检索结果-内蒙古大学图书馆

2011年全国理论计算机科学学术年会

作者： QU Huaqiao ZHANG Shichao LIU Huawen ZHAO Jianmin Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China Department of Computer Science Zhejiang Normal University Jinhua 321004 Department of Computer Science Zhejiang Normal University Jinhua 321004 China Department of Computer Science Zhejiang Normal University Jinhua 321004 China

lti-label learning aims at predicting a proper label set for each unseen *** instance in the dataset is associated with a set of predefined ***-label learning approaches frequently used choose identical feature set to...

关键词：

来源：评论

学校读者我要写书评

暂无评论

UAV-enabled Collaborative Beamforming via Multi-Agent Deep Reinforcement Learning

arXiv

引用

arXiv 2024年

作者： Liu, Saichao Sun, Geng Li, Jiahui Liang, Shuang Wu, Qingqing Wang, Pengfei Niyato, Dusit The College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun130012 China The College of Computing and Data Science Nanyang Technological University 639798 Singapore The School of Information Science and Technology Northeast Normal University Changchun130117 China The Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China The School of Computer Science and Technology Dalian University of Technology Dalian116024 China

In this paper, we investigate an unmanned aerial vehicle (UAV)-assistant air-to-ground communication system, where multiple UAVs form a UAV-enabled virtual antenna array (UVAA) to communicate with remote base stations by utilizing collaborative beamforming. To improve the work efficiency of the UVAA, we formulate a UAV-enabled collaborative beamforming multi-objective optimization problem (UCBMOP) to simultaneously maximize the transmission rate of the UVAA and minimize the energy consumption of all UAVs by optimizing the positions and excitation current weights of all UAVs. This problem is challenging because these two optimization objectives conflict with each other, and they are non-concave to the optimization variables. Moreover, the system is dynamic, and the cooperation among UAVs is complex, making traditional methods take much time to compute the optimization solution for a single task. In addition, as the task changes, the previously obtained solution will become obsolete and invalid. To handle these issues, we leverage the multi-agent deep reinforcement learning (MADRL) to address the UCBMOP. Specifically, we use the heterogeneous-agent trust region policy optimization (HATRPO) as the basic framework, and then propose an improved HATRPO algorithm, namely HATRPO-UCB, where three techniques are introduced to enhance the performance. Simulation results demonstrate that the proposed algorithm can learn a better strategy compared with other methods. Moreover, extensive experiments also demonstrate the effectiveness of the proposed techniques. Copyright © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Application of Hybrid Monocular SLAM Method in Augmented Reality

引用

Journal of Physics: Conference Series 2021年第4期1748卷

作者： Zuoming Zhang Hanwen Wang Man Shu Xin Wang College of Software Engineering Jilin University Changchun Jilin 130000 China Key Laboratory of Symbolic Computation and Knowledge Engineer of Ministry of Education Jilin University Changchun Jilin 130000 China

In this paper, we design a hybrid (semi-direct) approach to simultaneous localization and mapping (SLAM) for monocular cameras and apply it to augmented reality (AR) for monocular cameras. We combine the advantagesof the direct method and the feature point method. We use both photometric bundle adjustment which is robust to camera exposure time and motion bundle adjustment which is geometrically robust based on feature points to do tracking process. This approach can maintain an intuitive direct local map as well as a reusable global sparse feature point map. Through the processing of point clouds, such as PCA plane detection and grid reconstruction, we greatly improve the effect of the augmented reality system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Msa-Net: A Medical Image Segmentation Network Based on Spatial Pyramid and Attention Mechanism

SSRN

引用

SSRN 2023年

作者： Feng, Yuncong Zhu, Xiaoyan Li, Yang Zhang, Xiaoli Lu, Huimin College of Computer Science and Engineering Changchun University of Technology Jilin Changchun130012 China Artificial Intelligence Research Institute Changchun University of Technology Jilin Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Jilin Changchun130012 China Academy for Advanced Interdisciplinary Studies Northeast Normal University Jilin Changchun130024 China Jilin Provincial Smart Health Joint Innovation Laboratory for the New Generation of AI 3000 North Yuanda Avenue Gaoxin North District Changchun130102 China

Medical image segmentation is an important way to assist doctors to accurately diagnose diseases. However, semantic features are difficult to be fully extracted due to the complexity of medical image lesion tissue features (e.g., size, location, and morphology) and the high similarity between the background and the target region. To tackle these problems, we propose a novel medical image segmentation network MSA-Net based on the spatial pyramid and attention mechanism. This technique facilitates the extraction of multi-scale spatial information and the establishment of channel dependencies within images. By incorporating efficient pyramid attention and channel-spatial dual attention modules, the network autonomously focuses on lesion regions while suppressing background interference. Additionally, the SPCA (Spatial Pyramid-Coordinate Attention) module is integrated at the bottleneck layer, enabling the assimilation of larger receptive field information and prioritizing relevant features. This augmentation improves the network's ability to gather both location and channel-based insights. We proceed to evaluate our model qualitatively and quantitatively across four public datasets: ISIC2018, Lung segmentation, Kvasir-SEG, and ISLES2022. The results substantiate the superior performance of our proposed model. © 2023, The Authors. All rights reserved.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

A Survey on Fairness in Large Language Models

arXiv

引用

arXiv 2023年

作者： Li, Yingji Du, Mengnan Song, Rui Wang, Xin Wang, Ying College of Computer Science and Technology Jilin University Changchun130012 China Department of Data Science New Jersey Institute of Technology Newark United States School of Artificial Intelligence Jilin University Changchun130012 China Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun130012 China

