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检索条件"任意字段=2022 3rd International Conference on Signal Processing and Computer Science, SPCS 2022"

共 761 条记录，以下是111-120 订阅

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3rd international conference on Innovations in computer science and Software Engineering, ICONICS 2022

3rd International Conference on Innovations in Computer Scie...

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3rd international conference on Innovations in computer science and Software Engineering, ICONICS 2022

ISBN: (纸本)9781665461412

The proceedings contain 28 papers. The topics discussed include: experimentation for decentralized resource-based multi-pool mining in Ethereum blockchain;performance enhancement in agriculture sector based on image processing;frameworks, applications and challenges in streaming big data analytics: a review;prevention and safety strategies for road accidents by using evolutionary algorithms;intrusion detection using deep learning techniques;analyzing applicant’s pre-admission data and predicting applicant’s performance in pre-admission test using data mining techniques;quantum computing and machine learning algorithms - a review;real-time violence detection using deep learning techniques;a study on the e-commerce trends using data analysis;and a systematic review on the motivations of cyber-criminals and their attacking policies.

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A Simultaneous Hole, Groove and Defect Detection Method Based on Yolov4-tiny and MMOE 3

A Simultaneous Hole, Groove and Defect Detection Method Base...

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3rd international conference on computer Vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Lin, Haicheng Gong, Jie Chen, Xiang Xie, Xiaohua Tang, Hengliang Jiang, Junfeng Sun Yat-sen University School of Computer Science and Engineering Guangzhou China Sun Yat-sen University School of Electronics and Information Technology Guangzhou China Guangdong Xinguang Intelligent System Co. Ltd. Zhongshan China

ISBN: (纸本)9781665459112

The quality detection of furniture boards is one of the most important parts of the furniture board quality control process. The boards may contain round holes, grooves, and defects for various reasons. In industry, it is necessary to detect them in real time. This paper proposes a multi-objective detection method based on the Yolov4-tiny and Multi-Gate Mixture-of-Experts(MMOE) structure that can simultaneously detect round holes, grooves and defects in high resolution board images in real time. Considering the high resolution of the board image and the small size of the dataset, data pre-processing and data augmentation are performed to reduce the size of the image and increase the size of the dataset. In consideration of the difference in the characteristics of the hole, groove and defect. the task of detecting defects and the task of detecting holes and grooves are decoupled, and different task headers and gate networks are designed. Finally, it is tested on a real production line and the combined mAP reaches 75.49% and the detection takes only 20ms. © 2022 IEEE.

关键词： Object detection

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Diabetic retinopathy detection using a pretrained machine learning model 3

Diabetic retinopathy detection using a pretrained machine le...

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3rd IEEE international conference on Electronics, Control, Optimization and computer science, ICECOCS 2022

作者： Sbai, Asma Touil, Abdelali Oukhouya, Lamya Cady Ayyad University Laboratory of Bioscience and Health Faculty of Medecine and Pharmacy of Marrakech Marrakech Morocco Faculty of Sciences Ibn Zohr University Laboratory of Engineering Sciences Agadir Morocco Ibn Zohr University Laboratory LIMA ENSA Agadir Agadir Morocco

ISBN: (数字)9781665457231

ISBN: (纸本)9781665457231

One of the possible side effects of diabetes is Diabetic Retinopathy. Early diagnosis of diabetic retinopathy is an important step toward healing and can prevent many patients from potential blindness. To identify diabetic retinopathy, practitioners may need an artificial intelligence tool to provide a second opinion to confirm or refute a diagnosis. In this article we use a pretrained machine learning model to find a solution to the issue of low-quality inputs by implementing, in the pre-processing step, the technique of Contrast Limited Adaptive Histogram Equalization to extract more features especially the blood vessels. © 2022 IEEE.

关键词： computer aided diagnosis

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Research on improved diffusion algorithm based on gradient quantization in target localization algorithm 3

Research on improved diffusion algorithm based on gradient q...

