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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems III"

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Mobile Smartphone-based Augmented Reality for Industry Remote Monitoring and Maintenance 3

Mobile Smartphone-based Augmented Reality for Industry Remot...

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conference on Unconventional Optical Imaging iii Part of SPIE Photonics Europe conference

作者： Naumov, I Sinakin, M. Semenishchev, E. Gapon, N. Don State Tech Univ Rostov Na Donu Russia LLC DAR Rostov Na Donu Russia Moscow State Univ Technol STANKIN Ctr Cognit Technol & Machine Vis Moscow Russia

ISBN: (纸本)9781510651494;9781510651487

Currently, VR and AR headsets are becoming widespread. In addition to entertainment purposes, these technologies are increasingly being used in education, science, medicine, and engineering. The remote maintenance monitoring technologies make it possible to significantly expand the possibilities of using services for remote maintenance and repair complex technical systems by highly qualified specialists. However, the problems of implementing such systems in a wide range of tasks are complicated by the presence of a wide variety of solutions of this kind and the high price of such models. In this paper, we investigate a new smartphone-based augmented reality device for industrial tasks. The article describes augmented reality glasses based on a mobile phone (system "DAR"), which combines the functions of VR and AR technologies and a low cost of the final product. The proposed solution combines a helmet with a smartphone, which transmits information about the surrounding space and connects the augmented reality elements built on this image. Information about the surrounding space comes to the smartphone screen from stereo cameras equipped with autofocus. images captured in such a system suffer from low contrast and faint color. We present a new image enhancement algorithm based on multi-scale block-rooting processing. This solution makes it possible to expand AR technology scope for remote maintenance of complex technical systems by highly qualified specialists at remote sites since using a smartphone and a DAR headset will be sufficient. Some experimental results are presented to illustrate the performance of the proposed algorithm on the real and synthesized image datasets.

关键词： augmented reality glasses DAR VR and AR technologies stereo camera image enhancement

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Enhancing Scene Simplification and Optimization for Retinal Prosthesis Platform 5

Enhancing Scene Simplification and Optimization for Retinal ...

引用

5th International IEEE Novel Intelligent and Leading Emerging Sciences conference, NILES 2023

作者： Holiel, Heidi Ahmed Fawzi, Sahar Ali Al-Atabany, Walid Nile University Medical Imaging and Image Processing Research Group Center for Informatics Science Sheikh Zayed City Egypt Cairo University Systems and Biomedical Engineering Department Giza Egypt Helwan University Biomedical Engineering Department Helwan Egypt

ISBN: (纸本)9798350381030

Retinal prostheses are designed to aid individuals with retinal degenerative conditions such as Retinitis Pigmentosa (RP) and Age-related Macular Degeneration (AMD). These prostheses seek to restore vision and improve the perceived scene by stimulating degenerated retinal cells using retinal stimulating electrodes. While these electrodes allow more efficient interaction with the surroundings, they offer limited *** paper presents an innovative approach to revolutionize the visual perception of retinal prosthesis users. The key idea behind the proposed approach is to fuse information extracted from advanced Meanshift and saliency detection algorithms. This proposed approach aims to improve the perceived scene for users, leading to enhanced visual perception and increased efficiency of retinal prostheses. © 2023 IEEE.

关键词： Computer vision

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RailSet: A Unique Dataset for Railway Anomaly Detection 5

RailSet: A Unique Dataset for Railway Anomaly Detection

引用

5th IEEE International conference on image processing Applications and systems (IPAS)

作者： Zouaoui, Arij Mahtani, Ankur Hadded, Mohamed Amine Ambellouis, Sebastien Boonaert, Jacques Wannous, Hazem FCS Railenium Famars France Gustave Eiffel Univ Lille France Univ Lille Ctr Digital Syst IMT Nord Europe Inst Mines Tel ecom Lille France

ISBN: (纸本)9781665462198

Understanding the driving environment is one of the key factors in achieving an autonomous vehicle. In particular, the detection of anomalies in the traffic lane is a high priority scenario, as it directly involves vehicle's safety. Recent state of the art image processing techniques for anomaly detection are all based on deep learning of neural networks. These algorithms require a considerable amount of annotated data for training and test purposes. While many datasets exist in the field of autonomous road vehicles, such datasets are extremely rare in the railway domain. In this work, we present a new innovative dataset relevant for railway anomaly detection called RailSet. It consists of 6600 high-quality manually annotated images containing normal situations and 1100 images of railway defects such as hole anomaly and rails discontinuity. Due to the lack of anomaly samples in public images and difficulties to create anomalies in the railway environment, we generate artificially images of abnormal scenes, using a deep learning algorithm named StyleMapGAN. This dataset is created as a contribution to the development of autonomous trains able to perceive tracks damage in front of the train. The dataset is available at this link.

