Hedieh Sajedi – Machine learning – Best Researcher Award

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Hedieh Sajedi – Machine learning – Best Researcher Award

Dr. Hedieh Sajedi  distinguished academic and researcher in the field Machine learning.  Her research interests encompass a wide range of advanced topics, including deep learning and machine learning, where she delves into the development and refinement of algorithms that enable computers to learn from and make decisions based on data. She is also deeply involved in multimedia processing, exploring techniques to enhance and manipulate various forms of media, such as images, videos, and audio. Additionally, her work in data mining and information retrieval focuses on extracting meaningful patterns and insights from large datasets, improving the efficiency and accuracy of information retrieval systems. Furthermore, she investigates bio-inspired algorithms, drawing inspiration from natural processes to create innovative computational methods that solve complex problems.

🌐 Professional Profile

Educations📚📚📚

She completed her Ph.D. in Artificial Intelligence and Robotics at Sharif University of Technology in May 2010, following her M.Sc. in the same field from the same institution, which she earned in August 2005. Prior to her postgraduate studies, she obtained her B.Sc. in Computer Software Engineering from Amir Kabir University of Technology in September 2002.

Work Experience:

She has delivered several invited talks on various topics, including “Computer vision and machine learning for medical image analysis” at the Children’s International Research Center in Washington DC, USA, in July 2022, and “Age Prediction based on brain MRI images” at Pompeu Fabra University in Barcelona, Spain, in June 2022. Additionally, she discussed a “Blind Spot Warning System based on Vehicle Analysis in Stream Images” at the same university and “Brain Age Estimation based on Brain MRI Images” at Sehir University of Istanbul, Turkey, in March 2018. Earlier, in March 2014, she presented on the “Application of Steganography and Steganalysis Methods in Medical and Healthcare Systems” at the University of Pavia, Italy. Her executive activities include serving as the Scientific Chair of the International Conference on Pattern Recognition and Image Analysis (IPRIA) in 2023, head of the Computer Science Department from 2018 to 2022, and Scientific Chair of the 6th International Conference on Pattern Recognition and Image Analysis at the University of Tehran in 2022. She also held the position of Head of Computer Services and Information Technology in the College of Science from 2018 to 2020 and served as Inspector of the Image Processing and Machine Vision Society in Tehran, Iran, in 2015 and 2017. Her funded projects include research on the “Detection and Classification of Circular Objects on the Basis of Convolutional Neural Network (CNN)” funded by the Iran National Science Foundation (INSF) from 2021 to the present, “Investigating Brain Health from Brain MRI Images Using Machine Learning Methods,” partially funded by the Institute for Research in Fundamental Sciences (IPM) from 2018 to 2019, “Brain Age Estimation with Mathematical Modeling” funded by INSF from 2017 to 2018, and the development of “A High-Security and High-Capacity Steganography System” funded by INSF from 2011 to 2014.

Honors & Awards

She was recognized as a member of the University of Tehran Top Researchers Club in 2022 and received the Erasmus Mobility Award from the European Union in the same year. Additionally, she was honored with the Honors Program Graduate Award from Sharif University of Technology for the period from 2006 to 2010. Since 2009, she has been an active member of the Scientific Society for Image Processing and Machine Vision.

She has been an instructor at the University of Tehran since 2013, teaching courses such as “Machine Learning,” “Artificial Intelligence,” “Data Mining,” and “Digital Image Processing” in the Department of Computer Science. She has also instructed “Advanced Topics in Artificial Intelligence” since 2020 and “Advanced Information Retrieval” from 2017 to 2020. Additionally, she taught “Advances in AI” from 2013 to 2020 and “Machine Learning in Physics” from 2018 to 2019. Her teaching portfolio includes courses for Ph.D. students at the Institute of Biochemistry and Biophysics, such as “Advanced Data Structure” in 2018-2019. At AmirKabir University of Technology, she instructed “Machine Learning” from 2010 to 2011 and “Artificial Intelligence” in 2010-2011. She also co-instructed “Machine Vision” at Pompeu Fabra University in Barcelona, Spain, in May 2022. Her experience in bio-inspired computing includes teaching “Evolutionary Computing” at the University of Tehran from 2013 to 2016.