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3rd international conference on Electronic Information Engineering and computer Communication, EIECC 2023

作者： Liu, Yuanheng Yin, Yong School of Information Engineering Wuhan University of Technology Wuhan China Chongqing Research Institute Wuhan University of Technology Chongqing China

ISBN: (纸本)9798350359961

As the industrial automation field rapidly advances, the application of image processing in practical engineering becomes increasingly sophisticated. This study focuses on the target localization problem in industrial production lines, utilizing the Histogram of Oriented Gradient (HOG) algorithm to extract the gradient direction features from images. Building upon this, we propose an improved gradient diffusion algorithm. The algorithm enhances the precision and detail of each pixel's gradient direction by identifying primary gradient directions within the pixel's neighborhood and adjusting the central pixel's gradient information. This algorithm does not require a timeconsuming training phase, enhancing the robustness of image processing. It not only addresses interference from various image acquisition environments but also improves the reliability of the localization algorithm when dealing with irregularly shaped workpieces. Our experimental results have confirmed the effectiveness of the proposed method in the precise detection and localization within industrial production. When faced with various scenarios, the accuracy of its positioning exceeds 99%, and the execution time does not exceed 0.05 seconds. © 2023 IEEE.

关键词： computer vision Gradient direction diffusion Gradient feature extraction HOG

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Classification of Non-motorized Vehicle Based on Micro-Doppler Effect and Image processing 3

Classification of Non-motorized Vehicle Based on Micro-Doppl...

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3rd international conference on computer Vision and Pattern Analysis, ICCPA 2023

作者： Lin, Yang Liu, Jing Zhu, Lingzhi Zhang, Shuning School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing China School of Networks and Telecommunications Engineering Jingling Institute of Technology Nanjing China

ISBN: (纸本)9781510667563

With the rise of the take-out food industry and bicycle sharing, the frequency of non-motorized vehicle using has increased significantly, and the ensuing safety hazards have become increasingly serious. Since motor vehicles are always subject to traffic violations by non-motorized vehicles, it is important to classify non-motorized vehicles for optimal handling in emergency situations. Due to the uniqueness of the target information, the micro-Doppler effect is increasingly used to distinguish between different targets. In this paper, we propose a non-motorized vehicle classification method based on the micro-Doppler effect and image processing. Firstly, the relationship model between ground non-motorized vehicles and radar is established, the expression of the echo signal is derived, and the simulation analysis is carried out according to the set parameters, the differences between the non-motorized time-domain frequency domain diagrams and the joint time-frequency diagrams were investigated. Secondly, the classification features of the car hub echo signal are introduced, and the feasibility of these features as classification criteria is verified by simulations. Then, the feature extraction methods based on image processing are introduced, and the extraction results of different edge detection operators are compared and analyzed. Finally, the classification method of non-motorized vehicles based on these three features is introduced. © 2023 SPIE.

关键词： Feature extraction

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An Extensible Framework for Task Partitioning on Heterogeneous Systems 3

An Extensible Framework for Task Partitioning on Heterogeneo...

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3rd international conference for Emerging Technology, INCET 2022

作者： Yekbote, Pavan Raj, Poojita Anupindi, Ravi S. Sudarshan, T.S.B. Pes University Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9781665494991

High performance computing applications have witnessed significant speedups in performance from leveraging the compute capabilities of heterogeneous platforms. These speedups are seldom taken advantage of in practice partly due to the inefficacy of mapping parallel sections of an application to specific processing units. Ascertaining this mapping necessitates taking into account the run time and compile time features of the application on a heterogeneous platform. This paper proposes a framework capable of classifying a high performance computing application to its optimal partitioning in a heterogeneous CPU-GPU target system. This classifier has been trained on a combination of run time execution metrics and compile time static code features of applications from different domains collected from benchmark suites such as Rodinia [1] and OmpSCR [2]. The contribution of this work is twofold - an extensible framework demonstrating the utility of accurate mapping and a pair of data sets that exhibit the significance of run time and compile time features on the framework estimating the effect of varied input type and size. © 2022 IEEE.

关键词： Graphics processing unit

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Research on Image processing and Generative Teaching in the Context of AIGC 3

Research on Image Processing and Generative Teaching in the ...

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3rd international conference on Information science and Education, ICISE-IE 2022

作者： Rao, Jian Qiu, Chuqi Xiong, Mengzhen Art and Design College Wuhan China

ISBN: (纸本)9798350320381

AIGC, meaning AI-generated content, is discussed in this paper, mainly in the form of painting, without discussing the automation of music composition and text-writing poetry, etc. While generative art has aesthetic characteristics, more content needs to be studied in the context of computer information science, with a particular emphasis on computer vision and computer graphics. The article focuses on a comparative analysis of two models, diffusion algorithms and generative adversarial networks, and their application to tools. The practical part of image processing uses a combination of case studies and questionnaires to demonstrate the lack of methodology, teaching experience, and introductory learning materials for non-computer professionals in the emerging field, and to explain "filter mapping"through processing, a visual programming software. The author's reflections on the generated content combine the self-similarity of the "Uncanny Valley effect"and the "Dunning Kruger effect"lineage, comparing the "self-organizing"(machine) simulation personification and the "life form"(human) simulation personification. The process of cognitive assimilation of a "living organism"(human) is used to understand the new human-machine associative relationship. © 2022 IEEE.

