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A Survey of 3D Gaussian Splatting: Optimization Techniques, Applications, and AI-Driven Advancements 3

A Survey of 3D Gaussian Splatting: Optimization Techniques, ...

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3rd international conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Santosh Reddy, P. Abhiram, H. Archish, K.S. B.N.M. Institute of Technology Department of Computer Science Engineering Bengaluru India

ISBN: (纸本)9798331515911

3D Gaussian Splatting (3DGS) has emerged as a transformative technique for real-time, high-quality 3D rendering. This paper surveys the advancements in 3DGS, focusing on optimization strategies, applications across diverse domains, and AI-driven innovations that enhance its utility. Optimization techniques, such as Mini-Splatting and sparsification frameworks, address challenges like computational overhead and memory inefficiency while maintaining visual fidelity. AI has further expanded the capabilities of 3DGS through frameworks like SceneTeller, ART3D and GaussianEditor, enabling text-to-3D generation, object-level manipulation, and artistic scene creation with multi-view consistency. Applications of 3DGS range from autonomous driving and robotics to virtual and augmented reality, highlighting its adaptability and efficiency. This survey underscores the importance of continued research to refine 3DGS's scalability and applicability, solidifying its role at the intersection of computer graphics and artificial intelligence. © 2025 IEEE.

关键词： Augmented reality

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Short-term power load forecasting based on multi-step probability distribution deep learning network 6

Short-term power load forecasting based on multi-step probab...

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6th international conference on computer Information science and Application Technology, CISAT 2023

作者： Chen, Ming Gao, Huaijin Chen, Kun Du, Chong Yang, Zhijie Computer Technology and Software Engineering Wuhan Polytechnic Wuhan430074 China Biomedical Engineering and Instrument Science Zhejiang University Hangzhou310027 China Electric Power Research Institute State Grid Hubei Electric Power Co. Ltd Wuhan430077 China Huanggang Power Supply Company State Grid Hubei Electric Power Co. Ltd Huanggang438021 China Wuhan Marine College Wuhan430062 China

ISBN: (纸本)9781510668546

With the improvement of renewable energy utilization rate, its proportion in power generation continues to increase. However, the uncertainty of renewable energy power generation has always been an urgent problem. Accurate forecast of short-term power load can assist modern power systems in accurately allocating the proportion of traditional and renewable energy generation. This is crucial for the safety and economic operation of the power grid. Power load forecasting can be seen as a multivariate time series forecasting problem. Most of existing studies have focused on predicting the next moment power load. However, a great number of decisions in power planning scenarios require predictive models that can provide a complete conditional distribution with richer information, namely probability distribution prediction. To address this limitation, we applied a multi-step probability prediction model based on recurrent neural networks on short-term power load forecasting. Experiments conducted on the annual power load of multiple regions in the United States and comparison with some classic models verify the superiority of the applied model. The results indicate that the model applied in the article has a promising predictive performance. © 2023 SPIE.

关键词： Forecasting

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AI-Powered Classification of Artistic Attributes 2

AI-Powered Classification of Artistic Attributes

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2nd IEEE international conference on Electrical, Automation and computer engineering, ICEACE 2024

作者： Wenhui, Li Guiping, Lu Qichen, Zhang Yuhuan, Wen Kejun, Wang Weidong, Hu Beijing Institute of Technology Zhuhai Faculty of Information Zhuhai China Beijing Institute of Technology Zhuhai Terahertz Science and Applications Center Zhuhai China Beijing Institute of Technology Zhuhai Aviation Academy Zhuhai China Beijing Institute of Technology Zhuhai Faculty of Mathematics Physics and Civil Engineering Zhuhai China

ISBN: (纸本)9798350368208

In view of the current situation in image classification research where algorithms for classification based on the art-style attributes of images are still relatively rare, an automatic image classification system based on art attributes has been implemented. This system mainly involves several typical art-style images such as photographic works, traditional Chinese paintings, watercolor paintings, sketches, and oil paintings. The system uses the Support Vector Machine (SVM) as a classifier and adopts a hierarchical classification method. A specific SVM binary-tree multi-class classification algorithm for the classification of art-attribute images is proposed. Then, through the analysis of the art-style characteristics of various types of images, representative, well-discriminative, and easy-to-calculate features are respectively extracted. Finally, experimental analyses are carried out for the characteristics of each level of classification and the overall characteristics of the classifier. The experimental results show that the system has good classification performance. © 2024 IEEE.

关键词： Trees (mathematics)

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Relationship of IQ with Causal Connections Between Brain Salient Network Regions 31

Relationship of IQ with Causal Connections Between Brain Sal...