Furthermore, she has taught “Distributed Systems” at Azad University, Qazvin, from 2011 to 2013, and courses such as “Computer Networks,” “Compiler Design and Principles,” and “Introduction to Programming” at the University of Tehran. She also taught “Operating Systems,” “Introduction to Programming,” and other foundational courses at Tarbiat Moallem University from 2006 to 2008. Her early teaching roles include instructing “Introduction to Programming” at Sharif University of Technology in 2006-2007 and several technical and scientific presentation courses at AmirKabir University of Technology from 2009 to 2011.

📝🔬Publications📝🔬

Wei Zhang – Digital algorithms – Best Researcher Award

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Wei Zhang – Digital algorithms – Best Researcher Award

Dr. Wei Zhang distinguished academic and researcher in the field Digital algorithms. Zhang Wei and Liu Hui have collaborated on several scholarly articles addressing rural economic issues in China. In their 2020 publication in “Jiangsu Agricultural Sciences,” they examined the “Problems and Countermeasures in the Development of Rural Collective Economy,” using Fenyi County, Jiangxi Province as a case study. This article, found in volume 48, issue 21, pages 28-33, discusses specific challenges faced by rural economies and proposes various strategies for improvement.

🌐 Professional Profiles

Educations📚📚📚

From September 2016 to June 2019, he pursued his Bachelor of Marketing at Hefei University of Technology. He continued his studies at Hunan Agricultural University, where he earned a Master of Agricultural and Forestry Economics and Management, completing the program in June 2021. Building on his academic achievements, he began his PhD in Capability Economic Management at the same university in September 2021, with an expected completion date of June 2025.

Research Experience

Zhang Wei and Liu Hui have collaborated on several scholarly articles addressing rural economic issues in China. In their 2020 publication in “Jiangsu Agricultural Sciences,” they examined the “Problems and Countermeasures in the Development of Rural Collective Economy,” using Fenyi County, Jiangxi Province as a case study. This article, found in volume 48, issue 21, pages 28-33, discusses specific challenges faced by rural economies and proposes various strategies for improvement. Following this, in 2022, they published an article in “Price Theory and Practice,” where they analyzed the effectiveness of reforms in the rural collective property rights system from the perspective of farmer participation. This research, featured in the March 2022 issue on pages 169-172 and 205, was underpinned by a survey of 315 farmer households across Hunan and Jiangxi provinces, offering valuable insights into the impact of these reforms on rural communities.

Project experience

He hosted the 2023 Hunan Provincial Postgraduate Research Innovation Project Key Project, CX20230730, which focused on the Research on the Contract and Performance of Farmland Infrastructure Governance under Endowment Heterogeneity. He also played a significant role in contributing to several major research projects. He participated in writing a major project for the Hunan Provincial Social Science Fund, numbered 23ZWA14, which involved researching the Current Situation and Countermeasures of Rural Collective Economic Development in Hunan Province. Additionally, he contributed to the general project of the Hunan Provincial Social Science Fund, 21YBA079, which examined the governance mechanism and performance of high-standard farmland in the context of food and ecological security. His research contributions extended to the Hunan Provincial Natural Science Foundation’s general project, 2023JJ30312, focusing on the mechanism and performance of digital technology in empowering farmland water conservancy facilities. Moreover, he was involved in writing for a project under the Hunan Provincial Development and Reform Commission that researched coordinated food and ecological security in the middle and lower reaches of the Yangtze River plain, considering “resources-factors-policies.”

Personal honor

He achieved notable recognition in various academic competitions and forums. At the 2021 Modern Agricultural Development Forum and the First “World Agriculture” Workshop in the context of “Dual Cycles,” he won the second prize in the paper competition. His research excellence continued into the following year when he won the first prize for outstanding paper at the 2022 Hunan Rural Economics Association Annual Meeting. Additionally, he received the award for the second “Economic Management Quantitative Research Methods” Excellent Paper at the School of Economics, Hunan Agricultural University. He also actively participated in advanced training sessions, including the “Jiangsu Province Applied Economic Research Methodology” workshop organized by the Economics Graduate Education Steering Committee of Jiangsu Province and the School of Economics and Management of Nanjing Agricultural University, where he earned the title of qualified student. Furthermore, he attended the “2021 Summer Econometrics and Scientific Research Methods Lecture Series” at the School of Statistics and Mathematics of Zhongnan University of Economics and Law, also achieving the status of qualified student.

