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IEEE Transactions on Intelligent Vehicles 2023年 1-13页

作者： Yuan, Di Zhang, Haiping Shu, Xiu Liu, Qiao Chang, Xiaojun He, Zhenyu Shi, Guangming Guangzhou Institute of Technology Xidian University Xian China School of Computer Science and Cyber Engineering Guangzhou University Guangzhou China National Center for Applied Mathematics Chongqing Normal University Chongqing China Faculty of Engineering and Information Technology University of Technology Sydney Broadway New South Wales Australia School of Computer Science and Technology Harbin Institute of Technology Shenzhen China

With the continuous advancement of autonomous driving technology, 3D vehicle detection has become of widespread interest. The traditional aggregate view object detection (AVOD) framework has achieved some good results in 3D vehicle detection tasks. However, the complexity of the 3D vehicle detection scenario makes the current detection methods still not meet the actual requirements. To enhance the detection accuracy of 3D vehicle targets, we propose to equip an attention mechanism to improve the representation capability of feature maps, thereby further increasing the precision of 3D vehicle detection. Specifically, we have added the channel attention ECANet, spatial attention SANet, and mixed attention ECANet+SANet respectively into the image-based feature pyramid network of the AVOD detection framework, which can enhance the feature maps representation and improve the detection accuracy observably. The improved AVOD network is verified using the KITTI dataset. By showing the detection results of these attention mechanisms, it is found that the feature pyramid networks (FPN) module in the AVOD network based on Image has the best performance when integrating a mixed attention mechanism. In comparison to the original AVOD network, the detection results on the average precision index of the proposed method have improved by 2.29%, 2.81%, and 1.32% in the three indexes of simple, medium, and difficult, respectively. Extensive experiments have confirmed the practicality and efficacy of the AVOD network to equip the attention mechanisms for 3D vehicle detection. IEEE

关键词： Semantics

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Brain-inspired artificial intelligence research: A review

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Science China(Technological Sciences) 2024年第8期67卷 2282-2296页

作者： WANG GuoYin BAO HuaNan LIU Qun ZHOU TianGang WU Si HUANG TieJun YU ZhaoFei LU CeWu GONG YiHong ZHANG ZhaoXiang HE Sheng Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and TelecommunicationsChongqing 400065China Key Laboratory of Cyberspace Big Data Intelligent Security Chongqing University of Posts and TelecommunicationsChongqing 400065China College of Computer and Information Science Chongqing Normal UniversityChongqing 401331China State Key Laboratory of Brain and Cognitive Science Institute of BiophysicsChinese Academy of SciencesBeijing 100101China School of Psychological and Cognitive Sciences Peking UniversityBeijing 100871China State Key Laboratory of Multimedia Information Processing School of Computer SciencePeking UniversityBeijing 100871China Department of Computer Science School of ElectronicsInformation and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Faculty of Electronic and Information Engineering Xi’an Jiaotong UniversityXi’an 710049China The Center for Research on Intelligent Perception and Computing Institute of AutomationChinese Academy of SciencesBeijing 100190China Institute of Biophysics Chinese Academy of SciencesBeijing 100101China

Artificial intelligence(AI) systems surpass certain human intelligence abilities in a statistical sense as a whole, but are not yet the true realization of these human intelligence abilities and behaviors. There are differences, and even contradictions, between the cognition and behavior of AI systems and humans. With the goal of achieving general AI, this study contains a review of the role of cognitive science in inspiring the development of the three mainstream academic branches of AI based on the three-layer framework proposed by David Marr, and the limitations of the current development of AI are explored and analyzed. The differences and inconsistencies between the cognition mechanisms of the human brain and the computation mechanisms of AI systems are analyzed. They are found to be the cause of the differences and contradictions between the cognition and behavior of AI systems and humans. Additionally, eight important research directions and their scientific issues that need to focus on braininspired AI research are proposed: highly imitated bionic information processing, a large-scale deep learning model that balances structure and function, multi-granularity joint problem solving bidirectionally driven by data and knowledge, AI models that simulate specific brain structures, a collaborative processing mechanism with the physical separation of perceptual processing and interpretive analysis, embodied intelligence that integrates the brain cognitive mechanism and AI computation mechanisms,intelligence simulation from individual intelligence to group intelligence(social intelligence), and AI-assisted brain cognitive intelligence.

