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

共 12976 条记录，以下是981-990 订阅

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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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A Survey on Music Genre Classification Using Multimodal Information processing and Retrieval

A Survey on Music Genre Classification Using Multimodal Info...

引用

2023 IEEE International conference on Recent Trends in Electronics and Communication, ICRTEC 2023

作者： Abhyankar, Shreya G. Bharadwaj, Shashank S. Rani, G. Shobha Karigiri, Pruthvi G. Srikanth, Sahana Gurugopinath, Sanjeev Pes University Department of Electronics and Communication Engineering Bengaluru560085 India

ISBN: (纸本)9798350396195

Musical descriptors play a very crucial role in automatic music genre classification. With the increase in digitized music, query and retrieval of musical data has always been subjective and controversial. More often, a musical clip is often spread across the genres, making the classification process very challenging. This paper presents a contemporary survey of the recent advances made in the classification of music genre using different machine learning and deep learning algorithms. Specifically, it looks into the recent developments in the area of genre classification based on audio based descriptors, image based descriptors, and other descriptors which include album cover art, brain signals, lyrics and musical instrument digital interface data. © 2023 IEEE.

关键词： Music

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Enhancing Scene Simplification and Optimization for Retinal Prosthesis Platform 5

Enhancing Scene Simplification and Optimization for Retinal ...

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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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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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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...

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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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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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Color Transformations of Video Endoscopic images

Color Transformations of Video Endoscopic Images

引用

International conference on Vision, image and Signal processing (ICVISP)

作者： Natalia A. Obukhova Alexandr A. Pozdeev Konstantin A. Smirnov Alexandr A. Motyko Olga R. Savelieva SPbSU ETU “LETI” St. Petersburg Russia

ISBN: (数字)9798331541460

ISBN: (纸本)9798331541477

The paper considers the main procedures of digital processing of endoscopic images aimed at increasing their diagnostic value. It is shown that the existing approaches, solving private problems, lead to the general inconsistency of color transformations in the endoscopic video system. A new multi-objective quality criterion for the synthesis of color transformations, taking into account both the accuracy of color reproduction and the transmission of local color contrast, is proposed. Exemplary methodologies for target-specific color transformation synthesis are developed and validated, addressing critical challenges in endoscopic image enhancement. Experimental results underscore the efficacy of the approach in maintaining color integrity while significantly amplifying the diagnostic value through enhanced contrast articulation. The proposed algorithms were evaluated on diverse datasets of endoscopic images, demonstrating a substantial improvement in local contrast and image clarity compared to existing techniques. The virtual chromoendoscopy method achieved a balance between natural color representation and enhanced diagnostic features, while the bimodal visualization approach optimized the integration of fluorescence and white-light imaging. These results contribute to the evolution of visualization and perceptually optimized imaging solutions, marking a substantial advancement in medical image processing. The study establishes a robust foundation for the development of context-aware imaging methodologies in modern medical systems.

关键词： Visualization Accuracy image color analysis Signal processing algorithms Signal processing Fluorescence Biomedical image processing Medical diagnostic imaging image enhancement

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Traffic image text detection via YOLOv8 based on attention mechanism and rotation proposals location

Traffic image text detection via YOLOv8 based on attention m...

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International conference on Advanced Mechatronic systems (ICAMechS)

作者： Zhou Xianwang Zhang Xianfeng Engineering College Guangzhou College of Technology and Business Foshan China

ISBN: (数字)9798350366204

ISBN: (纸本)9798350366211

Traffic scene text detection is an important technology in the field of image processing, which has significant practical significance in the applications of assisted driving, automatic driving and intelligent transportation. However, traffic scene text detection faces many challenges, such as background complexity and text Angle diversity. In this paper, the YOLOv8 model is applied to text detection tasks in traffic scenarios. In YOLOv8s model, attention mechanism is introduced to enhance feature extraction ability. At the same time, Circular Smooth Label (CSL) is used for Angle classification, so as to achieve accurate prediction of text with different oblique *** experimental results show that compared with DBNet algorithm, F-measure on self-made datasets CTST and public datasets ICDAR2015 is improved by 1.7% and 2.1%, respectively. In addition, the proposed algorithm is 2.03 times faster than the EAST algorithm in terms of image processing speed, and the detection time of a single image is about 0.03 seconds, which effectively meets the needs of real-time detection during driving.

关键词： Attention mechanisms Mechatronics Shape Text detection Transportation Prediction algorithms Feature extraction Real-time systems Classification algorithms Proposals

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Automated Optic Disk Detection in Fundus images using a Combination of Deep Learning and Local Histogram Matching

Automated Optic Disk Detection in Fundus Images using a Comb...

引用

conference on Medical Imaging - Biomedical Applications in Molecular, Structural, and Functional Imaging

作者： Tavakoli, Meysam Univ Pittsburgh Med Ctr Dept Radiat Oncol Pittsburgh PA 15260 USA UPMC Hillman Canc Ctr Pittsburgh PA 15232 USA

ISBN: (数字)9781510649484

ISBN: (纸本)9781510649484;9781510649477

Retinal images have been used in the diagnosis of many ocular diseases such as glaucoma and diabetic retinopathy. Here, automatic detection of optic disk (OD) is essential in deriving clinical parameters to assist clinical diagnosis. In fact, detecting OD center and its boundary is the essential step of most vessel segmentation, disease diagnostic, and retinal recognition algorithms. In this study, we proposed a new approach for localizing OD by combining local histogram matching and the concept of deep learning. The algorithm is composed of 4 steps, image partitioning, Local histogram matching and validation, Convolutional Neural Network (CNN) classification, and OD detection. Here, we used OD of the five reference retinal images in each dataset to extract the histograms of each color channel. Then, we calculated the mean of histograms for each channel as template for creating some OD candidates. An AlexNet-like CNN was applied to classify candidates as ODs or nonODs. The candidates used as an input to feed the CNN for final classification. In this study, we worked on three databases (one rural, MUMS-DB, and two publicly available databases, DRIVE, STARE) including 520 retinal images to evaluate the proposed method. The accuracy of our algorithm was 100%, 90%, and 95% for the DRIVE, STARE, and MUMS-DB respectively. It is shown that this method provides higher detection rates than the existing methods that have reported.

关键词： image segmentation image processing image processing algorithms and systems Optical discs image resolution MATLAB Radon transform

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