 

📝🔬Publications📝🔬

Jianxiao Wang – Data Science – Best Researcher Award

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 Dr. Jianxiao Wang  distinguished academic and researcher in the Data Science and Smart Grid. He is currently an Assistant Professor at the National Engineering Laboratory For Big Data Analysis and Applications, Peking University, and a Distinguished Researcher at the PKU-Changsha Institute for Computing and Digital Economy. He obtained Bachelor’s degrees in Engineering and Economics from Tsinghua University in 2014, and completed his Ph.D. in Electrical Engineering from Tsinghua University in 2019. From 2016 to 2017, he served as a visiting researcher at Stanford University and the University of California, Berkeley. From 2019 to 2020, he worked as a project leader at the Ministry of Science and Technology of the People’s Republic of China, contributing to the 14th Five-Year Plan for High Tech Development in the field of energy and transportation, and conducting research on the 2035 National Science and Technology Development Strategy in China.

His research interests revolve around data-driven decision making for energy storage and renewable power systems, focusing on evaluating the levelized cost and designing national low-carbon pathways for emerging technologies such as AIGC, roadside photovoltaics, electric and fuel cell vehicles, power-to-hydrogen, green ammonia chemical industry, and carbon capture and storage utilization. As the first or corresponding author, he has published 1 paper in Nature Sustainability, 2 papers in Nature Communications, 1 paper in Cell The Innovation, 1 paper in Cell Patterns, and 2 papers in Cell iScience. Additionally, he has authored 99 papers published in top journals and conferences, including two 0.1% ESI Hot Paper, two 1% ESI Highly Cited Paper, and four IEEE Conference Best Paper Awards. He has applied for 35 China Invention Patents and 2 US Patents. Furthermore, he has published one Springer monograph as the first author, one IEEE Press monograph as a contributing author, and coauthored three Chinese monographs. The research article in Nature Sustainability was selected as a cover paper candidate and received an official report from Johns Hopkins University. As of August 2023, the research article in Nature Communications has been accessed over 10,000 times and cited 147 times, selected as a 0.1% ESI Hot Paper and officially reported by People’s Daily.

🌐 Professional Profiles

Educations📚📚📚

He pursued his academic journey at Tsinghua University, where he completed his Bachelor’s degrees in Electrical Engineering from the Department of Electrical Engineering and Economics from the School of Economics and Management from August 2010 to July 2014. Subsequently, he continued his academic pursuit at Tsinghua University, specializing in Electrical Engineering, where he earned his Ph.D. from the Department of Electrical Engineering from August 2014 to January 2019. During his Ph.D., he achieved a GPA of 92.8, ranking 2nd out of 55 students. His outstanding performance led to his recognition as an Outstanding Doctoral Graduate and his dissertation being acknowledged as one of the top 2% at Tsinghua University. Additionally, he was awarded the Tsinghua University President Jiang Nanxiang Scholarship, a prestigious honor bestowed upon 10 Ph.D. students annually.

As part of his academic journey, he expanded his horizons through visiting researcher positions at renowned institutions. From April 2017 to December 2017, he conducted research as a visiting researcher at the University of California, Berkeley. Prior to this, from November 2016 to December 2017, he engaged in research activities as a visiting researcher at Stanford University. Furthermore, he broadened his research experience with a visiting researcher position at Texas A&M University from July 2013 to September 2013.

Research Experience

He has been serving as an Assistant Professor at the National Engineering Laboratory for Big Data Analysis and Applications at Peking University since June 2022. Concurrently, he holds the position of Distinguished Researcher at the PKU-Changsha Institute for Computing and Digital Economy. Prior to his current roles, from October 2019 to September 2020, he worked as a Project Manager at the Ministry of Science and Technology of the People’s Republic of China. Additionally, he gained valuable experience as a Lecturer at North China Electric Power University from June 2019 to May 2022.

He has received numerous accolades and awards for his outstanding contributions to science, technology, and innovation. In 2023, he was honored with the Second Prize of the Science and Technology Progress Award from the China Electrotechnical Society for his work on “Transmission and Distribution Network Coordinated Control Technology and Applications Under High Distributed Energy Penetration.” Additionally, he received the Second Prize of the Power Innovation Award from the China Electric Power Union for his achievements in “Technology and Application for Data Value-driven Hierarchical Scheduling of Renewable Power Systems.” He was also recognized with the Wu Wen-Jun Artificial Intelligence Outstanding Youth Award by the Chinese Association for Artificial Intelligence for his research on “Physics-informed Data Driven Theory for Smart Grid Operation.” Furthermore, he was selected for the Wiley Open Science Excellent Author Program.

