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

共 15616 条记录，以下是671-680 订阅

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Adaptive density peaking clustering algorithm combined with sparrow search algorithm 3

Adaptive density peaking clustering algorithm combined with ...

引用

3rd International conference on Advanced algorithms and Signal image processing, AASIP 2023

作者： Wu, Chenwen Li, Hengtong Lei, Dandan School of Electronics and Information Engineering Lanzhou Jiaotong University Lanzhou730070 China

ISBN: (纸本)9781510668522

Aiming at the problem that the density peak clustering algorithm (DPC) can not adaptively adjust the cutoff distance and the clustering center needs to be specified manually, an adaptive density peak clustering algorithm combined with sparrow search algorithm (ISSA-ADPC) is proposed. Firstly, the parameter of local density and relative distance is considered comprehensively, and the adaptive selection of cluster centers is realized according to the arrangement order and downward trend of parameter;Secondly, the homogenized distribution Chebyshev chaotic map is used to initialize the sparrow population, and then the adaptive t distribution strategy is introduced to improve the sparrow search algorithm, which avoids the algorithm falling into local optimization. At the same time, the improved sparrow search algorithm is used to realize the adaptive adjustment of cutoff distance;Finally, Compared with the experimental results of K-means, DBSCAN, DPC algorithm on the artificial and UCI datasets, the proposed algorithm has higher accuracy, adjusted rand index and adjusted mutual information values, and has better clustering performance. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Chaotic systems

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An Event-Driven Approach to the Recognition Problem in video Surveillance System Development 32

An Event-Driven Approach to the Recognition Problem in Video...

引用

32nd conference of Open-Innovations-Association-FRUCT

作者： Bazhenov, Nikita Rybin, Egor Korzun, Dmitry Petrozavodsk State Univ PetrSU Petrozavodsk Russia

ISBN: (数字)9789526924489

ISBN: (纸本)9789526924489

Many video surveillance systems (VSS) have been already developed for various application domains. Such systems are based on well-elaborated recognition algorithms of Artificial Intelligence (AI) and implemented as Ambient Intelligence (AmI) services in Internet of Things (IoT) environments. In particular, algorithms support such smart VSS functions of video data processing as human detection, human identification, object location within an image, human activity recognition. Many software tools have been developed to implement various recognition algorithms for VSS development. In this paper, we consider the following VSS development problems: a) a generic model of events in video data for a given problem domain, b) a hardware-software architecture for data processing with existing recognition algorithms, and c) a model to construct a required smart VSS function using existing software tools. We introduce our event-oriented approach to solve the above VSS development problems. The approach is experienced in several use cases. Our experimental study shows the applicability of the proposed approach in terms of the accuracy and performance.

关键词： Technological innovation Face recognition Software algorithms Computer architecture Data processing video surveillance Data models

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Diagnosis of Pneumonia using image Recognition Techniques 7

Diagnosis of Pneumonia using Image Recognition Techniques

引用

7th International conference on Intelligent Computing and Control systems, ICICCS 2023

作者： Sangeetha, S. Suruthika, S. Keerthika, S. vinitha, S. Sugunadevi, M. Kongunadu College of Engineering and Technology Department of IT Tamil Nadu Trichy India

ISBN: (纸本)9798350397253

Pneumonia is a severe and fatal disease caused by viral or bacterial sepsis in human lungs. Early detection of pneumonia is critical for successful treatment. Deep learning algorithms that use many layers to interpret a boundary of data have obtained the best results in a variety of disciplines, particularly in the documenting and sorting of various diseases. As a result, there is an increasing need to design and develop a pneumonia detection system by using deep learning methods with an ability to evaluate chest CT-scan imageries and aid in the pneumonia exposure process. The proposed framework contains three phases: feature extraction, image classification, and image pre-processing. As a consequence, the projected Compared to other deep-learning models that have already been trained, such as (ResNet 50) and SVM, pneumonia diagnosis using the CNN model performed better in terms of accuracy and reliability. As a result, the efficient performance of the proposed Convolutional Neural Network centred pneumonia perception model in every parameter can provide valuable assistance to patients' care and reduce the human error rates. © 2023 IEEE.

关键词： Convolutional neural networks

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Advancing Fingerprint Recognition Quality Assessment: Introducing the FRBQ Metric for Enhanced Fingerprint Recognition 14

Advancing Fingerprint Recognition Quality Assessment: Introd...