关键词： artificial intelligence cognitive science brain science intelligence science large language model

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A CH9 Low-Profile Circularly-Polarized Antenna for Indoor Positioning 7

A CH9 Low-Profile Circularly-Polarized Antenna for Indoor Po...

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7th World Conference on Computing and Communication Technologies, WCCCT 2024

作者： Zhang, Zhenfeng Feng, Botao Gu, Wenzhe Ding, Xiao Sun, Sanshan Deng, Li Shenzhen University College of Electronics and Information Engineering Shenzhen518060 China Huizhou University School of Computer Science and Engineering Huizhou516007 China Macau University of Science and Technology Faculty of Humanities and Arts 999078 China Sichuan Normal University College of Physics and Electronic Engineering Sichuan China Beijing University of Posts and Telecommunications College of Information and Communication Engineering Beijing China

ISBN: (纸本)9798350372328

This paper presents a low-profile CH9 circularly polarized 3-element multiple input multiple output (MIMO) antenna for precise positioning applications. The feeding structure of the antenna employs a conventional wilkinson power divider to achieve circular polarization, where the feeding structure and the radiating patch are located on the same layer of the dielectric substrate with a grounded backside. The -10-dB bandwidth of each antenna element ranges from 7.04 to 8.55 GHz, with a gain larger than 2.21 dBi within the desired bandwidth. In order to enhance localization accuracy and minimize the impact of spatial correlation, the distance interval between antenna elements is designed to be 12.5 mm. Experimental results show that when ports 1, 2 and 3 are excited with equal amplitude phase differences of 0 °, 90 ° and -90 °, respectively, the frequency bandwidth of the MIMO antenna is ranging from 7.61 to 8.48 GHz, with corresponding gain fluctuating from 5.39 to 8.07 dBi. In addition, the circularly polarized bandwidth is from 7 to 8.89 GHz, which fully covers the CH9 frequency band. © 2024 IEEE.

关键词： Bandwidth

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A Novel Phase Shifter for 5G Base Station Antenna 7

A Novel Phase Shifter for 5G Base Station Antenna

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7th World Conference on Computing and Communication Technologies, WCCCT 2024

作者： Du, Lin Feng, Botao Ding, Xiao Gu, Wenzhe Sun, Sanshan Deng, Li Shenzhen University College of Electronics and Information Engineering Shenzhen518060 China Macau University of Science and Technology Faculty of Humanities and Arts 999078 China Huizhou University School of Computer Science and Engineering Huizhou516007 China Sichuan Normal University College of Physics and Electronic Engineering Sichuan China Beijing University of Posts and Telecommunications College of Information and Communication Engineering Beijing China

ISBN: (纸本)9798350372328

In this paper, a phase shifter for the base station antenna with low cost, ease of manufacturing and good performance on phase shift is presented. The phase shifter consists of a metal shell, a substrate, two dielectric plates, and two conductor lines. The phase shift is realized by moving the dielectric plates longitudinally, which cover the conductor lines. With the slots in dielectric materials, the slotted part of dielectric plates can function similarly to a quarter-wavelength impedance matching. Therefore, the function of this phase shifter is that the voltage standing wave ratio (VSWR) and power distribution ratio can be guaranteed when the dielectric plate is moved. The phase shifter exhibits a bandwidth of 1.7-2.1 GHz and the corresponding phase shift is 86.88° when the dielectric plate moves by 90 mm. Moreover, its good physical features including light weight, low cost, and easy fabrication make it well suitable for base station antenna applications. © 2024 IEEE.

关键词： Phase shifters

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A Vision-Based Auricular Diagnosis Assistance System with Deep Learning 4

A Vision-Based Auricular Diagnosis Assistance System with De...

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4th IEEE Global Conference on Life Sciences and Technologies, LifeTech 2022

作者： Chiang, Meng-Lin Hou, Ling Fang, Chiung-Yao Yamazaki, Tatsuya National Taiwan Normal University Department of Computer Science Information Engineering Taipei Taiwan Niigata University School of Engineering Faculty of Engineering Niigata Japan

