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Research on intelligent access control technology of face recognition model based on parameter sharing and dense connection

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International Journal of Computational Intelligence Studies 2023年第3-4期12卷 255-270页

作者： Xu, Yonghua School of Computer Engineering Jinling Institute of Technology Jiangsu Nanjing211169 China Jiangsu Key Laboratory of Data Science and Smart Software Jinling Institute of Technology Nanjing211169 China

This study proposes a laboratory intelligent facial recognition system based on improved CNN, which significantly improves the accuracy of facial recognition by optimising the portrait recognition algorithm, improving CNN calculation and large parameter scale, and utilising perspective projection to improve portrait effect and sample utilisation. The experimental results show that the recognition rate has been improved by 10%, the CPU usage rate is less than 100%, and the model parameters have been reduced by more than 95%. This system can effectively and accurately recognise faces, making it suitable for embedded facial recognition devices. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Face recognition

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Diff-ID: An Explainable Identity Difference Quantification Framework for DeepFake Detection

arXiv

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arXiv 2023年

作者： Yu, Chuer Zhang, Xuhong Duan, Yuxuan Yan, Senbo Wang, Zonghui Xiang, Yang Ji, Shouling Chen, Wenzhi The College of Computer Science and Technology Zhejiang University Zhejiang Hangzhou310027 China The school of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States The School of Software and Electrical Engineering Swinburne University of Technology HawthornVIC3122 Australia

Despite the fact that DeepFake forgery detection algorithms have achieved impressive performance on known manipulations, they often face disastrous performance degradation when generalized to an unseen manipulation. Some recent works show improvement in generalization but rely on features fragile to image distortions such as compression. To this end, we propose Diff-ID, a concise and effective approach that explains and measures the identity loss induced by facial manipulations. When testing on an image of a specific person, Diff-ID utilizes an authentic image of that person as a reference and aligns them to the same identity-insensitive attribute feature space by applying a face-swapping generator. We then visualize the identity loss between the test and the reference image from the image differences of the aligned pairs, and design a custom metric to quantify the identity loss. The metric is then proved to be effective in distinguishing the forgery images from the real ones. Extensive experiments show that our approach achieves high detection performance on DeepFake images and state-of-the-art generalization ability to unknown forgery methods, while also being robust to image distortions. Copyright © 2023, The Authors. All rights reserved.

关键词： Image enhancement

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Long Short Term Memory (LSTM)-based Cuffless Continuous Blood Pressure Monitoring

Long Short Term Memory (LSTM)-based Cuffless Continuous Bloo...

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International Conference on VLSI Design

作者： Vijay Kumar Goldy Kolin Paul Mahesh Chowdhary Amar Nath and Shashi Khosla School of Information Technology Indian Institute of Technology Delhi India Department of Computer Science and Engineering Indian Institute of Technology Delhi India MEMS Software Solutions ST Microelectronics Santa Clara California United States

Continuously monitoring blood pressure (BP) is crucial for individuals at high risk of cardiac diseases. However, existing BP measurement techniques lack the ability to provide non-invasive and continuous monitoring. To address this challenge, researchers have recently explored accelerometer-based systems for BP estimation. These systems rely on signal processing algorithms that often necessitate extensive feature engineering, making updates and calibration difficult. In this paper, we propose a novel device for non-invasive continuous BP monitoring. The device consists of a patch with two inertial measurement units (IMUs) attached to the skin in the user’s neck region, specifically along the carotid artery. A control unit connected to the patch receives sensor data from these IMU units. It employs a machine learning (ML) model based on Long Short Term Memory (LSTM) to estimate BP using the sensor data. The model undergoes two general ML processes. The first ML process involves training the analysis model using a training set comprised of data from various individuals. Subsequently, the second machine learning process re-trains a portion of the analysis model using an individualized training set gathered from the specific user. This approach enhances the accuracy and personalization of the BP estimation, providing a promising solution for continuous monitoring of BP in high-risk *** BP monitoring device’s analysis model is also trained and tested on 11 volunteers. The BP monitoring device can measure an individual’s BP every 5 seconds. Additionally, the best root mean squared error (RMSE) loss obtained with our model is less than 2.932 mmHg for systolic BP and 2.231 mmHg for diastolic BP.

