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检索条件"任意字段=7th International Conference on Computer and Information Processing Technology, ISCIPT 2022"

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WATNet: A Wavelet-Aware Lightweight Hybrid Model for Fast Low-Light Enhancement 7

WATNet: A Wavelet-Aware Lightweight Hybrid Model for Fast Lo...

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7th Asian conference on Artificial Intelligence technology, ACAIT 2023

作者： Wang, Qiangqiang Huang, Peiliang Li, Lei Han, Longfei Anhui University AHU-IAI Ai Joint Laboratory Hefei China Hefei Comprehensive National Science Center Institute of Artificial Intelligence Hefei China Northwestern Polytechnical University School of Automation Xi'an China Science And Technology On Complex System Control And Intelligent Agent Cooperation Laboratory Beijing China Beijing Technology And Business University Beijing China University of Science And Technology of China School of Information Science And Technology Hefei China

ISBN: (纸本)9798350359145

Low-light enhancement task is an essential component of computer low-level visual tasks, which involves processing images captured under dim lighting conditions to make them appear as if they were taken under normal illumination. Currently, deep neural networks have become the mainstream approach for image processing. However, recent works have devoted considerable efforts to designing high-performance models, which often come with high computational complexity and inference time, making real-time processing unfeasible. We observed that some convolutional methods are due to the need for deep layers which results in a large number of parameters. Moreover, enhancing details and removing noise in low-light images remains an open challenge. In order to solve the above problems, we propose a lightweight baseline that combines CNN and sparse grid attention transformer blocks to enable the model to capture a global receptive field at an early stage. Specifically, we propose a High-Frequency Wavelet-aware Block(HFWB) that focuses on processing high-frequency information in the wavelet domain to refine details and suppress noise. With a processing time of only 10.6ms, the performance of our model outperforms that of the current state-of-the-art lightweight models on benchmark low-light datasets. Compared to state-of-the-art models in the LOL dataset, our model achieves a reduction in inference time of over 90% and requires only about 1% of the FLOPS. © 2023 IEEE.

关键词： Deep neural networks

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7th international conference on computer Vision and Image processing, CVIP 2022

7th International Conference on Computer Vision and Image Pr...

引用

7th international conference on computer Vision and Image processing, CVIP 2022

ISBN: (纸本)9783031314162

the proceedings contain 54 papers. the special focus in this conference is on computer Vision and Image processing. the topics include: CT Image Synthesis from MR Image Using Edge-Aware Generative Adversarial Network;Modified Scaled-YOLOv4: Soccer Player and Ball Detection for Real Time Implementation;candidNet: A Novel Framework for Candid Moments Detection;cost Efficient Defect Detection in Bangle Industry Using Transfer Learning;single Image Dehazing Using Multipath Networks Based on Chain of U-Nets;leveraging Tri-Planar Views and Weighted Average Fusion Technique to Classify Lung Nodule Malignancy;a Bayesian Approach to Gaussian-Impulse Noise Removal Using Hessian Norm Regularization;deepTemplates: Object Segmentation Using Shape Templates;Data-Centric Approach to SAR-Optical Image Translation;MIS-Net: A Deep Residual Network Based on Memorised Pooling Indices for Medical Image Segmentation;linear and Non-Linear Filter-based Counter-Forensics Against Image Splicing Detection;Ischemic Stroke Lesion Segmentation in CT Perfusion Images Using U-Net with Group Convolutions;Multi-generator MD-GAN with Reset Discriminator: A Framework to Handle Non-IID Data;video Colorization Using Modified Autoencoder Generative Adversarial Networks;Real-Time Violence Detection Using Deep Neural Networks and DTW;skin Disease Detection Using Saliency Maps and Segmentation Techniques;an Alternate Approach for Single Image Haze Removal Using Path Prediction;Detecting Tropical Cyclones in INSAT-3D Satellite Images Using CNN-Based Model;Two Stream RGB-LBP Based Transfer Learning Model for Face Anti-spoofing;Logarithmic Progressive-SMOTE: Oversampling Minorities in Retinal Fundus Multi-disease Image Dataset;HD-VAE-GAN: Hiding Data with Variational Autoencoder Generative Adversarial Networks;sequence Recognition in Bharatnatyam Dance;Multi-modality Fusion for Siamese Network Based RGB-T Tracking (mfSiamTrack).

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Research on Continuance Intention of Platform: Influence of Video System, information, and Service Quality 7

Research on Continuance Intention of Platform: Influence of ...