关键词： image generation Anomaly dataset Railway tracks anomaly Autonomous train Generative and Adversarial Neural Networks

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Shape-Constrained Symbolic Regression with NSGA-iii 18th

Shape-Constrained Symbolic Regression with NSGA-III

引用

18th International conference on Computer Aided systems Theory, EUROCAST 2022

作者： Haider, Christian Kronberger, Gabriel Josef Ressel Center for Symbolic Regression Heuristic and Evolutionary Algorithms Laboratory University of Applied Sciences Upper Austria Hagenberg Austria

ISBN: (纸本)9783031253119

Shape-constrained symbolic regression (SCSR) allows to include prior knowledge into data-based modeling. This inclusion allows to ensure that certain expected behavior is reflected by the resulting models. This specific behavior is defined by constraints which restrict the functional form e.g. monotonicity, concavity or model image boundaries. That allows finding more robust and reliable models in the specific case of highly noisy data or in extrapolation domains. This paper presents a multi-objective approach to minimize the approximation error as well as the constraint violations. Explicitly the two algorithms NSGA-II and NSGA-iii are implemented and compared against each other in terms of model quality and runtime. Both algorithms are executed on a selected set of benchmark instances from physics textbooks. The results indicate that both algorithms are able to generate mostly feasible solutions and NSGA-iii provides slight improvements in terms of model quality. Moreover, an improvement in runtime can be observed when using NSGA-iii. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Benchmarking

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Reach-to-Grasp Motion Tracking System Using Single Smart Phone Camera 7

Reach-to-Grasp Motion Tracking System Using Single Smart Pho...

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7th International conference on Business and Industrial Research (ICBIR)

作者： Thongprasan, Sahawatchara Liangsorn, Natsakorn Raden-ahmad, Chafik Kongkaew, Kotchakorn Tretriluxana, Jarugool Tretriluxana, Suradej King Mongkuts Inst Technol Dept Elect Engn Sch Engn Bangkok Thailand Mahidol Univ Fac Phys Therapy Motor Control & Neural Plast Lab Bangkok Thailand

ISBN: (纸本)9781665494755

Assessment of human movement is necessary for physical therapy management. This article presents a development of motion tracking system for human Upper Extremity (UE) function analysis. We proposed the optical motion capture system made by a single smart phone camera. It was used to capture the Reach-to-Grasp (RTG) movement of participants in sitting position. image processing were used to detect color markers placed on chosen hand anatomical landmarks. With our simple camera calibration technique, the 3D coordinates of hand movement were obtained. Two clinical parameters, grasp aperture and hand transport velocity were computed. These results were compared with the outputs, collected at the same time, from the higher accuracy Electromagnetic Motion (EM) tracking system. Qualitatively, the result patterns from two systems were parallel to each other. Our ongoing work is to improve the algorithms according to the feedback from clinicians. This system may provide implication for physical therapist to assess the clients' movement in the clinical setting.

关键词： motion tracking system Reach-To-Grasp (RTG) movement image processing Upper Extremity (UE) smart phone camera

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Comparative Study of TRANS - GAN Architecture for Bio-Medical image Semantic Segmentation 7

Comparative Study of TRANS - GAN Architecture for Bio-Medica...

引用

7th International conference on Communication and Electronics systems, ICCES 2022

作者： Ashok, Malvika Gupta, Abhishek Shri Mata Vaishno Devi University School of Computer Science and Engineering Jammu and Kashmir Katra India

ISBN: (数字)9781665496346

ISBN: (纸本)9781665496346

In the area of biomedical image processing, medical image segmentation plays a crucial role. Today due to the deep sculptures of deep neural networks and innovative by-passes like the Transformers this field has rejuvenated. This paper analyzes various algorithmic advancements regarding Transformers and Generative Adversarial Networks (GAN) which have paved the anatomy of image segmentation. The GAN network is not only able to regenerate feature spaces but also can transpose the inputs from the transformer. These algorithms are not only at par with the bifurcation of networks like U-net and ResNet but showcase a strong and more intuitive idea of human neural intelligence. Finally, all methods are compared based on accuracy, dice score, architectural evaluation, etc. The ability of these networks are deduced to regenerate and recreate the feature spaces for the given input image and thus can segment high features for prediction. © 2022 IEEE.

关键词： Generative adversarial networks

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Modified U Net Based Learning Model for Semi Supervised Medical image Segmentation 3

Modified U Net Based Learning Model for Semi Supervised Medi...