In 2022, he was honored with the Young Scientist Award by the Ministry of Science and Technology of China. He has also been recognized under the Young Elite Scientist Sponsorship Program by the China Association for Science and Technology for his work on “Smart City Energy System Operation Considering Adaptive Consistency Control of Water Electrolysis.” He received a Gold Medal at the Geneva International Exhibition of Inventions for his contribution to “Edge-intelligence Control Technology and System of Solar+Storage Powered Microgrid.” Additionally, his paper titled “Defending Against Adversarial Attacks by Energy Storage Facility” earned the IEEE PES General Meeting Best Paper Award.

He has been recognized for his exceptional service and expertise, receiving the IEEE Transactions on Sustainable Energy Excellent Reviewer Award multiple times. He was also listed in the Forbes China 30 Under 30 Elite List and acknowledged as one of the Outstanding Young Science and Technology Talents by the China Renewable Energy Society. In 2020, he was honored as one of the Beijing Outstanding Young Talents and recognized for his contributions to energy science and technology by the China Energy Research Association. Furthermore, his innovative work on “Renewable Energy-Dominated Virtual Power Plant” secured a place in the top 10 of the Elsevier Renewable Transformation Challenge. He has also been acknowledged with various awards for his inventions and innovations, including the Silver Award at the Beijing Invention and Innovation Competition and the Gold Award at the China Invention Exhibition. Additionally, he has been recognized as a Youth Of China’s High-End Technology Innovation Think Tank for his contributions to the technological development and environmental governance benefits of China’s photovoltaic and energy storage industry.

Monograph

He has authored several publications across various domains, showcasing his expertise and contributions to the field. As the first author, he collaborated with colleagues on the book “Sharing Economy in Energy Markets: Modeling, Analysis and Mechanism Design,” published by Springer in 2022. Additionally, he authored chapters 28-30 in the book “Microgrids: Theory and Practice,” published by IEEE Press in 2023.

Furthermore, he has contributed to monographs in different capacities. In the book “Introduction to the Electricity Spot Market: Trading Strategy and Profit Model for Information Driven Growth,” published by Mechanical Industry Press in 2021, he co-authored chapters 2, 4, and 6. Additionally, he was part of the team contributing to chapter 7 in “2060 China Carbon Neutrality,” published by Chemical Industry Press in 2022. He also co-authored chapters 1 and 2 in “Introduction to New-type Power Systems,” published by the China Association for Science and Technology Carbon Peak and Carbon Neutrality Series in 2022.

Representative Academic Service

He has been recognized for his exemplary contributions and leadership in various professional capacities. In 2023, he served as the Youth Editor for Cell The Innovation, a prestigious role reflecting his expertise in the field, with the journal boasting an Impact Factor of 32.1. He was also appointed as a National Graduate Education Evaluation and Monitoring Expert by the Ministry of Education, showcasing his commitment to education excellence.

In 2022, he was honored as a Distinguished Researcher under the Beijing “Thousands of People Entering Thousands of Enterprises” program, highlighting his significant contributions to research and innovation. He was also recognized as a National Excellent Educator in the National Simulation Innovation Application Competition and appointed as an Instructor by the IEEE Industry Applications Society (IAS) at Peking University. Additionally, he received accolades as an Excellent Editor from the IET Energy Conversion and Economics.

In 2021, he was appointed as an Executive Member of the IEEE Power and Energy Society (PES) China, underscoring his leadership and expertise in the field. He also served as a Youth Working Committee Member of the 9th Council of the Chinese Electrotechnical Society, demonstrating his active involvement in professional organizations.

In 2020, he was recognized as an expert in the 6th National Technology Prediction by the Ministry of Science and Technology of China, further acknowledging his expertise and contributions to technology development. Additionally, he joined the Editorial Board of IET Renewable Power Generation, contributing his insights to the publication.

From 2019 to 2022, he chaired panel sessions at the IEEE PES General Meeting, showcasing his leadership and expertise in the field. Through these diverse roles and responsibilities, he has demonstrated his commitment to advancing research, education, and innovation in his field.

