extensive experiments show that the proposed method improves the PSNR and SSIM by 43.4% and 101.7% compared with CycleGan, which is a benchmark method for the unsupervised development in THz image restoration. The code is available at https://***/hellogry/UnsupervisedCycleTHz © Published under licence by IOP Publishing Ltd.

关键词： image reconstruction

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An Improved Real-time Visual Tracking Method for Space Non-cooperate Target

An Improved Real-time Visual Tracking Method for Space Non-c...

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International Symposium on Optoelectronic Technology and Application 2016(OTA 2016)——Conf.6 Robot Sensing and Advanced Control

作者： Limin Zhang Feng Zhu Yingming Hao Shenyang institute of automation Chinese academy of sciences University of Chinese Academy of Sciences Key laboratory of optical-electronics information processing Chinese academy of science Key laboratory of image understanding and computer vision

In order to enable the non-cooperative rendezvous, capture, and removal of large space debris, robust and fast tracking of the non-cooperative target is needed. This paper proposes an algorithm of rea

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Edge direction dispersion and its application in automatic suitable-matching area selection

Edge direction dispersion and its application in automatic s...

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Chinese Control and Decision Conference

作者： Qing-Hai, Ding Xin-Rong, Yu Hai-Bo, Luo Hong-Mei, Liu Research Institute of General Development and Demonstration of Equipment Equipment of Air Force Bejing 100076 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Graduate School Chinese Academy of Sciences Beijing 100039 China Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Science Shenyang 110016 China Key Laboratory of Image Understanding Computer Vision Liaoning Province 110016 China AVIC HONGDU Aviation Industry Group Ltd. Nanchang 330024 China

ISBN: (纸本)9781424487363

Automatic suitable-matching area selection is an important research in visual guidance, scene matching and local non-texture target tracking. Meanwhile, it is the major research subject in computer vision and accurate guidance. In this paper, a new characteristic quantity, i.e., the edge direction dispersion was defined. Then the computation method, parameters selection and real-time realization of this characteristic quantity were investigated. Furthermore, the application of its characteristic in automatic suitable-matching area selection was studied. With a reasonable design for calculation precision, solving method for arctan(x) function in [-∞,+∞ ] could be simplified to linearization calculations in [0, 0.25], then a fast algorithm for arctan(x) function was presented. Experimental results showed that the sub-image extracted by our fast algorithm had higher matching level and was suitable to be a matching template. All the calculations involved in the proposed matching algorithm could be done in one filed period and the real-time request could be satisfied. Moreover, this characteristic of edge direction could also be used to measure the comparability of template and real-time images, which could be widely used in automatic target recognition and target tracking. © 2011 IEEE.

关键词： Target tracking

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Shape Matching under Affine Transformation Using Normalization and Multi-scale Area Integral Features

Shape Matching under Affine Transformation Using Normalizati...

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International Symposium on Optoelectronic Technology and Application 2016(OTA 2016)——Conf.6 Robot Sensing and Advanced Control

作者： Huiying Cai Feng Zhu Yingming Hao Rongrong Lu Shenyang institute of automation Chinese academy of sciences University of Chinese Academy of Sciences Key laboratory of optical-electronics information processing Chinese academy of science Key laboratory of image understanding and computer vision

Shape refers to the equivalence representation of objects obtained through projecting the objects onto the imaging planes. The projecting action can be fitted by some finite-dimensional transformation

ISBN: (纸本)9781510607729

关键词： Shape matching Orthogonal normalization Equivalent resample Multi-scale area integral features Affine transformation Area integral shape analysis edge pixel Shape normalization multi-scale

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The correction method of computation of heat flux over dome based on turbulence models

The correction method of computation of heat flux over dome ...

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International Symposium on Optoelectronic Technology and Application 2016(OTA 2016)——Conf.12 Infrared Technology and Application

作者： ZHANG Daijun LUO Haibo ZHANG Junchao ZHANG Xiangyue Shenyang Institute of Automation Chinese Academy of Science University of Chinese Academy of Science Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Science Key Laboratory of Image Understanding and Computer Vision

Aerodynamic heating effect caused by high speed flight of optical guidance system will lead to optical dome fracture failure or thermal barrier effect, which results in the inefficiency of the optical

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Theanalysis and test ofthethermal shock resistance of the Multi-spectralCVD ZnS dome

Theanalysis and test ofthethermal shock resistance of the Mu...

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International Symposium on Optoelectronic Technology and Application 2016(OTA 2016)——Conf.12 Infrared Technology and Application

作者： ZHANG Daijun LUO Haibo ZHOU Peipei HOU Xinglin Shenyang Institute of Automation Chinese Academy of Science University of Chinese Academy of Science Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Science Key Laboratory of Image Understanding and Computer Vision

Optical guidance system start infrared guided mode by throwing away the fairing in the terminal guidance phase. After throwing away the fairing, the infrared dome will be suddenly exposed to the aerod

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