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Articles 3271 - 3300 of 11188
Full-Text Articles in Artificial Intelligence and Robotics
Preserving Linguistic Diversity In The Digital Age: A Scalable Model For Cultural Heritage Continuity, James Hutson, Pace Ellsworth, Matt Ellsworth
Preserving Linguistic Diversity In The Digital Age: A Scalable Model For Cultural Heritage Continuity, James Hutson, Pace Ellsworth, Matt Ellsworth
Faculty Scholarship
In the face of the rapid erosion of both tangible and intangible cultural heritage globally, the urgency for effective, wide-ranging preservation methods has never been greater. Traditional approaches in cultural preservation often focus narrowly on specific niches, overlooking the broader cultural tapestry, particularly the preservation of everyday cultural elements. This article addresses this critical gap by advocating for a comprehensive, scalable model for cultural preservation that leverages machine learning and big data analytics. This model aims to document and archive a diverse range of cultural artifacts, encompassing both extraordinary and mundane aspects of heritage. A central issue highlighted in the …
An Automated Approach For Improving The Inference Latency And Energy Efficiency Of Pretrained Cnns By Removing Irrelevant Pixels With Focused Convolutions, Caleb Tung, Nick Eliopoulos, Purvish Jajal, Gowri Ramshankar, Chen-Yun Yang, Nicholas Synovic, Xuecen Zhang, Vipin Chaudhary, George K. Thiruvathukal, Yung-Hsiang Lu
An Automated Approach For Improving The Inference Latency And Energy Efficiency Of Pretrained Cnns By Removing Irrelevant Pixels With Focused Convolutions, Caleb Tung, Nick Eliopoulos, Purvish Jajal, Gowri Ramshankar, Chen-Yun Yang, Nicholas Synovic, Xuecen Zhang, Vipin Chaudhary, George K. Thiruvathukal, Yung-Hsiang Lu
Computer Science: Faculty Publications and Other Works
Computer vision often uses highly accurate Convolutional Neural Networks (CNNs), but these deep learning models are associated with ever-increasing energy and computation requirements. Producing more energy-efficient CNNs often requires model training which can be cost-prohibitive. We propose a novel, automated method to make a pretrained CNN more energy-efficient without re-training. Given a pretrained CNN, we insert a threshold layer that filters activations from the preceding layers to identify regions of the image that are irrelevant, i.e. can be ignored by the following layers while maintaining accuracy. Our modified focused convolution operation saves inference latency (by up to 25%) and energy …
Data Supporting Research On Personalized Learning Paths, Sean Mochocki, Mark Reith
Data Supporting Research On Personalized Learning Paths, Sean Mochocki, Mark Reith
Faculty Publications
Personalized Learning Paths (PLPs) are a key application of Artificial Intelligence in E-Learning. In contrast to regular Learning Paths, they return a unique sequence of learning materials identified as meeting the individual needs of the students. In the literature, PLPs are often created from knowledge graphs, which assist with ordering topics and their associated learning materials. Knowledge graphs are typically directed and acyclic, to capture prerequisite relationships between topics, though they can also have bidirectional edges when these prerequisite relationships are not necessary. This data package provides a primarily un-directed knowledge graph, with associated repository of open-source learning materials that …
Icolc Statement On Ai In Licensing, International Coalition Of Library Consortia
Icolc Statement On Ai In Licensing, International Coalition Of Library Consortia
Copyright, Fair Use, Scholarly Communication, etc.
The International Coalition of Library Consortia (ICOLC) statement on artifical intelligence in licensing.
