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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
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Blog Post number 4
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Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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patents
Patents & Software Copyright
Published:
- Patent
- 一种虚拟火灾场景下多智能体情景规划方法 (申请号:202110978546.4)
- 一种面向 Web3D 的人造模型网页轻量级可视化方法.(申请号:201811446227.3)
- 新一代云技术框架下海量三维模型集成平台.(申请号:201811590873.7)
- 基于循环神经网络的虚拟现实场景下人机交互方法及系统.(申请号:201811592245.2)
- Software copyright:
- 虚拟火灾逃生演练系统V1.0. (登记号:2022SR0438966)
- 虚拟教室自动布局设计系统v1.0. (登记号:2022SR0973155 )
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
projects
Natural Science Research Projects
- Project 01:
- Source: University Natural Science Research Project of Anhui Province(No. 2023AH050142)
- Research terms: 2024.1 - 2025.12
- Current status: Under research
- My role: Principal
- Project 02 :
- Source: National Natural Science Foundation of China (NSFC), Youth Project (No.61902003)
- Research terms: 2020.1 - 2022.12
- Current status: Completed
- My role: Principal
- Project 03:
- Source: National Natural Science Foundation of China (NSFC), General Project (No. 61976006)
- Research terms: 2020.1 - 2023.12
- Current status: Completed
- My role: Participant
- In Chinese:
- 安徽省高校科研重点项目(No.2023AH050142)”面向虚拟场景的虚实融合学习和交互方法的研究”,2024.1-2025.12,主持 (在研)
- 国家自然科学基金青年项目NSFC (No. 61902003) "面向WebVR的轻量级三维模型检索关键技术研究", 2020.1-2022.12, 主持 (已结题)
- 国家自然国家自然科学基金面上项目NSFC (No. 61976006) "面向功能磁共振成像的动态脑网络分析及应用研究", 2020.1-2023.12, 参与 (已结题)
University Teaching Research Projects
Published:
- In Chinese :
- 安徽省质量工程一般项目(No. 2022jyxm563),数字图像处理课程多元混合式教学方法的探索与实践,2023-2025, 主持
- 安徽师范大学教研项目 (校教字〔2020〕44 号),”新工科”建设背景下人工智能专业教学模式的研究,2022-2024,主持
- 安徽省质量工程虚拟仿真实验教学课程(No.2020xfxm23), 计算机组成虚拟实验,2022-2024,参与
- 安徽省质量工程教学团队(皖教秘高[2020]155号),计算机系统能力培养教学团队, 2022-2025, 参与
publications
WebVR Human-centered Indoor Layout Design Framework using a Convolutional Neural Network and Deep Q-learning
Published in IEEE Access, 2019
Web3D layout design framework based on DQN and CNN.
Recommended citation: Wen Zhou, W. JIANG, W. BIAN, B. JIE, WebVR Human-centered Indoor Layout Design Framework using a Convolutional Neural Network and Deep Q-learning. IEEE Access, 2019, 7(1):185773-185785.
Web3D learning framework for 3D Shape retrieval based on hybrid Convolutional Neural Networks
Published in Tsinghua Science and Technology, 2019
realizing the 3D sketch-based shape retrieval using Hybrid CNN method.
Recommended citation: Wen Zhou, J. JIA, C. HUANG, Y. CHENG, Web3D learning framework for 3D Shape retrieval based on hybrid Convolutional Neural Networks. Tsinghua Science and Technology, 2019, 25(1): 93-102
Training convolutional Neural Network for sketch recognition on large-scale dataset
Published in The International Arab Journal of Information Technology, 2020
Sketch recognition based on Convolutional Neural Network.
Recommended citation: Wen Zhou, J. JIA, Training convolutional Neural Network for sketch recognition on large-scale dataset.The International Arab Journal of Information Technology,2020,17(1):82-89.
Training Deep Convolutional Neural Networks to Acquire the Best View of a 3D Shape
Published in Multimedia Tools and Applications, 2020
Acquring the best view to achieve 3D shape transforming 2D images, which is the best respresentation for 3D shape.
Recommended citation: Wen Zhou, J. Jia "Training Deep Convolutional Neural Networks to Acquire the Best View of a 3D Shape"[J]. Multimedia Tools and Applications, 2020, 79(1):581-601.
Sketch Augmentation-driven Shape Retrieval Learning Framework Based on Convolutional Neural Networks
Published in IEEE Transactions on Visualization and Computer Graphics, 2021
Augmentated-driven sketch-based shape retrieval.
Recommended citation: Wen Zhou, J. Jia, W. Jiang, C. Huang, Sketch Augmentation-driven Shape Retrieval Learning Framework Based on Convolutional Neural Networks. IEEE Transactions on Visualization and Computer Graphics, 2021,27(8):3558–3570.