Representative Research Project

He has undertaken numerous significant research projects as the primary investigator, showcasing his leadership and expertise in the field. From November 2022 to October 2025, he leads the National Key R&D Plan project titled “Resilience Enhancement Technology for Large Urban Power Grids Amidst Extreme Events,” with a funding of 4.5 million Chinese yuan. Similarly, from January 2023 to December 2026, he is leading a project funded by the National Natural Science Foundation of China titled “Renewable-dominated Power System Flexible Ramping Operation Considering Consistency Control of Water Electrolysis Multiphysics,” with a grant of 540 thousand Chinese yuan.

In previous years, he has led various other research projects funded by prestigious organizations such as the National Natural Science Foundation of China and the State Grid Corporation of China. These projects cover a wide range of topics including virtual power plant market operation, energy systems integration, self-sustained energy systems for highways, and collaborative regulation technology for large-scale energy storage clusters. Through his involvement in these projects, he has made significant contributions to advancing research and innovation in the energy sector.

📝🔬Publications📝🔬

1 Jianxiao Wang#, Liudong Chen#, Zhenfei Tan, Ershun Du, Nian Liu, Jing Ma, Mingyang Sun, Canbing Li, Jie Song,
Xi Lu*, Chin-Woo Tan*, Guannan He*. Inherent spatiotemporal uncertainty of renewable power in China. Nature
Communications, 2023, 14: 5379.
2 Yang Yu#, Jianxiao Wang#, Qixin Chen, Johannes Urpelainen, Qingguo Ding, Shuo Liu, Bing Zhang*.
Decarbonization efforts hindered by China’s slow progress on electricity market reforms. Nature Sustainability.
2023, 6, 1006-1015.
Special Comments from Johns Hopkins University:

China’s Sluggish Electricity Market Reforms Impede Decarbonization Efforts


Representative Publications
3 Jianxiao Wang#, Haiwang Zhong*, Zhifang Yang, Mu Wang, Daniel M Kammen*, Zhu Liu, Ziming Ma, Qing Xia
and Chongqing Kang. Exploring the trade-offs between electric heating policy and carbon mitigation in China,
Nature Communications, 2020, 11: 6054. (0.1% ESI Hot Paper) https://doi.org/10.1038/s41467-020-19854-y
Special Comments from People’s Daily and Tsinghua University News:
https://www.tsinghua.edu.cn/info/1175/21483.ht

4 Jianxiao Wang#, Feng Gao#, Yangze Zhou, Qinglai Guo, Chin-Woo Tan, Jie Song, Yi Wang*. Data sharing in energy
systems. Advances in Applied Energy, 2023, 10: 100132.
AEii International Applied Energy and EnergyVision Youth Scientists Forum Report:
https://mp.weixin.qq.com/s/9FyaH55gpaKFirXhlrboGg
5 Jianxiao Wang#, Haiwang Zhong*, Zhifang Yang, Xiaowen Lai, Qing Xia, Chongqing Kang. Incentive mechanism
for clearing energy and reserve markets in multi-area power systems. IEEE Transactions on Sustainable Energy, 2020,
11(4): 2470 – 2482.
6 Jianxiao Wang#, Junjie Qin, Haiwang Zhong*, Ram Rajagopal, Qing Xia, Chongqing Kang. Reliability value of
distributed solar+storage systems amidst rare weather events. IEEE Transactions on Smart Grid, 2019, 10(4): 4476 –
4486.
7 Jianxiao Wang#, Haiwang Zhong*, Xiaowen Lai, Qing Xia, Yang Wang, Chongqing Kang. Exploring key weather
factors from analytical modeling toward improved solar power forecasting. IEEE Transactions on Smart Grid, 2019,
10(2): 1417-1427.
8 Jianxiao Wang#, Haiwang Zhong, Qing Xia*, Chongqing Kang. Optimal planning strategy for distributed energy
resources considering structural transmission cost allocation. IEEE Transactions on Smart Grid, 2018, 9(5):
5236-5248.
9 Jianxiao Wang#, Haiwang Zhong, Chin-Woo Tan, Xiao Chen, Ram Rajagopal, Qing Xia*, Chongqing Kang.
Economic benefits of integrating solar-powered heat pumps in a CHP system. IEEE Transactions on Sustainable
Energy, 2018, 9(4): 1702-1712.
10 Jianxiao Wang#, Haiwang Zhong, Ziming Ma, Qing Xia*, Chongqing Kang. Review and prospect of integrated.