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3rd International conference on Power, Energy, Control and Transmission systems, ICPECTS 2022

作者： Ramya, P. Babu, S. Venkatesh Venkatesan, G. PSNA College of Engineering and Technology Department of AI and DS Dindigul India SNS College of Engineering Department of CSE Coimbatore India Sri Sai Ram Engineering College Department of EEE Chennai India

ISBN: (纸本)9781665462754

The applications include scene interpretation, medical image processing, robotic perception, video based scrutiny systems, augmented and virtual reality, among many others the image segmentation is a being a key topic. In the literature, many picture segmentation methods have been created, and there have been a lot of recent efforts aimed at creating image segmentation algorithms using deep learning models due to the success of these models in a broader range of vision based utilities. The adaptability of a learning model to segment medical images like Modified U-net based convolution neural network has shown good results in retinal vessel region extraction and has greater feature learning ***, using the DRIVE and STARE datasets, we compare the accuracy, specificity, and sensitivity of modified U-Net deep learning with those of the U-Net model, and we also highlight several promising future research directions. © 2022 IEEE.

关键词： image segmentation

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Impacts of image Compression on the Detection Quality of a Novel Real-Time image processing Platform

Impacts of Image Compression on the Detection Quality of a N...

引用

International conference on Intelligent Transportation

作者： Jannik Mehrke Georg Volk Yannik Stumpp Oliver Bringmann Anestis Terzis Institute of Communication Technology Ulm University of Applied Sciences Dept. of Computer Engineering University of Tübingen

Cloud-based data processing latency mainly depends on the transmission delay of data to the cloud and the used data processing algorithm. To minimize the transmission delay, it is important to compress the transferred data without reducing the quality of the data. When using data compression algorithms, it is important to validate the impact of these algorithms on the detection quality. This work evaluates the effects of image compression and transmission over wireless interfaces on state of the art neural networks. Therefore, a modern image processing platform for next generation automotive processing architectures, as used in software defined vehicles, is introduced. The impacts of different image encoders as well as data transmission parameters are investigated and discussed.

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Deep Learning Deblurring for Improved Vehicle Number Plate Detection

Deep Learning Deblurring for Improved Vehicle Number Plate D...

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Smart systems for Electrical, Electronics, Communication and Computer Engineering (ICSSEECC), International conference on

作者： Kalaimathi B Jayanthy S Suriya Krishna M Subish R Kanna Sanjay K Department of Electronics and Communication Engineering Sri Ramakrishna Engineering College Coimbatore India

ISBN: (数字)9798350378177

ISBN: (纸本)9798350378184

This study describes a novel way for improving automatic license plate recognition (ALPR) systems, with a focus on addressing obstacles associated with indistinct license plate photos. The suggested method combines advanced picture deblurring algorithms with reliable information extraction methods to improve the accuracy and dependability of ALPR systems. The major goal is to create a comprehensive pipeline capable of efficiently extracting license plate information while improving image clarity. This entails using sophisticated deblurring algorithms to reduce distortion effects and hence improve overall image quality. Subsequently, advanced computer vision algorithms recognize relevant elements such as characters and patterns, allowing for accurate content recognition. Finally, post-processing techniques are used to thoroughly evaluate and refine the collected plate content. By greatly enhancing accuracy and dependability, particularly in practical circumstances, the proposed ALPR system promises to make major contributions to traffic management and security applications.

关键词： image quality Accuracy Law enforcement Transfer learning Traffic control Information retrieval Distortion

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Using image processing and Optical Character Recognition to Recognise ID cards in the Online Process of Onboarding

Using Image Processing and Optical Character Recognition to ...

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2022 International conference on Smart Information systems and Technologies, SIST 2022

作者： Gulnara, Bektemyssova Yerassyl, Akhmer International Information Technology University Almaty Kazakhstan

ISBN: (数字)9781665467902

ISBN: (纸本)9781665467902

A broad range of computer vision studies have been conducted on the recognition of identity documents using mobile devices. A portfolio of techniques and algorithms for solving problems like face recognition, document detection and correction, text field recognition, and so on has been developed, and the lack of data sets has become a critical challenge. The electronic ID card has been commonly used to verify or recognize an individual since its discovery in 2011. Take note of several issues, such as high requirements for detecting the id-card field and challenges recognizing the data in the id-card. In this research, we realized an approach for identifying electronic ID cards using image detection and Optical Character Recognition (OCR). This paper provides a short outline of how banking institutions and other fintech companies utilize highly developed OCR tools to automate their processes, enhancing not just service quality, as well as the precision, speed, and protection of their transaction data. As an outcome of our image processing and OCR techniques, we can achieve 99 percent ID detection. This research was based on the interface of a mobile application, such as those owned by one of Kazakhstan's banks. © 2022 IEEE.

关键词： Optical character recognition

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