Unraveling Biases And Customer Heterogeneity In E-Commerce Recommendation Systems, Sachin Sharma
Unraveling Biases And Customer Heterogeneity In E-Commerce Recommendation Systems, Sachin Sharma
Dissertations
This research explores the biases present in AI algorithms within e-commerce recommendation systems, focusing on how these biases prioritize popular, sponsored, and private-label products over actual customer preferences. We extend the responsible AI discourse by critically examining these biases and their implications for fairness in e-commerce. To strengthen the current understanding of AI fairness in the fields of information systems and computer science, we aim to challenge the assumption that AI fairness is objective and the same for everyone. We examine how individual differences, such as equity sensitivity and exchange ideology, contribute to users' varied perceptions of AI fairness. Through …
Using Chatgpt To Generate Gendered Language, Shweta Soundararajan, Manuela Nayantara Jeyaraj, Sarah Jane Delany
Using Chatgpt To Generate Gendered Language, Shweta Soundararajan, Manuela Nayantara Jeyaraj, Sarah Jane Delany
Conference papers
Gendered language is the use of words that denote an individual's gender. This can be explicit where the gender is evident in the actual word used, e.g. mother, she, man, but it can also be implicit where social roles or behaviours can signal an individual's gender - for example, expectations that women display communal traits (e.g., affectionate, caring, gentle) and men display agentic traits (e.g., assertive, competitive, decisive). The use of gendered language in NLP systems can perpetuate gender stereotypes and bias. This paper proposes an approach to generating gendered language datasets using ChatGPT which will provide data for data-driven …
Challenges On Public Security System In Ai Era—Preface For Special Column “Artificial Intelligence And Public Security”, Juan Cao, Qiang Sheng, Guojie Li
Challenges On Public Security System In Ai Era—Preface For Special Column “Artificial Intelligence And Public Security”, Juan Cao, Qiang Sheng, Guojie Li
Bulletin of Chinese Academy of Sciences (Chinese Version)
The rapid development of artificial intelligence generated content (AIGC) technology has triggered new public security risks, posing a serious threat to national security and social stability. This study exhibits the recent advances of artificial intelligence (AI) content generation and detection techniques, points out the challenges of detection techniques in real-world scenarios, and advocates that it is necessary to develop AIGC detection technology for public security needs and build a whole-process detection technology system from generative models to online platforms, which supports AIGC to be labeled at the generation phase, identifiable during dissemination and source-traceable after the incident occurs.
Research On Artificial Intelligence Crime And China’S Countermeasures, Jianxin Gao, Jinping Sun, Yukun Cai, Chongpeng Wang, Yanyan Yang, Kaiyue Wang
Research On Artificial Intelligence Crime And China’S Countermeasures, Jianxin Gao, Jinping Sun, Yukun Cai, Chongpeng Wang, Yanyan Yang, Kaiyue Wang
Bulletin of Chinese Academy of Sciences (Chinese Version)
The rapid development of artificial intelligence technology has constantly given rise to new scenarios, models, and markets, changing the way information and knowledge are generated. Nevertheless, the security risks exposed by technology, such as algorithm bias, data leakage, false content generation, and improper use, are also prone to trigger various new types of crimes. There are still loopholes in legal regulation and technological prevention under the current situation, which poses severe challenges to crime crackdown. In order to effectively meet the new challenges of China’s artificial intelligence (AI) crime, we should supplement and improve the existing legal norms, improve the …
Intelligent Algorithm Safety: Concepts, Scientific Problems And Prospects, Xueqi Cheng, Wei Chen, Huawei Shen, Shiguang Shan, Xilin Chen, Guojie Li
Intelligent Algorithm Safety: Concepts, Scientific Problems And Prospects, Xueqi Cheng, Wei Chen, Huawei Shen, Shiguang Shan, Xilin Chen, Guojie Li
Bulletin of Chinese Academy of Sciences (Chinese Version)
Intelligent algorithms refer to the methods embodied in the computational processes that realize intelligence. These methods are often characterized by being data-driven, involving uncertain computations, and with unexplainable model inferences. These characteristics simultaneously introduce potential safety risks to the application of intelligent algorithms and AI. This study firstly explores the concepts of intelligent algorithm safety. Specifically, intelligent algorithm safety, based on the degree of human-machine integration, extends from the univariate safety of the algorithm itself to the bivariate applicational safety when the algorithm serves humans, and finally evolves into the multivariate systemic safety arises within complex socio-technical systems of human-machine …
Embodied Artificial Intelligence Security And Governance, Wenyuan Xu, Xiaoyu Ji, Chen Yan, Yushi Cheng
Embodied Artificial Intelligence Security And Governance, Wenyuan Xu, Xiaoyu Ji, Chen Yan, Yushi Cheng
Bulletin of Chinese Academy of Sciences (Chinese Version)
Embodied artificial intelligence (EAI) is progressively integrated into the fabric of our daily lives, enhancing various sectors such as industrial production, healthcare, and national defense. Nevertheless, the diverse range of hardware devices, software algorithms, and data communications that constitute these complex systems may contain vulnerabilities that could be exploited by attackers, posing a serious threat to personal, social, and national security. Thus, this study examines the security implications and proposes a security framework of EAI, from the perspectives of the information domain, physical domain, and social domain, focusing on its ontological security, interaction security, and application security. To mitigate these …
Editorials For Spencial Topic “Scientific Focus: Open Source Innovation And Open Source Paradigm”
Editorials For Spencial Topic “Scientific Focus: Open Source Innovation And Open Source Paradigm”
Bulletin of Chinese Academy of Sciences (Chinese Version)
No abstract provided.