引用

7th IEEE/ACIS international conference on Big Data, Cloud Computing, and Data Science, BCD 2022

作者： Cho, Hee Jun Lee, Se Yong Soongsil Univ Graduate School Dept. of Business Administration Seoul Korea Republic of

ISBN: (数字)9781665465823

ISBN: (纸本)9781665465823

the online video service market is expanding day by day as the demand for video services has exploded in recent years. Compared to the growth of other platforms, the growth of video platform services is very rapid. Nevertheless, studies on platform selection and continued use intention are insufficient. this study studies the factors that affect the user's continuance intention of video platforms. the influence of each factor on users' use of platform services was analyzed using the information Systems Success Model and technology Acceptance Model. As a result of the analysis, it was found that system quality, information quality, and service quality had a significant effect on perceived fun, perceived ease of use, and perceived usefulness. In addition, it was found that perceived fun, perceived ease of use, and perceived usefulness all had a significant effect on continued use intention. © 2022 IEEE.

关键词： Quality of service

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7th international conference on computer Vision and Image processing, CVIP 2022

7th International Conference on Computer Vision and Image Pr...

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7th international conference on computer Vision and Image processing, CVIP 2022

ISBN: (纸本)9783031314063

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Frequency Offset Estimation of X-band Marine Radar Sampling Signal Based on Phase Difference 7th

Frequency Offset Estimation of X-band Marine Radar Sampling ...

引用

7th EAI international conference on Advanced Hybrid information processing, ADHIP 2023

作者： Wang, Jianming Maritime College Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9783031505454

Due to the relative radial movement between the transmitter and receiver of marine radar, the frequency of radar sampling signal is prone to deviation, which reduces the quality of radar sampling signal. In order to ensure the effective transmission of radar signals, a frequency offset estimation method of marine radar sampling signals in X-band based on phase difference is proposed. the AD9225 chip is selected to acquire the marine radar signal, and the undersampling theorem is used to determine the marine radar signal sampling frequency, so as to prevent the radar signal from mixing. After digital down conversion processing, two baseband signals are obtained, and the phase information of the radar sampling signal is extracted. Based on the Midamble code, the frequency offset estimation program of marine radar sampling signal is designed. the frequency offset estimation result of the signal can be obtained by executing the established procedure, and the frequency offset estimation of the sampling signal of the X-band marine radar can be realized. Experimental data show that after the application of the proposed method, the minimum signal to noise ratio of radar sampling signal is 4 dB, the minimum mean square error of frequency offset estimation is 4%, and the minimum time of frequency offset estimation is 2 s, which fully confirms that the proposed method has better application performance. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Radar signal processing

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Android Malware Risk Evaluation Using Fuzzy Logic 7

Android Malware Risk Evaluation Using Fuzzy Logic

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7th international conference on Parallel, Distributed and Grid Computing, PDGC 2022

作者： Dhalaria, Meghna Gandotra, Ekta National Institute of Technology Hamirpur Department of Computer Science and Engineering H.P Hamirpur India Jaypee University of Information Technology Department of Computer Science and Engineering and Information Technology Waknaghat H.P. Solan India

ISBN: (纸本)9781665454018

the static and dynamic malware analysis are used by industrialists and academics to understand malware capabilities and threat level. the antimalware industries calculate malware threat levels using different techniques which involve human involvement and a large number of resources and analysts. As malware complexity, velocity and volume increase, it becomes impossible to allocate so many resources. Due to this reason, it is projected that the number of malware apps will continue to rise, and that more devices will be targeted in order to commit various sorts of cybercrime. It is therefore necessary to develop techniques that can calculate the damage or threat posed by malware automatically as soon as it is identified. In this way, early warnings about zero-day (unknown) malware can assist in allocating resources for carrying out a close analysis of it as soon as it is identified. In this paper, a fuzzy modelling approach is described for calculating the potential risk of malicious programs through static malware analysis. © 2022 IEEE.

关键词： Fuzzy logic

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Literature review on human-computer interaction research in marketing field under the background of big data: A bibliometric research through CiteSpace 7

Literature review on human-computer interaction research in ...