Guangli Wu – Video Summarization – Best Researcher Award

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Guangli Wu – Video Summarization

prof Dr. Guangli Wu  distinguished academic and researcher in the field  Video summarization.  The existence of software vulnerabilities will cause serious network attacks and information leakage problems. Timely and accurate detection of vulnerabilities in software has become a research focus on the security field. Most existing work only considers instruction-level features, which to some extent overlooks certain syntax and semantic information in the assembly code segments, affecting the accuracy of the detection model. In this paper, we propose a binary code vulnerability detection model based on multi-level feature fusion. The model considers both word-level features and instruction-level features. In order to solve the problem that traditional text embedding methods cannot handle polysemy, this paper uses the Embeddings from Language Models (ELMo) model to obtain dynamic word vectors containing word semantics and other information. Considering the grammatical structure in the assembly code segment, the model randomly embeds the normalized assembly code segment to represent it. Then the model uses bidirectional Gated Recurrent Unit (GRU) to extract word-level sequence features and instruction-level sequence features respectively.

Eduvation

He pursued his academic journey with a solid foundation in computer science and technology, earning a Bachelor’s degree from Shandong Technology and Business University in 2003. Building upon this, he delved into the realm of Computer Application Technology, completing his Master’s degree at Northwest Minzu University in 2007. Driven by a passion for cultural diversity and linguistic exploration, he further expanded his expertise by attaining a doctoral degree in Chinese Minority Ethnic Languages and Literature from Northwest Minzu University in 2011. This educational trajectory reflects his commitment to a multidisciplinary approach, seamlessly blending computer technology with a profound understanding of language and culture.
Professional Profiles:

RESEARCH INTEREST

⚫ Video Summarization
⚫ Temporal Language Localization in videos
⚫ Botnet Detection
⚫ Binary Code Vulnerability Detection
⚫ Video Abnormal Event Detection
FUND PROJECTS
1. Natural Science Foundation of Gansu Province (17JR5RA161, 21JR7RA570)
2. Gansu University of Political Science and Law Major Scientific Research and Innovation Projects
(GZF2020XZDA03)
3. Young Doctoral Fund Project of Higher Education Institutions in Gansu Province (2022QB-123)
4. Gansu Province Higher Education Innovation Fund Project (2017A-068)
5. University-level Innovative Research Team of Gansu University of Political Science and Law
6. Longyuan Youth Innovation and Entrepreneurship Talent Project (2022QB-123)

MAIN SCIENTIFIC PUBLICATIONS

1. Guangli Wu,ShengTao Wang,Shipeng Xu. “Feature fusion over hyperbolic graph convolution networks for
video summarization.” IET Computer Vision,2023.
2. Guangli Wu,Tongjie Xu. “Video Moment Localization Network Based on Text Multi-semantic Clues
Guidance.” Advances in Electrical and Computer Engineering,2023,23(3):85-92.
3. Guangli Wu,Huili Tang. “Binary Code Vulnerability Detection Based on Multi-Level Feature Fusion.” IEEE
Access,2023,11: 63904-63915.
4. Guangli Wu,Shanshan Song,Leiting Li. “Video Summarization Generation Model Based on Transformer
and Deep Reinforcement Learning.” in 2023 8th International Conference on Computer and
Communication Systems (ICCCS). IEEE, 2023: 916-921.
5. Guangli Wu,Shengtao Wang,Liping Liu. “Fast Video Summary Generation Based On Low Rank Tensor
Decomposition.” IEEE Access,2021,9:127917-127926.
6. Guangli Wu,Zhenzhou Guo,Mianzhao Wang,Leiting Li and Chengxiang Wang. “Video Abnormal Event
Detection Based on CNN and Multiple Instance Learning.” in twelfth international conference on signal
processing systems. SPIE,2021:134-139.
7. Guangli Wu,Zhenzhou Guo,Leiting Li and Chengxiang Wang. “Video Abnormal Event Detection Based on
CNN and LSTM.” in 2020 IEEE 5th International Conference on Signal and Image Processing (ICSIP).
IEEE,2020: 334-338.
8. Guangli WU,Leiting LI,Zhenzhou GUO,Chengxiang WANG and Yanpeng, YAO. “Video summarization
Based on ListNet Scoring Mechanism.” in 2020 5th International Conference on Computer and
Communication Systems (ICCCS). IEEE,2020: 281-285.
9. Guangli WU,Liping LIU,Chen Zhang and Dengtai TAN. “Video Abnormal Event Detection Based on ELM.”
in 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP).IEEE,2019: 367-371