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31st National and 9th international Iranian conference on Biomedical engineering, ICBME 2024

作者： Ghoorchian, Mina Soltanian-Zadeh, Hamid Pedram, Mir Mohsen Sadeghi, Mohsen Mir Mohammad Institute for Cognitive Science Studies Department of Cognitive Science Tehran Iran University of Tehran School of Electrical and Computer Engineering Tehran Iran Kharazmi University Department of Electrical and Computer Engineering Faculty of Engineering Tehran Iran

ISBN: (纸本)9798331529710

IQ is one of the indicators that has always been of interest to psychiatrists, doctors and cognitive science researchers. Since this index plays a key role in people's lives and also in the occurrence of brain abnormalities, many studies have been conducted on it. In this paper, we used the resting state magnetic resonance imaging data available in the HCP database to classify people into three groups with low, medium, and high IQ and applied machine learning methods on the matrix of causal connections between related network regions. We applied brain highlights. We calculated the matrix of causal relationships in this network by the spDCM algorithm and then obtained the differences of the three groups using the ANOVA statistical test and 6 edges out of 169 edges with p-value © 2024 IEEE.

关键词： Support vector regression

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Applying Conflict-Based Search to Improve Pathfinding Efficiency in multi-Agent Big Data Adventure Games 2

Applying Conflict-Based Search to Improve Pathfinding Effici...

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2nd IEEE international conference on Electrical engineering, computer and Information Technology, ICEECIT 2024

作者： Setyawan, Anindito Hidayat, Wahyu Nur Widyaningtyas, Triyanna Fahlevi, Achmad Reza Andreanto, Dodik Dwi Siswanto, Figo Kurniawan Department of Electrical Engineering and Informatics Universitas Negeri Malang Malang Indonesia

ISBN: (纸本)9798331504373

The implementation of intelligent pathfinding algorithms is essential for improving gameplay experience and educational value in educational games. This study looks into applying conflict-based search for multi-agent pathfinding in an educational game called "Data Quest: Big Data Adventure," intended for active learning in teaching big data concepts. Conflict-based Search (CBS) optimizes pathfinding and conflict resolution through multi-agent coordination, thereby improving real-time responsiveness and educational engagement. CBS enhances real-time response and education. The results show that compared with conventional approaches such as cooperative A*, CBS reduces the computation time of pathfinding by 30-50% in medium to high-density environments and achieves a conflict resolution efficiency of 75% to 85% in the first iteration. The generated paths by CBS are nearly optimal, differing by only 5-10% from ideal paths, which is adequate in educational scenarios. The successful application of CBS not only enhances the performance of multi-agent interactions but also underscores the importance of integrating advanced AI techniques in educational gaming, paving the way for more immersive and effective learning experiences. These results show how well CBS can enable dynamic and complex interaction within an educational game, highlighting its potential for broader educational applications that benefit from advanced AI-driven, multi-agent systems. © 2024 IEEE.

关键词： Big Data Conflict-Based Search Educational Games Game AI Gamification multi-Agent Pathfinding

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An Optimized Equivariant Quantum Network for Ingenious Building Monitoring and Control using an Android Application 4

An Optimized Equivariant Quantum Network for Ingenious Build...

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4th international conference on Sustainable Expert Systems, ICSES 2024

作者： Prasad, S. Tulasi Sarishma Rekha, G. Sunitha Vekariya, Daxa Patil, Harshal Maranan, Ramya Potti Sriramulu Chalavadi Mallikarjuna Rao College of Engineering & Technology Department of Computer Science & Engineering Andhra Pradesh Vijayawada520001 India Graphic Era Deemed to be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Telangana Hyderabad501510 India Parul institute of Engineering and Technology Parul University Department of Computer Science & Engineering Post Limda Gujarat 391760 India School of Computer Science & Engineering Iilm University Uttar Pradesh Greater Noida201 306 India Saveetha School of Engineering Simats Department of Research and Innovation Tamil Nadu Chennai602105 India

ISBN: (纸本)9798331540364

For enhancing the security and functionality of smart environments, motion recognition, classification and intruder detection has to be added into the building monitoring and control system. This research developed a Self-Guided Efficient Net UNet based Equivariant Quantum Network with Alpine Skiing Optimization (SGENUN-EQN-ASO) for improving intruder detection in buildings by utilizing an Android application for real-time motion detection and categorization. To prepare the data for analysis, processing can be done on the Self-Guided Filtering (SGF). An enhanced approach is Essential Objectness, Cascade Networks, Equivariant Quantum Convolutional Neural Networks (EquivQCNN) to enhance the detection precision and EfficientNet-based EE-UNet for precise motion assessment. Thus, the Android application works as monitoring and control interface providing real-time notifications and the answers to detected intrusions. With the use of optimisation techniques like Alpine Skiing Optimisation (ASO), which is used to fine-tune the hyperparameters of Equivariant Quantum Neural Networks (EQNNs), the system is able to provide stable and flexible performance. The results demonstrating that the integration of the latest machine learning approaches into the solutions in smart buildings brings significant enhancement to the detection effectiveness and response times, as to the overall security and management. © 2024 IEEE.

关键词： Intrusion detection

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Study of spatial invariance methods for multi-target individual recognition 3

Study of spatial invariance methods for multi-target individ...

