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4th Chinese conference on Pattern Recognition and computer vision (PRCV)

作者： Li, Haodong Chen, Xiaoming Zhuang, Peiyu Li, Bin Shenzhen Univ Guangdong Key Lab Intelligent Informat Proc Shenzhen 518060 Peoples R China Shenzhen Univ Shenzhen Key Lab Media Secur Shenzhen 518060 Peoples R China Shenzhen Inst Artificial Intelligence & Robot Soc Shenzhen 518129 Peoples R China

ISBN: (纸本)9783030880071;9783030880064

Image tampering localization has attracted much attention in recent years. To differentiate between tampered and pristine image regions, many methods have increasingly leveraged the powerful feature learning ability of deep neural networks. Most of these methods operate on either spatial image domain directly or residual image domain constructed with high-pass filtering, while some take inputs from both domains and fuse the features just before making decisions. though they have achieved promising performance, the gain of integrating feature representations of different domains is overlooked. In this paper, we show that learning a unified feature set is beneficial for tampering localization. In the proposed method, low-level features are firstly extracted from two input streams: one is a spatial image, and the other is a high-pass filtered residual image. the features are then separately enhanced with channel attention and spatial attention, and are subsequently subjected to an early-fusion to form a unified feature representation. the unified features play an important role under an adapted Mask R-CNN framework, achieving more accurate pixel-level tampering localization. Experimental results on five tampered image datasets have shown the effectiveness of the proposed method. the implementation is available at https://***/media-sec-lab/AEUF-Net.

关键词： Image forgery localization Feature fusion Attention mechanism Mask R-CNN

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Research and Simulation of Intelligent Grasping of robotic Arm Based on Machine vision Recognition

Research and Simulation of Intelligent Grasping of Robotic A...

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Power Electronics, computer Applications (ICPECA), IEEE International conference on

作者： Jinshun Dong Lixia Deng Dapeng Wan Haiying Liu School of Information and Automation Engineering Qilu University of Technology (Shandong Academy of Sciences) Jinan China

With the economic and social development of human beings, people have higher and higher requirements for the intelligence of machinery and equipment. With the vigorous development of robot vision technology, robots are becoming more and more widely used in various industries, and they also gradually have “eyes”. this not only broadens the scope of its use, but also improves its intelligence. In this paper, the PUMA-560 manipulator was simulated to realize its visual recognition and grasping functions. It has been applied to the original industrial robots. For example, the six-axis manipulator used this time is to obtain relevant information about the target and the surrounding environment through computer vision technology, so as to accurately identify the action to be carried out, and respond according to the action to guide the robot to grasp.

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MERTZ: a quest for a robust and scalable active vision humanoid head robot

MERTZ: a quest for a robust and scalable active vision human...

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IEEE-RAS International conference on Humanoid robots

作者： L. Aryananda J. Weber Artificial Intelligence Laboratory MIT Computer Science Cambridge MA USA

We present the design and construction of MERTZ, an active-vision humanoid head robot, with the immediate goal of having the robot runs continuously for many hours a day without supervision at various locations. We address how the lack of robustness and reliability lead to limitations and scalability issues in research robotic platforms. We propose to attend to these issues in parallel with the course of robot development. Drawing from lessons learned from our previous robots, we incorporated various fault prevention strategies into the electromechanical design. We have implemented a preliminary system, integrating sensorimotor, vision, and audio in order to test the full range of all degrees of freedom and enable the robot to engage in simple visual and verbal interaction with people. We conducted a series of experiment where the robot ran for $2 hours within 9 days at different public spaces. the robot interacted with a large number of passersby and collected at least 100,000 face images of at least 600 individuals within 4 days. We learned various lessons involving the robustness of current design and identified a set of failure modes. Lastly, we present the long term research direction for the robot.

关键词： Robustness Humanoid robots robot vision systems robot sensing systems Orbital robotics Head Intelligent robots Parallel robots Human robot interaction computer science

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2014 4th International conference on Mechanical Science and Engineering, ICMSE 2014

2014 4th International Conference on Mechanical Science and ...

