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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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Design of Regenerative Chatter Stability Detection System in Machine Tool Cutting based on computer Vision and SAR Image 3

Design of Regenerative Chatter Stability Detection System in...

引用

3rd international conference on Electronics and Sustainable Communication Systems, ICESC 2022

作者： Li, Liyao Yancheng Institute of Educational Science Yancheng224000 China

ISBN: (数字)9781665479714

ISBN: (纸本)9781665479714

The thesis starts with the analysis of the stability of the regenerative cutting chatter system. Based on the SAR image algorithm, the machine is processed in the processing steps of image denoising, image segmentation, target detection and recognition, focusing on the limit cutting width and random bed spindle speed W. The main factors affecting the stability of the machine tool cutting system are systematically analyzed, including the dynamic parameters of the main vibration system, and a SAR image segmentation method based on the global Maxflow neighborhood growth algorithm is proposed, which combines the texture and boundary information In combination, using C# as the development tool, designed a turning chatter stability limit prediction software, and systematically introduced the function realization and use method of the software. © 2022 IEEE.

关键词： Synthetic aperture radar

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A Technical Survey on Deep Learning and AI Solutions for Plant Quality and Health Indicators Monitoring in Agriculture 3

A Technical Survey on Deep Learning and AI Solutions for Pla...

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3rd international conference on Smart Electronics and Communication, ICOSEC 2022

作者： Sornalakshmi, K. Sujatha, G. Sindhu, S. Hemavathi, D. Srm Institute of Science and Technology Department of Data Science and Business Systems Tamil Nadu Kattankulathur India Srm Institute of Science and Technology Department of Networking and Communications Tamil Nadu Kattankulathur India

ISBN: (数字)9781665497640

ISBN: (纸本)9781665497640

The crop production and quality face many challenges due to the loss caused by plant diseases and destruction due to pests. The traditional method of manual monitoring is not an early indicator when the span of the agricultural land is vast. Image processing is more accurate now with deep learning and computer vision techniques. The computer vision-based image classification can help identify diseases in plants at early stages from multi-angle images of the plant leaves and fruits. Such images can be auto captured by autonomous drones. The advantage of using drones as an edge device for image acquisition, filtering, and basic image preprocessing with further layers of Artificial Intelligence (AI) and deep learning to identify diseases in plants would solve the challenges faced by the human methods to a great extent. This paper surveys the state-of-the-art works done for the early detection of plant diseases using computer vision and deep learning techniques. © 2022 IEEE.

关键词： computer vision

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Research on Question Matching of Operation System FAQ with Knowledge Graph and Image Information 3

Research on Question Matching of Operation System FAQ with K...

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2022 3rd international conference on computer Information and Big Data Applications, CIBDA 2022

作者： Zhao, Haomin Liu, Yu Gu, Jinguang College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan China Key Laboralory of Intelligent Information Processing and Real-time Industrial System in Hubei Province Hubei Wuhan China Institute of Big Data Science and Engineering Wuhan University of Science and Technology Hubei Wuhan China

ISBN: (纸本)9783800758760

The FAQ system is to match the questions asked by the user with the questions in the FAQ library, and subsequently return the answers to the questions according to the smenatic similarity between questions. The existing matching methods of question pair are not specially designated for the OS domain and do not incorporate domain knowledge. The screenshots of Operating System provided by user usually contain important information, which can be uesed to improve the effectiveness of question matching method. In this paper, we evaluate the important of text in image with the highlighted evaluation, location evaluation, and text evaluation, and filter out important text for question matching. In order to use knowledge of Operation System, we introduce a pretraining model incorporating the domain knowledge that can be used for problem matching. In the experiment, the method with knowledge graph and image information can fully improve the accuracy rate, recall rate and F1 score of the matching reuslts compared to the mainstream method. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Domain Knowledge

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Invading Deep Neural Information Management Systems by Adaptive Multi-Gradient Based Method 3

Invading Deep Neural Information Management Systems by Adapt...