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3rd international conference on Intelligent Computing and Human-computer Interaction, ICHCI 2022

作者： Bao, Jingwen Li, Meian Gao, Tian Inner Mongolia Agricultural University Computer and Information Engineering College Hohhot010000 China

ISBN: (纸本)9781510661301

Livestock modernization is the front-runner and wind vane of agricultural modernization. Smart animal husbandry for living individuals such as sheep has been widely researched and practiced as a typical application solution of smart agriculture. How to accurately identify different individuals in the same kind of target in the shortest possible time is one of the key problems facing the field of visual recognition and matching at present. In this study, a spatial invariance method is proposed to match multi-target individuals. In the paper, the set of line segments is taken as the unique feature of the target, and a threshold is proposed as the criterion to judge the difference between targets. Experiments show that the accuracy of line segment measurement can reach 99.00% on average;the recognition accuracy reaches 100% when the difference between target individuals is large. The method in this paper has some research significance for the identification of clustered cattle and sheep individuals in smart farming and animal husbandry. © 2023 SPIE.

关键词： Agriculture

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Uncertainty-Aware Global-View Reconstruction for multi-View multi-Label Feature Selection 39

Uncertainty-Aware Global-View Reconstruction for Multi-View ...

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39th Annual AAAI conference on Artificial Intelligence, AAAI 2025

作者： Hao, Pingting Liu, Kunpeng Gao, Wanfu College of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University China Department of Computer Science Portland State University PortlandOR97201 United States

ISBN: (纸本)157735897X

In recent years, multi-view multi-label learning (MVML) has gained popularity due to its close resemblance to real-world scenarios. However, the challenge of selecting informative features to ensure both performance and efficiency remains a significant question in MVML. Existing methods often extract information separately from the consistency part and the complementary part, which may result in noise due to unclear segmentation. In this paper, we propose a unified model constructed from the perspective of global-view reconstruction. Additionally, while feature selection methods can discern the importance of features, they typically overlook the uncertainty of samples, which is prevalent in realistic scenarios. To address this, we incorporate the perception of sample uncertainty during the reconstruction process to enhance trustworthiness. Thus, the global-view is reconstructed through the graph structure between samples, sample confidence, and the view relationship. The accurate mapping is established between the reconstructed view and the label matrix. Experimental results demonstrate the superior performance of our method on multi-view datasets. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Feature extraction

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AN ANALYSIS OF INTERACTION BEHAVIORS IN PERSONALIZED LEARNING 18

AN ANALYSIS OF INTERACTION BEHAVIORS IN PERSONALIZED LEARNIN...

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18th international conference on Interfaces and Human computer Interaction 2024, IHCI 2024, the 17th international conference on Game and Entertainment Technologies 2024, GET 2024 and the 18th international conference on computer Graphics, Visualization, computer Vision and Image Processing 2024, CGVCVIP 2024, Part of the 18th multi conference on computer science and Information Systems 2024, MCCSIS 2024

作者： Cabı, Emine Türkoğlu, Hacer Baskent University Faculty of Education Department of Computer and Instructional Technology Education Ankara Turkey

ISBN: (纸本)9789898704580

The purpose of this study is to examine the relationship between students' participation behaviors in online learning analytics (LA) and their academic performance and self-regulated learning (SRL) in learning analytics-based feedback systems. In the study, 73 university students participated. Moodle was used as a learning management system (LMS) to share digital content, communicate with students, and make evaluations. In the flipped learning (FL) environment, LA including different types of activities was made available to students for four weeks. During this process, students were supported with feedback within the framework of instructional design based on learning analytics. Interaction data, achievement test, and SRL Scale were used as data collection tools. The data obtained in the study were examined using K-Means Clustering Analysis and Mann-Whitney U-test. Cluster analysis was performed to classify students with similar behavioral patterns into a homogeneous group. As a result of the analysis, two clusters were obtained: those with high engagement and those with low engagement. Students' interaction behaviors were determined and the relationship between different interaction behaviors and students' academic success and self-regulation skills was examined. As a result, students with high interaction/engagement spend more time in activities than students with low engagement. Additionally, the academic success and self-regulation score averages (except for help-seeking) of students with high engagement were found to be higher than those with low engagement. When academic achievement and self-regulation skills were compared according to clusters, no statistically significant difference was observed. © 2024 Interfaces and Human computer Interaction. All Rights Reserved.

关键词： Federated learning

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H∞ Synchronization and Sensitivity Analysis of High-Order Complex Dynamical Networks 4

H∞ Synchronization and Sensitivity Analysis of High-Order C...

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4th international conference on Electronic Information engineering and computer Communication, EIECC 2024

作者： Ni, Anling Hu, Jia Tu, Lilan Wuhan University of Science and Technology Hubei Province Key Laboratory of Systems Science in Metallurgical Process Wuhan China Wuhan University of Science and Technology College of Science Wuhan China

ISBN: (纸本)9798331534622

In complex dynamical networks, interactions among nodes not only represent binary relationships but also multivariate relationships. This paper investigates H∞ synchronization of high-order complex dynamical networks with second-order interactions, which are characterized by 2-simplex. Based on Lyapunov stability theory, linear matrix inequality (LMI), and H∞ control theory, this paper proposes sufficient conditions to achieve asymptotic H∞ synchronization by adding controllers to high-order complex dynamical networks. Numerical simulations validate the feasibility and effectiveness of the proposed theoretical results. © 2024 IEEE.

关键词： Synchronization

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