ISBN: (纸本)9781665419048

In the area of auricular medicine research, researchers believe that human diseases are reflected in corresponding locations on the external ears, known as the positive reactions of auricular points. If some auricular points on a person's external ear exhibit abnormal positive reactions, then the person is being attacked by a corresponding disease. This paper proposes a vision-based auricular diagnosis assistance system to help doctors detect diseases by discovering the visual positive reactions of auricular points on patients' external ears. The proposed vision-based auricular diagnosis assistance system includes visual positive reaction detection and disease identification. First, external ear images are input into the system to detect the visual positive reactions of the auricular points on the external ear using an improved version of the U-Net model. Improvements of the U-Net model include batch standardization, atrous convolution, convolution stage reduction, and multi-expansion-rate integration. Second, the detection results of visually positive reactions are then used to identify the diseases. This study identified nine types of diseases through their corresponding positive reactions, including hepatitis, mastitis, cervicitis, prostatitis, frontal headache, migraine, occipital headache, vertex headache, and headache. The dataset used in this study was collected by the authors and called the CVIU 108 EAR Dataset. The experimental results show that the disease diagnosis accuracy rate of the proposed system is 99.60%. © 2022 IEEE.

关键词： Semantic Segmentation

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Research on inscription rubbings text detection based on deep learning 2021

Research on inscription rubbings text detection based on dee...

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4th International Conference on information Systems and computer Aided Education, ICISCAE 2021

作者： Song, Xu Liu, Guoying Wang, Zhiyin School of Computer and Information Engineering Anyang Normal University Anyang China Key Laboratory of Oracle Bone Inscriptions Information Processing Ministry of Education Anyang China

ISBN: (纸本)9781450390255

It is of great practical significance to use advanced digital and intelligent technology to digitally apply and effectively protect China's ancient cultural heritage and resolve the problems that cannot be solved by manpower in a faster and more efficient way. Based on the YOLOv4 target detection algorithm, this paper effectively expands the collected data according to the data characteristics of inscription rubbings and text images, and carries out many training and verification tests. The accuracy of the detection model is 92.3%, so as to improve the speed and quality of rubbing arrangement of inscriptions. © 2021 ACM.

关键词： Deep learning

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Physical Layer Security in Untrusted Diamond Relay Networks with Imperfect Source-Relay Links

Physical Layer Security in Untrusted Diamond Relay Networks ...

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2022 International Symposium on Networks, computers and Communications, ISNCC 2022

作者： Qian, Shen He, Xin Zhou, Xiaobo Faculty of Engineering Kanagawa University Department of Information Systems Creation Japan Anhui Normal University School of Computer and Information China Tianjin University School of Computer Science and Technology China

ISBN: (数字)9781665485449

ISBN: (纸本)9781665485449

A two-untrusted-relay transmission scheme is proposed with lossy-forward (LF) relaying being utilized. Two untrusted relays are located between one source and one common destination and there is no direct link between the source and the destination, which referred to as diamond relaying network. Since LF relaying allows intra-link errors and always forwards the decoded information sequences from the relays to the destination, it realizes the reliable and secure transmission of decoder-and-forward based relay networks with untrusted relays. Reliable-and-secure probability is derived to evaluate the performance of the untrusted relay networks, which represents the probability that the destination can recover the original message sent from the source whereas the relays cannot. We find that as long as the contributions of the transmit power of source and relays are balanced, a certain degree of reliable-and-secure probability can be held, even without the support from a friendly jamming signal. © 2022 IEEE.

关键词： Probability

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Enhancing Mild Cognitive Impairment Detection through Efficient Magnetic Resonance Image Analysis

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computers, Materials & Continua 2024年第8期80卷 2081-2098页

作者： Atif Mehmood Zhonglong Zheng Rizwan Khan Ahmad Al Smadi Farah Shahid Shahid Iqbal Mutasem K.Alsmadi Yazeed Yasin Ghadi Syed Aziz Shah Mostafa M.Ibrahim Department of Computer Science and Technology Zhejiang Normal UniversityJinhua321002China Zhejiang Institute of Photoelectronics&Zhejiang Institute for Advanced Light Source Zhejiang Normal UniversityJinhua321004China Department of Data Science and Artificial Intelligence Zarqa UniversityZarqa13100Jordan School of Chemical and Environmental Engineering College of ChemistryChemical Engineering andMaterials ScienceSoochow UniversitySuzhou215123China Department of Management Information Systems College of Applied Studies and Community ServiceImam Abdulrahman Bin Faisal UniversityDammam32244Saudi Arabia Department of Computer Science Al Ain UniversityAbu Dhabi999041United Arab Emirates Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61519Egypt Healthcare Technology and Innovation Theme Faculty Research Centre for Intelligent HealthcareCoventry UniversityCoventryCV48BWUK