关键词： Mapping

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Differential sparse single-pixel imaging with wavelet coefficients 3

Differential sparse single-pixel imaging with wavelet coeffi...

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3rd international conference on computer Vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Wang, Qian Huo, Yaoran Leshan Vocational and Technical College Leshan China Information & Communication Company State Grid Sichuan Electric Power Company Chengdu China

ISBN: (纸本)9781665459112

Wavelet tree-based adaptive compressed ghost imaging has higher imaging speed and better imaging quality than compressed sensing methods. However, the number of samples can be reduced, since finer significant coefficients can be calculated with the existing measurements. This paper proposes a compressive adaptive ghost imaging with block-wise computational sampling in this paper. This method takes full use of the sparsity of the image in the wavelet domain. The block-wise computational sampling computes four LL band coefficients of high resolution via fewer than two measurements. The calculation strategy takes the useful information of the sampled low-resolution coefficients. This brings in fewer measurements. The computed LL band coefficients are also used to sample significant HH, HL, and LH coefficients of the same scale. The extended prediction method can accurately locate the positions of the important coefficients, by eliminating insignificant coefficients that belongs to significant parent coefficient. The simulation results show that the proposed compressive adaptive ghost imaging using block-wise computing sampling can achieve lower rate of sampling and advanced imaging quality. © 2022 IEEE.

关键词： Optical data processing

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Interaction-Enhanced Textual Similarity Matching Distance Measurement - Exploration on Chinese 3

Interaction-Enhanced Textual Similarity Matching Distance Me...

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3rd international conference on computer science and Management Technology, ICCSMT 2022

作者： Zhang, Yijia Wang, Jiyao Xiong, Dan The Hong Kong University of Science and Technology School of Engineering Hong Kong Hong Kong GF Securities CO.LTD Department of Information Technology Guangzhou China

ISBN: (纸本)9798350320404

Textual similarity matching is one of the most valuable tasks in natural language processing. Meanwhile, due to the wide development of applications and increase in requirements, various subtasks are proposed and expected to be resolved. In addition, Chinese, which owns the largest population of native speakers, introduced more challenges because of its different grammar and characteristics. In this project, we explore the best design of representation, interaction, and prediction layers for Chinese textual similarity matching by extensive experiments on two public datasets. Results prove that the precise interaction paradigm and unlearnable distance metric is more suitable for matching task considering effectiveness and efficiency. And for the option of representation structure, we should simultaneously consider textual information distribution within datasets and computational cost. © 2022 IEEE.

关键词： Deep learning

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Accelerometer signals denoising without clean training data based on Noise2Noise approach 3

Accelerometer signals denoising without clean training data ...

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3rd international conference on Electronic Information Engineering and Data processing, EIEDP 2024

作者： Zheng, Fengling Li, Wei Cui, Xiaohui Rajaboevich, G.S. School of Artificial Intelligence and Computer Science Jiangsu Key Laboratory of Media Design and Software Technology Jiangnan University Jiangsu China School of Cyber Science and Engineering Wuhan University Wuhan China Tashkent University of Information Technologies named after Muhammad al –Khwarizmi Yunusobod district 108 Amir Temur str Tashkent100202 Uzbekistan

ISBN: (纸本)9781510680531

The accelerometer signal is capable of providing crucial information regarding object motion, posture, and vibration. Therefore, it is of great significance to investigate noise suppression techniques for accelerometer signals. However, in complex industrial environments and under various equipment conditions, the noise generated exhibits a diverse nature, leading to suboptimal noise reduction outcomes when employing conventional denoising algorithms. This paper proposes a neural network model (AgentUNet) for denoising accelerometer signals. The network consists of a combination of UNet and Agent Attention, enhancing its ability to learn contextual information and achieve superior denoising performance. Additionally, instead of using clean signals as labeled data, we train the neural network using pairs of noisy data, thereby alleviating the challenge of collecting clean signals in industrial environments. Finally, we conduct experiments on experiment dataset. The experimental results indicate that AgentUNet achieves superior denoising performance compared to other baseline models. Furthermore, the denoising effectiveness of the neural network trained without using clean signals as labeled data is similar to that of the network trained using supervised learning methods. © 2024 SPIE.

关键词： Accelerometers

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