A robust approach for privacy data protection: IoT security assurance using generative adversarial imitation learning
Published in IEEE Internet of Things Journal, 2021
With the increasing importance of data security, privacy protection has gradually risen to a strategic position, especially IoT data privacy protection. The concern for data security has become a national strategy. The discovery of potential risks of privacy data is of great significance, such as the risk of data privacy leakage, data security vulnerabilities, etc. In this article, starting from the privacy data protection mechanism in the Industrial Internet of Things (IIoT) scenario, we proposed a method based on generative adversarial imitation learning (GAIL) to discover the privacy data security risks in IIoT by training privacy protection agents using a large amount of expert data on privacy protection. Finally, our proposed method is validated by relevant simulation experiments, and the results show that our proposed method has wide generalizability and reliability to obtain the maximum payoff of the agents and thus, reduce the risk of data security leakage
Recommended citation: C. Huang, S. Chen, Y. Zhang, Wen Zhou*, etc. "A robust approach for privacy data protection: IoT security assurance using generative adversarial imitation learning." IEEE Internet of Things Journal. 2021,9(18):17089-17097.
Multiagent Evacuation Framework for a Virtual Fire Emergency Scenario Based on Generative Adversary Imitation Learning
Published in Computer Animation and Virtual Worlds, 2022
MultiAgents GAIL methods for conducting the fire path planning on virutal fire emeregency scenario.
Recommended citation: Wen Zhou,W. Jiang, B. Jie, W. Bian. "Multiagent Evacuation Framework for a Virtual Fire Emergency Scenario Based on Generative Adversary Imitation Learning." Computer Animation and Virtual Worlds. 2022, 33(1): e2035.
An Improved Federated Learning Approach Enhanced Internet of Health Things Framework for Private Decentralized Distributed Data
Published in Information Science, 2022
With the privacy protection increasingly being concerned, Data centralization often heavily causes a big risk of privacy protection, gradually, there is a prevailing trend to enhance the security performance by means of data decentralization, above all, for health care internet of things(IoT) data.Meanwhile, Federated learning has obvious privacy advantages compared to data center training on protecting privacy data.For this reason, a novel framework based on federated learning is presented in this paper, which is suitable for private and decentralized data sets, such as big data in healthy Internet of Things. Specifically, the main work of the puts forward framework includes: (1)Multi-center data collection of healthy Internet of Things. (2)healthy data analysis of Internet of Things. (3)privacy protection method for data of healthy Internet of Things. Finally, related experiments show that the proposed method is feasible, and compared with the traditional methods, it has significantly improved the performace in Quality of Service (QoS) and IoUs indicator.
Recommended citation: Huang, C., Xu, G., Chen, S., Zhou, Wen*, NG, E. Y., & de Albuquerque, Victor Hugo C. de Albuquerque*. An Improved Federated Learning Approach Enhanced Internet of Health Things Framework for Private Decentralized Distributed Data. Information Sciences, 2022, 614:138-152
Dual deep Q-learning network guiding a multiagent path planning approach for virtual fire emergency scenarios
Published in Applied Intelligence, 2023
With continuous deterioration of the natural environment and the corresponding significant increase in the occurrence of disasters, forest fire accidents have frequently occurred in recent decades. Therefore, it is important to perform extensive effective fire drills to increase evacuation experience and emergency reaction capacity. In comparison to traditional fire drills, which are subject to many latent uncertainties and incur high costs, fire exercises based on virtual scenarios offer many advantages, such as low cost and high safety. Accordingly, the planning and design of effective evacuation paths that sufficiently match real conditions have become an imperative focus of related research. In this paper, we propose a novel framework for path planning in virtual emergency scenarios, which consists of three parts. (a) Configuration of the virtual environment: for convenience in handling, the virtual emergency scenario is discretized into many individual grid cells. (b) Policy generation: a dual deep Q-learning network approach is employed to obtain an effective policy that can allow agents to intelligently find effective paths. (c) Grouping strategy: a strategy is proposed to support multiple agents in achieving collective evacuation based on a given policy. Finally, extensive experiments are presented to validate the superiority of the proposed framework. The results show that by comparison with the existing related state-of-the-art methods, our proposed framework is superior and feasible
Recommended citation: Wen Zhou , C. Zhang, S. Chen, Dual deep Q-learning network guiding a multiagent path planning approach for virtual fire emergency scenarios. Applied Intelligence, 2023,53:21858–21874.
Novel learning framework for optimal multi-object video trajectory tracking
Published in Virtual Reality & Intelligent Hardware, 2023
With the rapid development of Web3D, virtual reality, and digital twins, virtual trajectories and decision data considerably rely on the analysis and understanding of real video data, particularly in emergency evacuation scenarios. Correctly and effectively evacuating crowds in virtual emergency scenarios are becoming increasingly urgent. One good solution is to extract pedestrian trajectories from videos of emergency situations using a multi-target tracking algorithm and use them to define evacuation procedures.