Open Source In China: Opportunities In New Era, Qigang Zhu, Guofeng Zhang, Caihua Zhu, Yi Zhang
Open Source In China: Opportunities In New Era, Qigang Zhu, Guofeng Zhang, Caihua Zhu, Yi Zhang
Bulletin of Chinese Academy of Sciences (Chinese Version)
China has rapidly experienced industrialization and informatization, entering the era of digital economy. The combination of new productive forces represented by artificial intelligence, non-exclusive production factors represented by knowledge, and open source related relationships may form a new model. From the perspective of social practices of open source innovation, open source lacks systematic preparedness at theoretical, institutional, and talent levels. China should seize the historical opportunity to complete theoretical updates and cultural reconstruction those are adapted to it. Open source and openness also have conditions for China to create a global paradigm of cooperation, sharing, and innovation in the digital …
Thoughts On Ai Innovation And Open Source Development: Lessons From Deepseek, Yanjun Wu
Thoughts On Ai Innovation And Open Source Development: Lessons From Deepseek, Yanjun Wu
Bulletin of Chinese Academy of Sciences (Chinese Version)
At a critical moment of intense competition in the artificial intelligence (AI) field, DeepSeek has released foundational large language models (LLM) such as V3/R1, with performance comparable to leading international organizations like OpenAI. This not only demonstrates China’s technological innovation capabilities in AI but also provides a Chinese innovative pathway for global AI development. Firstly, through low-cost training and inference, break the monopolistic barriers of high-end computing power and lower research and development thresholds. Secondly, through full-stack and comprehensive open-source strategies, support customizable and local deployment that benefits various industries. This technological innovation and open-source practice from DeepSeek deserves in-depth …
Suggestions On Building China’S Artificial Intelligence Open Source Innovation Ecosystem, Yuntao Long, Haibo Liu, Zheping Xu, Yungang Bao, Yanjun Wu
Suggestions On Building China’S Artificial Intelligence Open Source Innovation Ecosystem, Yuntao Long, Haibo Liu, Zheping Xu, Yungang Bao, Yanjun Wu
Bulletin of Chinese Academy of Sciences (Chinese Version)
With the release and application of open-source large language models (LLMs) represented by DeepSeek, open-source innovation has played an increasingly important role in the rapid development of global artificial intelligence (AI) technology. Through technological innovation, cost reduction, performance improvement, and application demonstration, DeepSeek has opened up a disruptive innovation path and improved the research and application level of AI in China and its international influence. In order to further promote the construction of China’s AI open source innovation ecosystem and promote the continuous innovation and iteration of AI technology, this study analyzes the outstanding problems in China’s AI innovation ecosystem …
Discussion On Open-Source And Closed-Source Technology Models In Era Of Artificial Intelligence, Xiaolong Zheng, Jiatong Li
Discussion On Open-Source And Closed-Source Technology Models In Era Of Artificial Intelligence, Xiaolong Zheng, Jiatong Li
Bulletin of Chinese Academy of Sciences (Chinese Version)
This article presents the advantages and disadvantages of open-source and closed-source models in technology innovation and ecosystem construction in the era of artificial intelligence. We explore some current cutting-edge controversies between the two technology models, and puts forward some basic ideas for breaking the deadlock, which can provide some significant insights into promoting the healthy development of artificial intelligence technologies.