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An Empirical Mode Decomposition Fuzzy Forecast Model for Air Quality

Research Square

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Research Square 2021年

作者： Chen, Bo-Lun Zhu, Guo-Chang Sheng, Yi-Yun Xie, Qian Ji, Min Yu, Yong-Tao Faculty of Computer and software Engineering Huaiyin Institute of Technology Jiangsu Huaian223003 China

Air quality is related to people’s health. Severe air pollution can cause respiratory diseases, while good air quality is beneficial to physical and mental health. Therefore, the prediction of air quality is very important. As an important algorithm for signal analysis, empirical mode decomposition can analyze the change trend of air quality well, smooth the complex and changeable air quality data, and get the change trend of air quality under different time scales. According to the change trend under different time scales, the extreme learning machine is used for training, and the corresponding prediction value is obtained. The adaptive fuzzy inference system is used for fitting to obtain the final air quality prediction result. The experimental results show that the signal decomposition fuzzy prediction model has a good learning ability and has good accuracy in predicting the concentration of various pollutants in air quality. © 2021, CC BY.

关键词： Health

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Transformer-based Text Classification on Unified Bangla Multi-class Emotion Corpus

Transformer-based Text Classification on Unified Bangla Mult...

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Information technology (ACIT)

作者： Md Sakib Ullah Sourav Mohammad Sultan Mahmud Hua Zheng Mohammad Aljaidi Md. Simul Hasan Talukder Rejwan Bin Sulaiman Abdullah Hafez Nur Ahmad Al-Qerem School of Management Science and Engineering Shandong University of Finance and Economics Jinan China College of Computer Science and Software Engineering Shenzhen University Senzhen China Department of Software Engineering Software Engineering Institute of Guangzhou Guangzhou China Department of Computer Science Zarqa University Zarqa Jordan College of Engineering University of Business and Technology Jeddah Saudi Arabia Department of Electrical and Electronic Engineering Dhaka University of Engineering and Technology Dhaka School of Computer Science & Technology Northumbria University Newcastle Tayne United Kingdom Northumbria UK Department of Electronic and Telecommunication Engineering International Islamic University Chittagong Chittagong Bangladesh Department of Computer Science Faculty of Information Technology Zarqa University Zarqa Jordan

ISBN: (数字)9798331540012

ISBN: (纸本)9798331540029

Due to its importance in studying people’s thoughts on various Web 2.0 services, emotion classification is a critical undertaking. Most existing research is focused on the English language, with little work on low-resource languages. Though sentiment analysis, particularly emotion classification in English, has received increasing attention in recent years, little study has been done in the context of Bangla, one of the world’s most widely spoken languages. In this research, we propose a complete set of approaches for identifying and extracting emotions from Bangla texts. We provide a Bangla emotion classifier for six classes, i.e., anger, disgust, fear, joy, sadness, and surprise, from Bangla words using transformer-based models, which exhibit phenomenal results in recent days, especially for high-resource languages. The Unified Bangla Multi-class Emotion Corpus (UBMEC) is used to assess the performance of our models. UBMEC is created by combining two previously released manually labelled datasets of Bangla comments on six emotion classes with fresh manually labelled Bangla comments created by us. The corpus dataset and code we used in this work are publicly available.