引用

14th Indian conference on Computer vision, Graphics and image processing, ICVGIP 2023

作者： Jaiswal, Prateek Koner, Arka Namboodiri, Anoop M. CVIT IIIT Hyderabad India India

ISBN: (纸本)9798400716256

In the field of biometric security, the quality assessment of fingerprint images is paramount for boosting the accuracy of fingerprint recognition systems. These systems are fundamental for the secure and efficient authentication and identification of individuals. Our research presents FRBQ (Fingerprint Recognition-Based Quality), an innovative quality metric designed to navigate the limitations of the NFIQ2 model. FRBQ exploits deep learning algorithms in a weakly supervised setting and utilizes matching scores from DeepPrint, a Fixed-Length Fingerprint Representation Model. Each score is paired with labels indicating the robustness of fingerprint image matches. However, in a fully referenced setting, these labels can be subjective, lacking a clear definition of what "image quality" inherently means. This weakly labeled approach strives to capture diverse perspectives on image quality, potentially making it a more encompassing metric. In comparison to NFIQ2, our research showcases the superior performance of the FRBQ model. It not only correlates better with recognition scores but also effectively evaluates challenging images that NFIQ2 struggles with. Validated by the esteemed FVC 2004 dataset, FRBQ proves its efficacy in fingerprint image quality assessment. This study underscores the transformative potential of AI in biometrics, emphasizing its capability to capture details that traditional methods might overlook. Our work stresses the critical role of precise quality assessment in the evolution of fingerprint recognition systems. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： image quality

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Stopping Method for Iterative Scene Identification in an image Stream 18

Stopping Method for Iterative Scene Identification in an Ima...

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18th International Scientific and Technical conference on Dynamics of systems, Mechanisms and Machines, Dynamics 2024

作者： Muranov, A.N. Titova, A.P. Nogmov, M.H. Laboratory No 3 Institute of Design-Technology Informatics of RAS Moscow Russia

ISBN: (纸本)9798331509019

As part of solving a set of computer vision problems when analyzing video streams, a fairly popular task is to effectively stop the process of identifying scenes or objects. Arresters are one of the main problems in systems that implement online computer vision. This is explained by the fact that period of time spent obtaining results in video analytics systems is no less important than the reliability of the analysis results. In this regard, the conducted research focused on the problem of stopping when identifying scenes in a video stream. This requires detailed stopping algorithms for identifying scenes in video streams with a decision to arrest iterations, taking into account that it is not possible to generally assess the accuracy of the identification result. In this work, a list of properties of monotonic stopping functions was compiled, and an original algorithmic technique for solving stopping problems was proposed. The testing results demonstrated the high efficiency of the proposed method for identifying the text part of documents. © 2024 IEEE.

关键词： video streaming

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Review Paper on Glaucoma Detection Using Machine Learning 5th

Review Paper on Glaucoma Detection Using Machine Learning

引用

5th International conference on Energy systems, Drives and Automations, ESDA 2022

作者： Jha, Kushal Gokharu, Naman Mathur, Rohan Bhandari, Sachin Department of Computer Engineering Mukesh Patel School of Technology Management and Engineering SVKM’s NMIMS Shirpur Campus India

ISBN: (纸本)9789819701537

Glaucoma is one of the leading causes of vision loss worldwide. Glaucoma cannot be cured in its advance stages. So, early detection of disease has become an important factor in the medical field. Numerous studies quickly became clear that using different image processing methods, the retinal fundus picture could be uncovered. In this study, many automated glaucoma detection techniques were thoroughly reviewed various papers were compared on the basis of the methodologies they adopted for detecting glaucoma from 2D fundus images created using CDR. 85% of glaucoma cases can be accurately detected by the majority of machine learning algorithms. First, image segmentation techniques like Elliptical Hough transform and edge detection gave the region of interest, i.e. optic disc and cup. These extracted images were then given to the machine learning and deep learning models to detect presence of glaucoma in the fundus image of the eye. The most significant deep learning, machine learning, and transfer learning methods for analysing retinal images were reviewed, along with their benefits and drawbacks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： image segmentation

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Nonlinear SVM Classifier based Online Attendance System for Facial Recognition and Mask Detection

Nonlinear SVM Classifier based Online Attendance System for ...

引用

2024 International conference on Knowledge Engineering and Communication systems, ICKECS 2024

作者： Devi, M. Varshana Surya, K. A. Jai Meethashree, E. Keerthivasan, V.S. Saraswathy, S. K. S. Rangasamy College of Technology Computer Science and Engineering Tiruchengode637 215 India Sri Sai Ram Engineering College Computer Science and Business Systems Chennai600044 India