Exploration And Practice Of New Industry-Academia-Research Collaboration Mechanism Based On Open-Source Model, Yungang Bao
Exploration And Practice Of New Industry-Academia-Research Collaboration Mechanism Based On Open-Source Model, Yungang Bao
Bulletin of Chinese Academy of Sciences (Chinese Version)
DeepSeek has rapidly expanded globally on a large scale through the open-source model, prompting various sectors to reflect on the value and significance of open-source. This study argues that open-source is an effective way to build consensus and organize high-density talent, as it is supported by objective laws. These include sociological principles such as breaking knowledge monopolies and promoting knowledge dissemination, as well as economic principles like “transaction cost” and the “Jevons effect”. Furthermore, this study suggests that open-source is also an effective approach to establish efficient collaborative mechanisms among industry, academia, and research. Two specific cases are introduced—the Open-Source …
Current Status, Trends, And Policy Recommendations For Global Open Source Ecosystem Development, Xue Guo
Current Status, Trends, And Policy Recommendations For Global Open Source Ecosystem Development, Xue Guo
Bulletin of Chinese Academy of Sciences (Chinese Version)
Open source, as an innovative production model characterized by openness and sharing, has become a core driving force for innovation, openness, sharing, and sustainable development in the digital economy. This study explores the significant value of open source from four dimensions: technological innovation, industrial development, economic contribution, and social sustainability. The current global open source ecosystem is showing a positive development trend, with a continuous increase in the number of open source projects and the scale of contributors. In China, open source efforts are gradually gaining momentum in emerging technology fields. Looking ahead, open source projects are expected to follow …
Current Situation, Challenges And Policy Suggestions Of Chinese Enterprises Participation In Open Source Innovation, Kaihua Chen, Xin Wen, Qigang Zhu
Current Situation, Challenges And Policy Suggestions Of Chinese Enterprises Participation In Open Source Innovation, Kaihua Chen, Xin Wen, Qigang Zhu
Bulletin of Chinese Academy of Sciences (Chinese Version)
Open source is emerging as a new paradigm and a crucial driving force for technological innovation and industrial development. It is shaping new impetus for the development of the digital economy, promoting the construction of an innovation ecosystem in the digital era, and it also serves as an effective path for Chinese enterprises to catch up in technology and industry. Through investigations and literature research, this study discovers that Chinese enterprises have achieved remarkable progress in the field of open source, with the scale of participation continuously expanding and the influence steadily increasing. Nevertheless, they still face numerous challenges in …
Computing Power Security Governance From Perspective Of Overall National Security Concept, Hui Li, Na Wang, Long Wang
Computing Power Security Governance From Perspective Of Overall National Security Concept, Hui Li, Na Wang, Long Wang
Bulletin of Chinese Academy of Sciences (Chinese Version)
Currently, with the rapid development of computing technology and the continuous expansion of computing applications, various types of computing security incidents occur frequently. As an emerging security issue, computing security has become a key fact affecting national security. Strengthening the governance of computing power security has become an important part of the modernization of the national security governance system and governance capacity in China. To clarify the theoretical connotation, risk manifestations, and governance strategies of computing power security governance, this study takes the overall national security concept as guidance and the logical guidance of “issue identification-risk deconstruction-governance response” to analyze …
Breaking Through “Data Bottleneck” Of Ai Large Models—Reflections On Building A National Corpus Operation Platform, Xingteng Li, Feng Feng, Liqiang Huang
Breaking Through “Data Bottleneck” Of Ai Large Models—Reflections On Building A National Corpus Operation Platform, Xingteng Li, Feng Feng, Liqiang Huang
Bulletin of Chinese Academy of Sciences (Chinese Version)
At present, the competition within the global artificial intelligence (AI) large model industry is intensifying, and corpus resources emerging as a critical determinant for enhancing the technical performance and practical efficacy of AI systems. Nevertheless, China’s corpus development faces dual challenges in both quantity and quality, struggling to meet the escalating training demands of the rapidly evolving AI large model sector. Internationally, nations are ramping up efforts to develop their corpus infrastructures, particularly prioritizing the creation and deployment of high-quality linguistic datasets. In this context, through comparative analysis of international benchmarks and domestic conditions, this study proposes a strategic framework …