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2014 4th International conference on Mechanical Science and Engineering, ICMSE 2014

ISBN: (纸本)9783037859650

the proceedings contain 198 papers. the special focus in this conference is on Advanced Research in Intelligent Equipment Manufacturing. the topics include: Optimization design on the performance of the shaper;modeling and dynamic research of the pneumatic-hydraulic loading simulator system;test and numerical analysis of natural frequency for tube;wind turbine gearbox transmission chain forced vibration analysis exerted by random actuator;vibration characteristics analysis of large dismountable out-moving jaw crusher;excitation order research in bladed-disk coupling resonance condition;driving intention based optimal shift control for automatic transmission;dispersion curves calculation for guided waves in rod by modal analysis;dynamic characteristics analysis for seismic vibrator;finite element research on damping of viscoelastic free layer damping sheet;coupling vibration of tapered rod;resonance reliability analysis of aeroengine compressor rotor blade;present status of damping test techniques for magnesium alloys;parameter sensitivity analysis of gear contact in gear-bearing-rotor system based on romax;investigation of crack line offset of fracture splitting connecting rod;near-field noise prediction for landing gear based on detached eddy simulations;fatigue life analysis of auger stem in soft coal seam;research on walking principle of a worm pipe robot;a new way to simulate the fluid structure interaction between the bioprosthetic heart valve and blood;based on ANSYS large diameter metallic high-speed rotating disk modal analysis;the numerical investigation of cracking areas under nonuniform settlements of the construction;simulation and control of a duopoly model;topological optimization for damping structure of cylindrical shell based on DIMFM;development of double-axis double-rest CNC machining center;construction of computer controlled bioreactor;study on detection method for crack in eggs based on computer vision and support vector machine neural network;

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Tracking foveated corner clusters using affine structure

Tracking foveated corner clusters using affine structure

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International conference on computer vision (ICCV)

作者： I.D. Reid D.W. Murray Department of Engineering Science University of Oxford UK

the authors describe a novel method of obtaining a fixation point on a moving object for a real-time gaze control system. the method makes use of a real-time implementation of a corner detector and tracker and reconstructs the image position of the desired fixation point from a cluster of corners detected on the object using the affine structure available from two or three views. the method is fast, reliable, viewpoint invariant, and insensitive to occlusion and/or individual corner dropout or reappearance. Results are presented for the method used with a high performance head/eye platform. the results are compared with two naive fixation methods.< >

关键词： Layout Object detection Detectors Head Target tracking Real time systems computer vision Turning Availability robot vision systems

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Enhancing Manufacturing Efficiency With computer vision And Doosan robotics: An Overview Of Real-Time Object Detection And Automated Decision-Making

Enhancing Manufacturing Efficiency With Computer Vision And ...

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2023 4th International Informatics and Software Engineering conference (IISEC)

作者： Ameni Chaabani Raef Cherif Yacine Yaddaden Département de mathématiques Informatique et génie Université du Québec à Rimouski Rimouski Canada

this article presents a solution developed with Doosan robotics and Onrobot for identifying missing or broken pull tabs in manufacturing processes using computer vision and robotics integration. the solution involves a collaborative robot equipped with a 2.5D camera and an end-effector capable of grasping and manipulating objects. the 2.5D camera captures images of the objects, and computer vision algorithms are applied to detect and identify the presence of pull tabs and assess their condition. the system utilizes advanced image processing techniques to analyze the captured images, identifying any instances of missing or broken pull tabs. Upon detection, the robot employs its end-effector to interact with the identified pull tabs, facilitating their removal or replacement as necessary. the integration also incorporates automated decision-making algorithms to optimize production efficiency, reduce errors, and improve product quality. Integrating these technologies enhances precision, accuracy, and speed in identifying and manipulating objects, leading to increased productivity, cost reduction, and improved product quality.

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2011年 6657 LNAI卷 VI页

作者： Butz, Cory Lingras, Pawan University of Regina Department of Computer Science 3737Wascana Parkway Regina SK S4S 0A2 Canada Saint Mary's University Department of Mathematics and Computing Science Halifax NS B3H 3C3 Canada

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Visual-based Machine Understanding Framework for Decision Making on Social robot 4th

Visual-based Machine Understanding Framework for Decision Ma...