Recommended citation: Siyuan Chen, Xiaowu Hu, Wenying Jiang, Wen Zhou* , Xintao Ding, Novel learning framework for optimal multi-object video trajectory tracking. Virtual Reality & Intelligent Hardware, 2023,5(5):422-438.
An improved social force model-driven multiagent generative adversarial imitation learning framework for pedestrian trajectory prediction
Published in Computer Animation and Virtual Worlds, 2025
An improved social force model-driven multiagent generative adversarial imitation learning framework for pedestrian trajectory prediction.
Recommended citation: Wen Zhou,Wangyu Shen, Xinyi Meng "An improved social force model-driven multiagent generative adversarial imitation learning framework for pedestrian trajectory prediction." Computer Animation and Virtual Worlds. 2025, 36(1): e2035.
A novel Internet of medical things framework for absorbing bioresorbable vascular scaffold towards healthcare monitoring based on improving YOLO paradigms
Published in Knowledges-based Systems, 2025
A novel Internet of medical things framework for absorbing bioresorbable vascular scaffold towards healthcare monitoring based on improving YOLO paradigms.
Recommended citation: Wangyu Shen, Wen Zhou* "A novel Internet of medical things framework for absorbing bioresorbable vascular scaffold towards healthcare monitoring based on improving YOLO paradigms " Knowledges-based Systems. 2025.
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown file that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Introduce to Computer Science
Undergraduate course, School of Computer and Information, Anhui Normal University, Anhui, China, 2020
- Teaching period: 1st term, 2020
- Position: Associated Professor
- Role: Specialty Basic Course
- Number of students: 100
- Abstract of course: Introduction to Computer is the first professional compulsory course for computer and related majors, and the leading course for many follow-up courses. It is built on the basis of the cognitive model of computing discipline, with the cultivation of computing thinking ability as the core, and guides the computing discipline from the perspective of discipline ideas and methods. The course focuses not only on the introduction of computer science, but also on the cultivation of students' basic computer operation ability.
- Course Profile: Goto
Computer Virus and Prevention Technology
Undergraduate course, School of Computer and Information, Anhui Normal University, Anhui, China, 2021
- Teaching period: 2nd term, 2021
- Position: Associated Professor
- Role: Specialty Elective Course
- Number of students: 60
- Abstract of course:Computer Virus and Prevention Technology, several common types, and characteristics of computer viruses, including Windows files viruses, Trojan horses, worms, mobile phone viruses, etc., and virus Encryption and polymorphism technology, etc. were detailed described. Additionally, related prevention technology, such as feature detection methods, heuristic code scanning technology, etc. were widely introduced to help us know how to prevent sorts of complex computer viruses.
- Course Profile: Goto
Visualization of Big Data
Undergraduate course, School of Computer and Information, Anhui Normal University, Anhui, China, 2021
- Teaching period: 2nd term, 2021
- Position: Associated Professor
- Role: Specialty Elective Course
- Number of students: 50
- Abstract of course: Visualization of Big Data is a professional elective course, which requires various tools including JavaScript, Python and other programs to visualize different types of data.
- Course Profile: Goto
Digital Image Processing
Undergraduate course, School of Computer and Information, Anhui Normal University, Anhui, China, 2022
- Teaching period: 2nd term, 2022 / 2nd term, 2023
- Position: Associated Professor
- Role: Specialized Elective Course
- Number of students: 39/ 57
- Abstract of course: Digital Image Processing, also known as computer image processing, refers to the process of converting image signals into digital signals and utilizing computers to process them. Specifically, it consists of the Augmentation of digital images, encoding images, color image processing, digital watermarking, etc.
- Course Profile: Goto
Computer Operation System
Undergraduate course, School of Computer and Information, Anhui Normal University, Anhui, China, 2022
- Teaching period: 2nd term, 2022
- Position: Associated Professor
- Role: Specialized Basic Course
- Number of students: 83
- Abstract of Course: Detailed introduction to Computer Operation system, including process management, CPU management, memory management, I/O device management, file management, disk management, etc.
- Course Profile: Goto
Mathematical Modeling
Undergraduate course, School of Computer and Information, Anhui Normal University, Anhui, China, 2023
- Teaching period: 2nd term, 2022-2023; 2nd term, 2023-2024; 2nd term, 2024-2025
- Position: Associated Professor
- Major: Computer Science; Software
- Role: Specialized Elective Course
- Number of students: 80; 52;67
- Abstract of course: The mathematical modeling competition was first held by the United States in 1985, and then China held its first National Mathematical Modeling Competition in 1992. The competition was directly organized and led by the Higher Education Department of the Ministry of Education and has become the largest, most participated in, and most widely involved technology competition activity in higher education institutions nationwide.
- Course Profile: Goto