Uav Swarm Obstacle Avoidance Algorithm Based On Visual Field And Velocity Guidance, Xueqi Gui, Chuntao Li
Uav Swarm Obstacle Avoidance Algorithm Based On Visual Field And Velocity Guidance, Xueqi Gui, Chuntao Li
Journal of System Simulation
Abstract: In the future aerial combat of multiple unmanned aerial vehicles (UAVs), the safe flight of UAV swarm in unknown airspace is an important content of swarm research. In view of avoiding obstacles and maintaining behavior in the UAV swarm system, this paper presents a UAV swarm collision avoidance algorithm based on visual field and velocity guidance (VFVG). The swarm adaptive communication topology mechanism is designed based on the visual field method. Combined with the principle of far attraction and near repulsion and the consensus method, the mechanism can accelerate the transmission of obstacle avoidance information among UAV swarms while …
Dynamic Digital Twin Modelling And Semi-Physical Simulation Of Wind Turbine Operation, Yang Hu, Weiran Wang, Fang Fang, Ziqiu Song, Yuhan Xu, Jizhen Liu
Dynamic Digital Twin Modelling And Semi-Physical Simulation Of Wind Turbine Operation, Yang Hu, Weiran Wang, Fang Fang, Ziqiu Song, Yuhan Xu, Jizhen Liu
Journal of System Simulation
Abstract: For the accurate mapping and real-time simulation requirements proposed by digital twin technology, a multi-input multi-output (MIMO) finite difference domain-hybrid semi-mechanical (FDDHSM) digital twin modeling method is proposed, and a semi-physical simulation system of wind turbine digital twin with physical controller is established for the complex nonlinear operation characteristics of large wind turbines. The integrated dynamic MIMO-FDD-HSM model structure is constructed. Finite difference regression vectors are defined to characterize the operating conditions of the wind turbine, and finite difference space tight convex partitioning, parametric model identification, and non-parametric model training are completed under full operating conditions. The wind turbine …
A Distributed Simulation System For Space Operation Missions, Yunzhao Liu, Mingming Wang, Jintao Li, Chuankai Liu, Jianjun Luo
A Distributed Simulation System For Space Operation Missions, Yunzhao Liu, Mingming Wang, Jintao Li, Chuankai Liu, Jianjun Luo
Journal of System Simulation
Abstract: For the ground verification requirements of complex space operation missions such as noncooperative target capture, on-orbit maintenance, and in-space assembly, a distributed simulation system is developed, which mainly consists of a back-end simulation model, a front-end visual demonstration system, and a front-end main controller. In order to realize the multidisciplinary model coupling and interaction among different modeling tools or programming languages, the functional mock-up interface (FMI) standard is introduced for system integration, improving the modularity, generality, and portability of the system. To fully utilize computing resources and improve the simulation efficiency, simulation subsystems and modules are deployed in a …
Modeling And Optimization Of Smart Warehouse Order Sorting Considering Splitting Strategy, Yuze Xu, Linxuan Zhang, Hui Li, Ming Ge, Wanyi He
Modeling And Optimization Of Smart Warehouse Order Sorting Considering Splitting Strategy, Yuze Xu, Linxuan Zhang, Hui Li, Ming Ge, Wanyi He
Journal of System Simulation
Abstract: For an automatic vehicle sorting problem involving mixed sorting of two types of orders, an order splitting strategy and a method for batch adjustment of sub-orders after splitting are proposed by considering the phenomena of blockage of automatic guided vehicles (AGVs) and idleness of manual collection stations in the order sorting process. In addition, with the optimization objective of minimizing the total order completion time, an order sorting integer planning model with order splitting is established. An improved discrete grey wolf optimization algorithm is proposed to jointly optimize the three sub-problems of order batching, batch sorting, and product unloading …
Construction Of Machine Learning Data Set For Analyzing The Replay Of The Wargaming, Dayong Zhang, Jingyu Yang, Jun Ma, Chenye Song
Construction Of Machine Learning Data Set For Analyzing The Replay Of The Wargaming, Dayong Zhang, Jingyu Yang, Jun Ma, Chenye Song
Journal of System Simulation
Abstract: The first problem to be solved in the application of machine learning to the analysis of the replay of the wargaming is the construction of data sets. Due to the standardization requirements of machine learning for data structure, as well as the limitations of computing power and storage, building a machine learning data set through the wargaming data still faces many problems in terms of how to describe the wargaming situation, how to describe the wargaming process, how to handle high dimensional data, and how to prevent data distortion. To solve these problems, this paper constructs a mapping model …