关键词： Measurement Human computer interaction Sentiment analysis Analytical models Codes Accuracy Web 2.0 Text categorization Transformers Information technology

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MLFuse: Multi-Scenario Feature Joint Learning for Multi-Modality Image Fusion

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IEEE Transactions on Multimedia 2025年

作者： Lei, Jia Li, Jiawei Liu, Jinyuan Wang, Bin Zhou, Shihua Zhang, Qiang Wei, Xiaopeng Kasabov, Nikola K. Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China Dalian University of Technology School of Mechanical Engineering Dalian116024 China Dalian University of Technology School of Computer Science and Technology Dalian116024 China Auckland University of Technology Knowledge Engineering and Discovery Research Institute Auckland1010 New Zealand Ulster University Intelligent Systems Research Center LondonderryBT52 1SA United Kingdom

Multi-modality image fusion (MMIF) entails synthesizing images with detailed textures and prominent objects. Existing methods tend to use general feature extraction to handle different fusion tasks. However, these methods have difficulty breaking fusion barriers across various modalities owing to the lack of targeted learning routes. In this work, we propose a multi-scenario feature joint learning architecture, MLFuse, that employs the commonalities of multi-modality images to deconstruct the fusion progress. Specifically, we construct a cross-modal knowledge reinforcing network that adopts a multipath calibration strategy to promote information communication between different images. In addition, two professional networks are developed to maintain the salient and textural information of fusion results. The spatial-spectral domain optimizing network can learn the vital relationship of the source image context with the help of spatial attention and spectral attention. The edge-guided learning network utilizes the convolution operations of various receptive fields to capture image texture information. The desired fusion results are obtained by aggregating the outputs from the three networks. Extensive experiments demonstrate the superiority of MLFuse for infrared-visible image fusion and medical image fusion. The excellent results of downstream tasks (i.e., object detection and semantic segmentation) further verify the high-quality fusion performance of our method. The code is publicly available at https://***/jialei-sc/MLFuse. © 1999-2012 IEEE.

关键词： Semantic Segmentation

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Boosting performance of virtualized desktop infrastructure with physical GPU and SPICE

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Science China(Information Sciences) 2020年第7期63卷 236-238页

作者： Shupan LI Limin XIAO Chungang SHI Liequan CHE Changyou ZHANG Yuanzhang LI State Key Laboratory of Software Development Environment Beihang University School of Computer Science and Engineering Beihang University Beijing Jinghang Computation and Communication Research Institute Institute of Software Chinese Academy of Sciences School of Computer Science and Technology Beijing Institute of Technology

Dear editor,The virtual desktop infrastructure (VDI) is widely used by enterprises, as it can be easily deployed,has a reduced management cost, improves resource utilization, and can be accessed at any location by the network. Currently, there is a demand for the VDIs to support applications, such as playing 3D games, playing HD videos, and using 3D design-

关键词： visualized desktop infrastructure SPICE physical GPU The virtual machine (VM) virtual machine monitor (VMM)

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CRFs for Digital Signature and NIZK Proof System in Web Services 1

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22nd International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2022

作者： Kang, Burong Zhang, Lei Yang, Yafang Meng, Xinyu Engineering Research Center of Software/Hardware Co-design Technology and Application Ministry of Education East China Normal University Shanghai200062 China Science and Technology on Communication Security Laboratory Sichuan610041 China Research Institute of China Telecom Corporation Limited Shanghai200062 China School of Computer Science Fudan University Shanghai200433 China

ISBN: (数字)9783031226779

ISBN: (纸本)9783031226762

Web services are service-oriented computing technology which allows computers running different operating domains to access and share each other’s databases. Each web service is an application (like online business) which may require the private information of users. Thus, it will be important to preserve these web users’ individual privacy. The traditional approaches to achieve this goal in web security is to use the cryptographic technologies, such as digital signature, NIZK proof system. Whereas, some recent research results indicate that these cryptographic technologies may suffer from the algorithm substitution attack (ASA). ASA means that the cryptographic technology would be embedded some backdoor in the process of its implementation by the attacker, and with the backdoor information the attacker can steal the user’s private information. To address this problem, the concept of cryptographic reverse firewall (CRF) has been introduced, which could sanitize the messages inputting and outputting the user’s computer. In this paper, we construct the CRFs for the efficient Pointcheval-Sanders (PS) signature as well as the NIZK proof system. © 2023, Springer Nature Switzerland AG.