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

作者： Wang, Pian Xiao, Yatie Jiang, Jingyu Guangdong Innovative Technical College Management School Dongguan China Guangzhou University School of Computer Science and Cyber Engineering Guangzhou China

ISBN: (纸本)9798350320404

The applications of deep learning have been widely employed in many specific domains (e.g., computer vision and language processing). The research on the security and privacy of deep neural networks (DNNs) has drawn much attention related to adversarial attacks and defense on DNNs. To provide a simple yet effective adversarial learning resource for building adversarial security, we formulate imperceptible adversarial perturbations in an adaptive multi-gradient learning manner, which calls a few adaptive operators on gradient-based terms. First, the proposed work searches for the input gradient based on the source representation in deep neural models. Then, fusing three adaptive gradient-based mechanisms to form the perturbed terms, which improves the capability of the generated samples to search the decision boundaries between original and adversarial domains directly. We compare the proposed work to other gradient-based adversarial attack methods in fooling convolutional neural networks in the field of computer vision. Experimental results reveal that adversarial examples generated by the introduced approach show surpassing effectiveness in fooling deep neural networks. It manifests fewer pixel changes in generated adversarial examples both on and norm constraints with specific attack strategies, respectively. © 2022 IEEE.

关键词： Deep neural networks

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A Proposed Siamese Convolutional Neural Network for Fingerprint Recognition 3

A Proposed Siamese Convolutional Neural Network for Fingerpr...

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2022 3rd international conference on computer Information and Big Data Applications, CIBDA 2022

作者： Zhang, Lin Information Science and Technology College Donghua University Shanghai201620 China

ISBN: (纸本)9783800758760

In the past, the main way for fingerprint recognition was based on traditional image processing technology, which is timeconsuming and easy to fail. In order to recognize fingerprints more efficiently, in this experiment, the study proposed to use a method based on Siamese Network consisting of Convolutional Neural Network (CNN), which was seldom studied in the past. This experiment also is employed the idea of Multi-Scale Dilated Convolutions which can improve the receptive field and make each output of the Convolution contains a large amount of information. Dilated Convolutions introduces a hyper-parameter called dilation rate, which defines the spacing of values when Convolutional kernels process the data. This model added the three convolutional layers together which dilation rate equals 1, 2, 3 respectively to get dilated convolutions. This study input fingerprints and measured the similarity via output distance. The smaller the distance, the more similar the fingerprint and therefore it can judge if the fingerprints belong to the same person. The experimental results support this view. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Convolution

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Daily solar radiation prediction using NARX and MLP-NNs networks: A Case study of Kenitra City, Morocco 3

Daily solar radiation prediction using NARX and MLP-NNs netw...

引用

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

作者： Elmousaid, Rachida Adnani, Younes El Hamdaouy, Achour Elgouri, Rachid Ibn Tofail University Advanced Systems Engineering Laboratory Kenitra Morocco Ibn Tofail University Electronic Systems Information Processing Mechanics and Energy Laboratory Kenitra Morocco

ISBN: (数字)9781665457231

ISBN: (纸本)9781665457231

The aim of this paper is to predict daily solar radiation by two artificial neural network models using weather data. The first model is a multilayer perceptron neural network (MLP-NNs)while the second is the nonlinear autoregressive network with exogenous inputs (NARX). In order to investigate the influence of different meteorological variables on daily solar radiation forecast, there are four input feature combinations to evaluate. To reduce the error, we used three training algorithms to develop the two models MLP-NNs and NARX, adjusting the number of neurons in each and the delay in the latter. These models were compared using four evaluation metrics: Mean square error (MSE), mean absolute error (MAE), root mean square error (RMSE), and the regression coefficient (R2). © 2022 IEEE.

关键词： Mean square error

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Research on Text Recognition of Natural Scenes for Complex Situations 3

Research on Text Recognition of Natural Scenes for Complex S...

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3rd international conference on Pattern Recognition and Machine Learning, PRML 2022

作者： Yu, Wenhua Ibrayim, Mayire Hamdulla, Askar Xinjiang University School of Information Science and Engineering Urumqi China Xinjiang Key Laboratory of Signal Detection and Processing Urumqi China Xinjiang Key Laboratory of Multilingual Information Technology Urumqi China

ISBN: (数字)9781665499507

ISBN: (纸本)9781665499507

As a great invention that affects human development and progress, writing plays an essential role in human life and learning and the inheritance and development of culture. For thousands of years, the inheritance of Chinese culture has been inseparable from the writing records. Papermaking and printing have played a crucial role in the development of the times. Text extraction and recognition technology in natural scenes, that is, text recognition from photos or videos, has become a popular research direction in computer vision in recent years. Scene text recognition is a fundamental task in computer vision. It is often a critical step in many text-related tasks, such as document retrieval, card recognition, license plate recognition, and other tasks. The vital difference between the text recognition process and text detection is that the text in the photo or video needs to be recognized. Detection and recognition are mainly divided into two steps: locating text areas in photos or videos, that is, finding words or text lines of the bounding box;then the positioned text is recognized. Combining these two steps results in End-to-end Recognition of text. The continuous development of scene text detection and recognition algorithm system will lay the foundation for the research of recognition problems such as multilingual recognition of scene text and formula recognition. © 2022 IEEE.