Neuroimaging has emerged over the last few decades as a crucial tool in diagnosing Alzheimer’s disease(AD).Mild cognitive impairment(MCI)is a condition that falls between the spectrum of normal cognitive function and ***,previous studies have mainly used handcrafted features to classify MCI,AD,and normal control(NC)*** paper focuses on using gray matter(GM)scans obtained through magnetic resonance imaging(MRI)for the diagnosis of individuals with MCI,AD,and *** improve classification performance,we developed two transfer learning strategies with data augmentation(i.e.,shear range,rotation,zoom range,channel shift).The first approach is a deep Siamese network(DSN),and the second approach involves using a cross-domain strategy with customized *** performed experiments on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset to evaluate the performance of our proposed *** experimental results demonstrate superior performance in classifying the three binary classification tasks:NC ***,NC ***,and MCI ***,we achieved a classification accuracy of 97.68%,94.25%,and 92.18%for the three cases,*** study proposes two transfer learning strategies with data augmentation to accurately diagnose MCI,AD,and normal control individuals using GM *** findings provide promising results for future research and clinical applications in the early detection and diagnosis of AD.

关键词： Alzheimer’s disease mild cognitive impairment normal control transfer learning classification augmentation

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Online Learning Behavior Analysis and Prediction Based on Spiking Neural Networks

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Journal of Social Computing 2024年第2期5卷 180-193页

作者： Yanjing Li Xiaowei Wang Fukun Chen Bingxu Zhao Qiang Fu the Institute of Education Science Research Heilongjiang UniversityHarbin 150080China the School of Cyberspace Security Shandong University of Political Science and LawJinan 250014China the School of Computer Science and Technology Harbin Engineering UniversityHarbin 150001China the Faculty of Electrical and Computer Engineering University of VictoriaVictoriaV8P 5C2Canada. the Guangxi Key Lab of Brain-Inspired Computing and Intelligent Chips School of Electronic and Information EngineeringGuangxi Normal UniversityGuilin 541004China

The vast amount of data generated by large-scale open online course platforms provide a solid foundation for the analysis of learning behavior in the field of *** study utilizes the historical and final learning behavior data of over 300000 learners from 17 courses offered on the edX platform by Harvard university and the Massachusetts Institute of Technology during the 2012-2013 academic *** have developed a spike neural network to predict learning outcomes,and analyzed the correlation between learning behavior and outcomes,aiming to identify key learning behaviors that significantly impact these *** goal is to monitor learning progress,provide targeted references for evaluating and improving learning effectiveness,and implement intervention measures *** results demonstrate that the prediction model based on online learning behavior using spiking neural network achieves an impressive accuracy of 99.80%.The learning behaviors that predominantly affect learning effectiveness are found to be students’academic performance and level of participation.

关键词： online learning learning outcomes prediction learning behavior analysis spiking neural network

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Essential proteins identification based on weak consensus model and neighborhood aggregation centrality

Essential proteins identification based on weak consensus mo...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Hu, Zhipeng Li, Gaoshi Wu, Jingli Luo, Xinlong Liu, Jiafei Peng, Wei Zhu, Xiaoshu Guangxi Normal University Key Lab of Education Blockchain and Intelligent Technology Ministry of Education Guilin541004 China Guangxi Normal University Guangxi Key Lab of Multi-Source Information Mining & Security Guilin541004 China Guangxi Normal University College of Computer Science and Engineering Guilin541004 China Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650500 China Guilin University of Electronic Science and Technology School of Computer and Information Security & School of Software Engineering Guilin China

ISBN: (纸本)9798350337488

Essential proteins play an essential role in cell survival and replication. Currently, more and more computational methods are developed to identify essential proteins, which overcome the time-consuming, costly and inefficient shortcomings with biological experimental methods. In order to improve the recognition rate, some new methods by fusing multiple features are developed, but they seldom consider the connection among features. After analyzing a large number of methods based on multi-feature fusion, a weak consensus model to fuse features is proposed in this paper. Then, this paper uses the weak consensus model to fuse protein-protein interaction network, gene expression data, and orthologous data, thus proposing a new method, WOL. Then experiments are performed on one *** dataset. The results show that compared with WDC, PeC, ION, JDC, NCCO and E_POC, WOL has a higher recognition rate. © 2023 IEEE.

关键词： Essential proteins orthologous data protein-protein interaction weak consensus model

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