关键词： Web services

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The Application of Blockchain technology in the Area of Satellite Remote Sensing Data

The Application of Blockchain Technology in the Area of Sate...

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International Conference on Agro-Geoinformatics

作者： Haiyu He Yongheng Shang Xiaoyu Zhang Jianwei Yin Shuiguang Deng Meng Han School of Software Engineering Zhejiang University Ningbo China Institute of Advanced Technology Zhejiang University Hangzhou China School of Earth Sciences Zhejiang University Hangzhou China School of Computer Science and Technology Zhejiang University Hangzhou China Binjiang Institute of Zhejiang University Hangzhou China

ISBN: (数字)9798350380606

ISBN: (纸本)9798350380613

The growth in the number of satellites and the wide expansion of application areas, driven by continuous progress in Satellite Remote Sensing Data technology, have led to an increasingly obvious trend toward commercialization and marketization. However, as Satellite Remote Sensing Data is an important data asset, it requires higher standards of data security and privacy protection. The traditional centralized data storage and management approach has the risk of a single point of failure, which can easily lead to data tampering and loss, while the lack of a reliable trust mechanism between multi-organizational data parties limits data integration and transactions. Against this background, this paper develops an innovative on-chain-off-chain data distributed storage and transaction system based on blockchain technology, aiming to address the many challenges faced in the area of Satellite Remote Sensing Data. Firstly, by adopting the distributed ledger technology of blockchain, this system ensures the security and integrity of data assets. The decentralized nature of the blockchain allows data to no longer be stored centrally in a single entity, thus avoiding the single-pointof-failure problem of traditional storage methods. Each transaction is recorded on the blockchain, forming an untamperable chain structure, effectively preventing data tampering and loss, and enhancing the overall security of data assets. Secondly, the system in this paper introduces smart contracts in the data transaction behavior, which realizes the automation of data transaction records on the chain through the automated execution of smart contracts. When a data transaction occurs, the smart contract is triggered to execute, and the transaction data can be encrypted and uploaded to the chain, thus safeguarding the privacy information of both parties to the transaction. This mechanism not only improves the security of data but also strengthens the transparency and credibility of the data transact

关键词： Data privacy Satellites Smart contracts Authentication Blockchains Security Reliability

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Entirety of Quantum Uncertainty and Its Experimental Verification

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Chinese Physics Letters 2021年第7期38卷 11-16页

作者： Jie Xie Li Zhou Aonan Zhang Huichao Xu Man-Hong Yung Ping Xu Nengkun Yu Lijian Zhang National Laboratory of Solid State Microstructures College of Engineering and Applied Sciences and School of PhysicsNanjing UniversityNanjing 210093China Collaborative Innovation Center of Advanced Microstructures Nanjing UniversityNanjing 210093China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Shenzhen Institute for Quantum Science and Engineering and Department of Physics Southern University of Science and TechnologyShenzhen 518055China Shenzhen Key Laboratory of Quantum Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Institute for Quantum Information&State Key Laboratory of High Performance Computing College of ComputerNational University of Defense TechnologyChangsha 410073China Centre for Quantum Software and Information School of SoftwareFaculty of Engineering and Information TechnologyUniversity of Technology SydneyNSWAustralia

As a foundation of quantum physics,uncertainty relations describe ultimate limit for the measurement uncertainty of incompatible ***,uncertainty relations are formulated by mathematical bounds for a specific *** we present a method for geometrically characterizing uncertainty relations as an entire area of variances of the observables,ranging over all possible input *** find that for the pair of position and momentum operators,Heisenberg's uncertainty principle points exactly to the attainable area of the variances of position and ***,for finite-dimensional systems,we prove that the corresponding area is necessarily semialgebraic;in other words,this set can be represented via finite polynomial equations and inequalities,or any finite union of such *** particular,we give the analytical characterization of the areas of variances of(a)a pair of one-qubit observables and(b)a pair of projective observables for arbitrary dimension,and give the first experimental observation of such areas in a photonic system.

关键词： observable union operators

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