ISBN: (纸本)9798350359688

This research presents a novel method for monitoring attendance by creating an online system that combines facial recognition technology with machine learning algorithms to detect masks. The main objective of this project is to provide a streamlined attendance management system that can be accessed through web browsers, removing the requirement for the installation of specialised software. The technology utilises facial biometrics to identify users, storing profiles with facial picture samples in a centralised online database. Before implementing facial recognition, the system goes through a model training phase where Support Vector Machines (SVM) are used to create a strong recognition model. Moreover, synthetic data is utilised to train the algorithm in recognising individuals who are wearing facial masks. The server-side application is developed using Python and utilises the OpenCV library for image processing. The web interfaces are managed through PHP, while the database is handled using MySQL. The combination of Python and PHP scripting enables immediate processing on web servers, guaranteeing availability from any device through a web browser. The experimental findings indicate that the face recognition system achieved an accuracy rate of around 81.8%, while the mask detection system achieved an accuracy rate of 80%. These results were obtained using a pre-trained model. In summary, this system provides a whole solution for effective and safe online attendance management in many fields. © 2024 IEEE.

关键词： Support vector machines

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An improved visual reality experience for gaming applications using visual image processing 15

An improved visual reality experience for gaming application...

引用

15th International conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Ruby, E.D. Kanmani Titus, Anita Anitha, R. vijayakumari, P. Ravi, S. Vel Tech Rangarajan Dr Sagunthala R&d Institute of Science and Technology Department of Ece Chennai India Jeppiaar University Department of Ece Chennai India S.A. Engineering College Department of Ai & Ds Chennai India Sairam Engineering College Department of Ece Chennai India Saveetha University Saveetha School of Engineering Department of Vlsi Microelectronics Chennai India

ISBN: (纸本)9798350370249

Digital and augmented truth has increased in recent years, with several packages in various industries. Gaming is one such industry that has benefitted significantly from those technologies, supplying customers with an immersive and interactive revel. But there's nevertheless room for improvement, especially in visible photograph processing. Cutting-edge digital and augmented fact systems depend upon pre-rendered three-D picks, which could bring a lower fine and much less realistic visual experience. This is especially obtrusive in rapid-paced gaming packages, where photographs may appear pixilated or need more elements. To deal with this difficulty, our research proposes an advanced visual fact enjoyed by gaming applications using superior visible picture processing techniques. Our method mainly includes the realtime processing of visual data to create exceptional realism in the digital environment. This may encompass strategies, texture mapping, dynamic lights, and superior rendering algorithms. © 2024 IEEE.

关键词： Applications. Exceptional Augmented Immersive Improvement Supplying

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Proceedings - 37th International conference on VLSI Design, VLSID 2024 - held concurrently with 23rd International conference on Embedded systems, ES 2024

Proceedings - 37th International Conference on VLSI Design, ...

引用

37th International conference on VLSI Design, VLSID 2024

ISBN: (纸本)9798350384406

The proceedings contain 124 papers. The topics discussed include: a novel approach to control a DC-DC converter using its empirical physical model;optimizing medical image analysis: leveraging efficient hardware and AI algorithms;DFT static verification using early RTL exploration and debug for mobile SoC and edge AI applications;reconfigurable processing-in-memory architecture for data intensive applications;parallel-series diode-based ring amplifier for switched capacitor circuits;enhancing output corruption through GSHE switch based logic encryption;on managing test-time, power, and layer assignment in 3D socs with built-in-self-repair modules;a compact low-power 29 Gb/s pseudo random quaternary sequence generator in 65 nm CMOS;and CAD tools pathway in hardware security.

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AG-Mono: A Monocular Dataset for Unmanned Air Vehicles 30

AG-Mono: A Monocular Dataset for Unmanned Air Vehicles

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30th IEEE Signal processing and Communications Applications conference (SIU)

作者： Simsek, Bugra Giden, Ibrahim Halil Bilge, Hasan Sakir ASELSAN Girisimcilik Merkezi Ankara Turkey Gazi Univ Ankara Turkey

ISBN: (数字)9781665450928

ISBN: (纸本)9781665450928

One of the most important information needed while performing unmanned aerial vehicles (UAV) operations is about the platform location and the environment. Such platforms mostly use GNSS signals outdoors. However, in indoor areas where GNSS signals cannot be received or in situations where signals are jammed, it is not possible to obtain location information using these signals. For that reason, alternative navigation systems have become so crucial. One of the most preferred systems among navigation technologies is the visual simultaneous localization and mapping (vSLAM) method performed using RGB cameras on the UAVs. In this study, an open monocular image dataset called AG-Mono was created and published online to test the performance of vSLAM algorithms. This dataset was created at three different exposure times using a handheld platform, and it includes video sequences at 640x480 image resolution. The experimental area where the images were created is a closed corridor with 16.5 x 4.5 meters and four sharp corners.

关键词： Unmanned Aerial Vehicles (UAVs) visual SLAM (vSLAM) Monocular image Dataset

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