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2022 7th international conference on information Science, computer technology and Transportation, ISCTT 2022

作者： Liang, Xuedong Yin, Hanyun Zhong, Xin Wang, Rong Business School Sichuan University Chengdu China Human Resource Management Sichuan Academy of Social Sciences Chengdu China Beijing Huaqing Chengyun Management Consulting Co. Ltd Beijing China

ISBN: (纸本)9783800760565

Purpose: From the perspective of academic literature, this research analyzes and summarizes the research of human-computer interaction in the field of marketing. through the analysis of the current development situation, we put forward suggestions for future academic research. Methodology: this research obtains relevant foreign literature from the Web of Science, uses scientific bibliometric methods through CiteSpace software to make analysis on the number of papers, authors, publishing journals and institutions, and puts forward the future development trend of human-computer interaction in the field of marketing through keyword co-occurrence analysis and cluster analysis. Finding: through literature review, this research found that after 2019, relevant research has shown a rapid growth trend in recent years. through keyword co-occurrence and cluster analysis, it shows that the research of human-computer interaction depends on the development of electronic information technology, and combined with users' personality differences and different perception, has become the key points of human-computer integration research. Intelligent immersive technology, anthropomorphic features of service robots, and diversification of interaction scenes will also become an important development direction of human-computer interaction research in the field of marketing in the future. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Marketing

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Comparative Analysis of CNN-based Deep Learning Approaches on Complex Activity Recognition 7

Comparative Analysis of CNN-based Deep Learning Approaches o...

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7th international conference on Digital Arts, Media and technology, DAMT 2022 and 5th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications Engineering, NCON 2022

作者： Mekruksavanich, Sakorn Jantawong, Ponnipa Jitpattanakul, Anuchit University of Phayao School of Information and Communication Technology Department of Computer Engineering Phayao Thailand King Mongkut's University of Technology North Bangkok Intelligent and Nonlinear Dynamic Innovations Research Center Faculty of Applied Science Department of Mathematics Bangkok Thailand

ISBN: (纸本)9781665495103

For those with Parkinson's disease, freezing of gait (FOG) could be a distressing condition. In individuals with diabetes, FOG could have a significant influence on their quality of life and cause falls, which can be dangerous. A questionnaire has traditionally been used to measure the severity of FOG symptoms;nevertheless, this technique is subjective and can not accurately reflect the intensity of this illness. the adoption of sensor-based devices may give reliable and objective information to follow the progression of symptoms, allowing for better Parkinson's disease management and therapy. A compact deep convolutional neural network comprising squeeze and excitation components, which we called SE-DeepConV model, was designed to identify FOG utilizing wearable data from the sensors. the SE-DeepConV model was constructed and evaluated using a publicly accessible standard FOG dataset, particularly the Daphnet dataset. the SE-DeepConV model outperforms other benchmark deep learning models in terms of accuracy, with the most outstanding accuracy of 95.65%, according to research observations. © 2022 IEEE.

关键词： Deep neural networks

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the classification-based machine learning algorithm to predict students' knowledge levels 7

The classification-based machine learning algorithm to predi...

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作者： Hongthong, Tew Temdee, Punnarumol Mae Fah Luang University Comp. and Commun. Engineering for Capacity Building Research Center School of Information Technology Chiang Rai Thailand

ISBN: (纸本)9781665495103

Innovation can give learning coherence in numerous unique situations when understudies cannot be truly present in their study halls. the current innovation and proactive systems are needed to advance a problematic type of schooling that does not make up for the customary learning climate. In any case, there are numerous boundaries to effective remote and internet learning driven by innovation. this research implemented k-mean clustering to a dataset of 146 students-the classification procedure for predicting grade outcomes using the decision tree technique. the attribute with the most significant effect on the classification of the student's grades is. the result is shown the grade property is the root node. this clustering technique acts as a benchmark for evaluating each student's growth and performance throughout their further education. © 2022 IEEE.

关键词： Students

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Image Forgery Detection Model using CNN Architecture with SVM Classifier 7

Image Forgery Detection Model using CNN Architecture with SV...

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7th international conference on Parallel, Distributed and Grid Computing, PDGC 2022

作者： Singh, Surjeet Sehgal, Vivek Kumar Jaypee University of Information Technology Department of Computer Science and Engineering and Infotmation Technology Waknaghat Himachal Pradesh Solan India

ISBN: (纸本)9781665454018

this Due to rapid advancement in computer vision system and easy availability of digital camera's acquisition of images and sharing the content on social media platform with falsify content is challenging task to the researcher community. For the legal purpose to provide the evidence in court, it's a difficult task identify the forgery in image that why various traditional artefacts of capturing device and internal footprints of image used to check the forgery in original image. Now a day's easy availability of software editing tools the captured image modify with wrong content to defame the person or misleading the people on social media with fake content. In this article, proposed a CNN based architecture to classify the forgery in given image. CNN architecture is capable to detect the unseen forgeries based on features extracted through various convolution layers and used SVM classifier to classify the label of forged image with high accuracy. © 2022 IEEE.

关键词： Digital forensics

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