Large Language Models (LLMs) have shown powerful performance and development prospects and are widely deployed in the real world. However, LLMs can capture social biases from unprocessed training data and propagate the biases to downstream tasks. Unfair LLM systems have undesirable social impacts and potential harms. In this paper, we provide a comprehensive review of related research on fairness in LLMs. Considering the influence of parameter magnitude and training paradigm on research strategy, we divide existing fairness research into oriented to medium-sized LLMs under pre-training and fine-tuning paradigms and oriented to large-sized LLMs under prompting paradigms. First, for medium-sized LLMs, we introduce evaluation metrics and debiasing methods from the perspectives of intrinsic bias and extrinsic bias, respectively. Then, for large-sized LLMs, we introduce recent fairness research, including fairness evaluation, reasons for bias, and debiasing methods. Finally, we discuss and provide insight on the challenges and future directions for the development of fairness in LLMs. Copyright © 2023, The Authors. All rights reserved.

关键词： computational linguistics

来源：评论

学校读者我要写书评

暂无评论

Web-based Teamwork: Distributed Software Development Course under Covid-19

Web-based Teamwork: Distributed Software Development Course ...

引用

International Conference on Computer Science & education (ICCSE)

作者： Rui ZHANG Pedro Mestre Carlos Serodio Marília Prada Wenjuan GAO College of Computer Science and Technology Jilin University Key Lab of Symbolic Computation and Knowledge Engineering Chinese Ministry of Education Changchun China Centro Algoritmi University of Minho Guimaraes Portugal CITAB University of Tras-os-Montes and Alto Douro Vila Real Portugal Department of Social and Organizational Psychology Instituto Universitário de Lisboa (ISCTE-IUL) Lisboa Portugal Library of Changchun University Changchun China

ISBN: (数字)9781728172675

ISBN: (纸本)9781728172682

In a increasingly globalized world, it is very important to help students to acquire the hard and soft skills needed to cope with the challenges they will face when working in such environments. However, even though students find this subject interesting and volunteer for it, it is hard, even impossible to teach college students such a distributed fashion of teamwork. In this paper, a case study is provided to illustrate the methodology and experiences of a joint course, distributed software development, of multiple universities from Asia, Europe, North and South Americas. The results show that student can get the spirit, effective communication for such web-based teamwork environment and achieve software project development. The recent developments because of the Covid-19 pandemic are the facts that now students have to cooperate remotely with each other not only across continents but also inside their own city or country. It has increased the awareness of the need for this kind of training and effectively improved the interactions between team elements in different countries and improved the students' feeling of belonging to their team.

关键词： Software Software engineering Games Faces Teamwork Electronic mail Tools

来源：评论

学校读者我要写书评

暂无评论

A new SAT Encoding Scheme for Exactly-one Constraints

引用

Journal of Physics: Conference Series 2019年第1期1288卷

作者： Jiatong Cai Yating Su Xixi Yang Jionghao Min Yong Lai College of Software Jilin University Changchun P.R. China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun P.R. China

Exactly-one constraints have comprehensive applications for the fields of artificial intelligence and operations research. For many encoded SAT problems generated by the existing encoding schemes of exactly-one constraints, the state-of-the-art knowledge compilers cannot complete compilation. In this paper, we propose a new encoding scheme of exactly-one constraints. We introduce two-dimensional auxiliary variables (represented as a matrix) to denote the constraint that exactly one of some variables can be assigned as true. The clauses generated by our scheme is significantly less than those generated by three other existing encoding schemes. The experimental results on the exact cover problems show that the encoded CNF formulas generated by our scheme requires less compilation time, compared with the other three coding schemes.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Nondestructive quantitative analysis of compound paracetamol and diphenhydramine hydrochloride powder using RBF networks

Nondestructive quantitative analysis of compound paracetamol...

引用

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Hong Zheng Li-Ming Wan Jing-Qing Jiang Yan-Chun Liang College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun China College of Computer Science and Engineering Changchun University of Technology Changchun China Institute of General Development and Evaluation of Equipment EAAF of PLA Beijing China College of Mathematics and Computer Science Inner Mongolia University for the Nationalities Tongliao China

A method for simultaneous analysis of the two components of compound paracetamol and diphenhydramine hydrochloride powdered drugs on near-infrared (NIR) spectroscopy is developed by using a radial basis function (RBF) network. Nearest neighbor-clustering algorithm is used as the learning algorithm of RBF network. Comparisons of the results obtained from the RBF models with those from BP models show that it is feasible to use the RBF network in nondestructive quantitative analysis of the components of drugs.

关键词： Powders Radial basis function networks Clustering algorithms educational institutions Computer science Drugs Spectroscopy educational technology knowledge engineering Artificial neural networks

来源：评论

学校读者我要写书评

暂无评论

A Pruning Based Continuous RkNN Query Algorithm for Large k

引用

电子学报(英文版) 2012年第3期21卷

作者： WANG Shengsheng CHAI Sheng LV Qiannan College of Computer Science and Technology Key Laboratory of Symbolic Computing and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

来源：评论

学校读者我要写书评

暂无评论

The Discretization for a Special Class of Ideal Projectors

引用

International Scholarly Research Notices 2012年第1期2012卷

作者： Zhe Li Shugong Zhang Tian Dong Department of Applied Mathematics School of Science Changchun University of Science and Technology Changchun 130022 *** Key Laboratory of Symbolic Computation and Knowledge Engineering (Ministry of Education) School of Mathematics Jilin University Changchun 130012 ***

We focus on a special class of ideal projectors, subspaces, which possesses two classes of D -invariant polynomial subspaces. The first is a classical type, while the second is a new class. With matrix computation, we...

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：