关键词： computer vision

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Research on several construction strategies of multilingual resource database 3

Research on several construction strategies of multilingual ...

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3rd international conference on computer science and Communication Technology, ICCSCT 2022

作者： Meng, Lingchun Kong, Shuying Li, Wenyue Cui, Lei Center of Network and Information Guangdong University of Foreign Studies Guangzhou China

ISBN: (纸本)9781510661240

In order to realize the effective use of information resources in different languages, it is necessary to establish a corresponding information resource database. Based on cross-language retrieval, this paper analyses the construction strategy of multilingual resource database, and takes language acquisition and processing as the perspective. The construction of the resource database provides a reference. In view of the construction of multilingual resource database, this paper makes an analysis from three aspects: resource collection and pre-processing, resource storage and retrieval, and multilingual translation technology, and summarizes its implementation methods. The collection, storage and retrieval of multilingual resources should adopt a distributed architecture. The resource library builds a language encoding and transcoding system for efficient collection and preprocessing of multiple languages. The translation between languages adopts machine translation technology mainly based on neural network machine translation. © 2022 SPIE.

关键词： computer aided language translation

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Abstractive Text Summarization Using Hybrid Methods 3

Abstractive Text Summarization Using Hybrid Methods

引用

3rd international conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Daga, Gautam Saha, Subhradeep Shah, Yash Nirmala, S Jaya National Institute of Technology Department of Computer Science and Engineering Tiruchirappalli India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

Text summarization involves the process of constructing a concise, condensed, short, coherent, and fluent summarized version of a comparatively longer document with more text and involves the process of collection and segregation of the text's major note points. There are broadly two different kinds of approaches that can be used for the process of text summarization - a) Extractive Summarization(selects important sentences as a subset of original text) and b) Abstractive Summarization(introduces new words to create a meaning summary). Hybrid methods try to incorporate a combination of both the above models, extractive and abstractive to summarize the text where the final summary can either be abstractive or extractive based on the relative positioning of the two models. © 2022 IEEE.

关键词： Text processing

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Traffic Surveillance System and Criminal Detection Using Image processing and Deep Learning 3

Traffic Surveillance System and Criminal Detection Using Ima...

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3rd international conference on Innovations in science and Technology for Sustainable Development, ICISTSD 2022

作者： Anoop, Aditya Harikrishnan, G. Nair, Keerthi Sangeetha, B.S. Praseedalekshmi, V. Tasneem Salam, H. College of Engineering Perumon Department of Electronics and Communication Kollam Kerala India

ISBN: (纸本)9781665499361

The unpredictability and blockage of current transportation frameworks frequently produce traffic circumstances that endanger the security of the individuals and it can cause several problems in our life. To identify traffic offenders, we propose a system that will intelligently use image processing and deep learning to penalize them by recognizing their license plate. This will identify criminals, case of accident and initiates an emergency call on detecting it. A GPS-enabled traffic surveillance camera can detect the location of an accident and send a message or call the traffic control room with the accident's location. Retinanet, an object detection technique is used here for detecting vehicles which violates the traffic rule and its number plate will be localized by using image processing operation. The number plate information extracted by Optical Character Recognition and the car's image are further processed by CNN for identifying criminals and alerts are given to the authorities. The accidents can be identified using deep learning and computer vision followed by delivering the signal to Arduino. The dislocated parts of object were detected from the images and fix it as an accident by CNN (Convolutional Neural Network) for certain threshold. When accident happens, alert is given for an emergency vehicle. This framework is made by fundamental GSM module. The system provides a robust and efficient method to detect red light offenders and criminals and provides an immediate emergency calling facility. © 2022 IEEE.

关键词： Optical character recognition

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