Gesture Recognition For Dynamic Vision Sensor Based On Multi-Dimensional Projection Spatiotemporal Event Frame, Lai Kang, Yakun Zhang
Gesture Recognition For Dynamic Vision Sensor Based On Multi-Dimensional Projection Spatiotemporal Event Frame, Lai Kang, Yakun Zhang
Journal of System Simulation
Abstract: Vision-based gesture recognition is a commonly used means of human-computer interaction in the fields of virtual reality and game simulation. In practical applications, rapid changes in gesture movements will lead to blurred imaging with traditional RGB cameras or depth cameras, which brings great challenges to gesture recognition. To solve the above problems, a dynamic visual data gesture recognition method based on a multi-dimensional projection spatiotemporal event frame (STEF) is proposed by a using dynamic vision sensor to capture high-speed gesture movement information. The spatiotemporal information is embedded in the data projection surface and fused to form a multidimensional projection …
Multi-Agent Path Planning With Obstacle Penalty Factor, Xingyu Yan, Dayan Li, Niya Wang, Kaixiang Zhang, Jianlin Mao
Multi-Agent Path Planning With Obstacle Penalty Factor, Xingyu Yan, Dayan Li, Niya Wang, Kaixiang Zhang, Jianlin Mao
Journal of System Simulation
Abstract: In light load environments, complex obstacle areas will exacerbate local conflicts between agents, leading to a decrease in path solving efficiency. This paper proposes a multi-agent path planning (MAPF) method with obstacle penalty factors in light load environments. First, in the low-level single machine planning process based on the conflict-based search (CBS) algorithm framework, by judging the distribution type of surrounding obstacles that are about to expand the agent's position, corresponding obstacle penalty factors are assigned to them; then, the penalty factors in the path planning process are accumulated and used as the heuristic value of single machine planning …
Research On Optimization Design Method Of Waverider Forebody/Bump Profile Of Aircraft, Jialin Qiu, Jun Huang, Peng Shu, Qingfeng Wang, Zhiqin Liu, Wenyou Qiao
Research On Optimization Design Method Of Waverider Forebody/Bump Profile Of Aircraft, Jialin Qiu, Jun Huang, Peng Shu, Qingfeng Wang, Zhiqin Liu, Wenyou Qiao
Journal of System Simulation
Abstract: The waverider forebody and Bump profile of aircraft are two classic cases reflecting the waverider idea in aircraft component design. They can effectively improve the overall aerodynamic performance of aircraft and have become the core technology of aircraft overall design. In order to seek the optimal design of the waverider forebody and Bump profile to improve the efficiency of aircraft design, an optimization design method for the waverider forebody and Bump profile is proposed in this paper. The initial waverider forebody and Bump profile are generated by the osculating cone theory and conical flow field, and the aerodynamic performance …
Research On Hybrid Solution Algorithm For Layout Problem Of Rectangular Parts With Multiple Constraints, Ye Liu, Weixi Ji, Xuan Su, Hongxuan Zhao
Research On Hybrid Solution Algorithm For Layout Problem Of Rectangular Parts With Multiple Constraints, Ye Liu, Weixi Ji, Xuan Su, Hongxuan Zhao
Journal of System Simulation
Abstract: A hybrid algorithm based on a cutting and matching algorithm and an improved ant colony algorithm was proposed to solve the layout problem of rectangular parts in the process of wood and glass blanking. A layout optimization model was established to maximize the mean square utilization and the remaining processing time; the ant colony algorithm was used as the layout sequence algorithm to determine the layout sequence of some parts and meet the processing time constraint. In order to improve the search efficiency of the ant colony algorithm, an adaptive pheromone updating strategy was proposed, and a hybrid mutation …
Human Action Recognition Based On Skeleton Edge Information Under Projection Subspace, Benyue Su, Peng Zhang, Bangguo Zhu, Mengjuan Guo, Min Sheng
Human Action Recognition Based On Skeleton Edge Information Under Projection Subspace, Benyue Su, Peng Zhang, Bangguo Zhu, Mengjuan Guo, Min Sheng
Journal of System Simulation
Abstract: In recent years, human action recognition based on skeleton data has received a lot of attention in the fields of computer vision and human-computer interaction. Most of the existing methods focus on modeling the skeleton points in the original 3D coordinate space. However, skeleton points ignore the physical chain structure of the human body itself, which makes it difficult to portray the local correlation of human motion. In addition, due to the diversity of camera views, it is difficult to explore the comprehensive representation of actions in different views under the original point-based 3D space. In view of this, …