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International conference on Interactive Digital and Media

作者： Marzuki Agus Sukoco Maria S. Febrianti School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Computer Science Faculty Bandar Lampung University Lampung Indonesia

ISBN: (纸本)9781509016709

Social robot acts based on any perceived information to interact and communicate with humans or other robots. One essential type of information is visual-based information captured by camera. Visual data from camera is processed to extract essential information through different perspectives such as gesture detection, facial recognition, sign and object detection, and text understanding. As an intelligent agent, the social robot should be able to determine and perform socially rational action autonomously based on the processed information. In this paper, a general framework of visual-based information process to produce rational action is presented. the proposed architecture is implemented on a platform of humanoid robot as a test subject.

关键词： social robot rational action computer vision image processing

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Phoneme-Viseme Mapping for Sinhala Speaking robot for Sri Lankan Healthcare Applications 4

Phoneme-Viseme Mapping for Sinhala Speaking Robot for Sri La...

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4th IEEE Eurasia conference on Biomedical Engineering, Healthcare and Sustainability, ECBIOS 2022

作者： Wakkumbura, W.G.V.K. Madhubhashana, R.A.H. Alahakoon, P.M.K. Kumara, W.G.C.W. Hinas, M.N.A. South Eastern University of Sri Lanka Department of Electrical and Telecommunication Engineering Oluvil Sri Lanka South Eastern University of Sri Lanka Department of Computer Science and Engineering Oluvil Sri Lanka

ISBN: (数字)9781728195797

ISBN: (纸本)9781728195797

Speech perception is considered entirely as an auditory process, but vision also has a significant influence on speech perception. In generating synthesized vocal systems, especially for robotic applications, inaccurate synchronization between voice and lip movements substantially decreases the speech understanding and the naturalness of face-to-face communication. Phoneme-viseme mapping is one of the most important approaches in the visual recognition of speech and visual speech synthesis applications. Although there are many phoneme-viseme mapping models for languages such as English, Indonesian, Arabic, German, no adequate phoneme-viseme mapping model is available for the Sinhala language. this research proposes a methodology for Sinhala static viseme classification and establishes a phoneme-viseme mapping model for the Sinhala language. the Sinhala language is a low-resource language that belongs to the Indo-European sub-family, it has some similarities to the languages like Hindi, Marathi, and Bengali. the traditional Sinhala phonetic alphabet consists of 40 phonemes including 14 vowels and 26 consonants. this paper outlines the analysis of geometrical lip movements and features of the speakers pronouncing Sinhala word sequences which have been recorded in optimal conditions. Viseme classes are obtained through a static viseme approach where K-means clustering techniques and Sinhala linguistic features are considered. the proposed model was validated through a subjective analysis method and this is expected to grow into a reference model for future research attempts, as well as for developing an instructional robotic face that will form the visual interface for Sinhala-speaking healthcare seekers. © 2022 IEEE.

关键词： Mapping

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Development of Tank-Based Military robot and Object Tracker

Development of Tank-Based Military Robot and Object Tracker

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Asia-Pacific conference on Intelligent robot Systems (ACIRS)

作者： Widodo Budiharto Vincent Andreas Jarot S. Suroso Alexander Agung S. Gunawan Edy Irwansyah Computer Science Department Bina Nusantara University Jakarta Indonesia Information Systems Management Department Bina Nusantara University Jakarta Indonesia

Indonesia is a country whose economy is developing very fast. According to World Bank data, Indonesia is the country with the largest economic development in Southeast Asia. Unfortunately, the threat of terrorism in Indonesia is very large, therefore it requires a smart system such as military robots. Today's vision-based robot technology has also been used in the development of autonomous military robots. A sophisticated military robot is a robot that is needed by the military/police because it can be deployed to the battlefield or the eradication of terrorism in a remote or autonomous manner. this system is needed to reduce the remaining casualties from the army, and this combat robot system can also be operated at any time with more numbers than regular soldiers and with minimal operator needs. In this paper, we propose a prototype of a tank-based military robot with object detection and tracking and turrets for simulation of shooting the enemy target based on the computer vision. the object tracker will detect an upper body of the target using a library in OpenCV and the tank will track until it reaches the best position to shoot the target. the methods explained, and experimental results were presented.

关键词： Military computing computer vision Object detection Target tracking Artificial intelligence

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