检索结果-内蒙古大学图书馆

14th International Conference on Interactive Theorem Proving, ITP 2023

作者： Joram, Philipp Veltri, Niccolò Department of Software Science Tallinn University of Technology Estonia

ISBN: (纸本)9783959772846

Finitely-branching and unlabelled dynamical systems are typically modelled as coalgebras for the finite powerset functor. If states are reachable in multiple ways, coalgebras for the finite bag functor provide a more faithful representation. The final coalgebra of this functor is employed as a denotational domain for the evaluation of such systems. Elements of the final coalgebra are non-wellfounded trees with finite unordered branching, representing the evolution of systems starting from a given initial state. This paper is dedicated to the construction of the final coalgebra of the finite bag functor in homotopy type theory (HoTT). We first compare various equivalent definitions of finite bags employing higher inductive types, both as sets and as groupoids (in the sense of HoTT). We then analyze a few well-known, classical set-theoretic constructions of final coalgebras in our constructive setting. We show that, in the case of set-based definitions of finite bags, some constructions are intrinsically classical, in the sense that they are equivalent to some weak form of excluded middle. Nevertheless, a type satisfying the universal property of the final coalgebra can be constructed in HoTT employing the groupoid-based definition of finite bags. We conclude by discussing generalizations of our constructions to the wider class of analytic functors. © Philipp Joram and Niccolò Veltri;licensed under Creative Commons License CC-BY 4.0 14th International Conference on Interactive Theorem Proving (ITP 2023)

关键词： Dynamical systems

来源：评论

学校读者我要写书评

暂无评论

Inference Retrieval-Augmented Multi-Modal Chain-of-Thoughts Reasoning for Language Models

Inference Retrieval-Augmented Multi-Modal Chain-of-Thoughts ...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： He, Qiangqiang Qian, Shuwei Zhang, Jie Wang, Chongjun State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

ISBN: (纸本)9798350368741

Recent advancements in Large Language Models (LLMs) have catalyzed the exploration of Chain of Thought (CoT) approaches, particularly in extending their application to multimodal tasks to enhance reasoning capabilities. However, current studies often fail to fully leverage the inferential capabilities of these models, as they primarily focus on selecting similar questions or images rather than exploring identical inferences, thereby limiting the potential for analogical learning. In this paper, we propose an inference retrieval-augmented method that incorporates two strategies to identify training set examples with inferential processes similar to those of the target problem. Initially, we fine-tune a vanilla model to generate the pseudo-inference relevant to the question, which is then utilized to retrieve analogous examples. Next, we hypothesize that questions sharing similar contexts may share inferences, thus retrieving examples based on similarity in contextual questions. Ultimately, we construct multiple reasoning pathways from the retrieved examples and employ a voting mechanism to determine the most frequent answer. Our method surpasses all few-shot approaches and most supervised methods on the scienceQA dataset, achieving an accuracy of 87.37% with ChatGPT and exceeding the human benchmark in several categories. © 2025 IEEE.

关键词： Chain of Thought Large Language Model Multimodal Reasoning

来源：评论

学校读者我要写书评

暂无评论

VR-Recon: Visual Refiner for Fine-Grained Human Reconstruction 4

VR-Recon: Visual Refiner for Fine-Grained Human Reconstructi...

引用

4th IEEE International Conference on Digital Twins and parallel Intelligence, DTPI 2024

作者： Xie, Hong Zhu, Zibin Zhang, Xiaoyan Shen Zhen University College of Computer Science & Software Engineering Shenzhen China

ISBN: (纸本)9798350349252

To reconstruct 3D human figures with fine-grained details from sparse views, this paper proposes a novel framework called VR-Recon, which is based on a viewpoint refiner. In this framework, we first decouple geometric features from multi-scale feature learning by integrating an MSG image encoder, aiming to extract high-quality multi-scale geometric features. Next, we employ a viewpoint refiner to accurately capture critical fine-grained geometric information in each independent view space, thereby avoiding the weighted average fusion of features and eliminating the influence of invalid information. This method is trained using a consistent cosine loss and a cascaded view-space geometric loss. The former encourages the MSG to accurately perceive fine geometric changes from the image, while the latter helps the viewpoint refiner discern critical information in different view spaces. Experimental results demonstrate that, compared to state-of-the-art methods, VR-Recon exhibits robust performance in capturing fine geometric details. © 2024 IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Injecting Global Context for Multivariate Time Series Forecasting on Variable Subsets

Injecting Global Context for Multivariate Time Series Foreca...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Li, Xin-Yi Yang, Yu-Bin State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

ISBN: (纸本)9798350368741

Variable Subset Forecasting (VSF) presents a critical challenge where variable availability fluctuates between the training and inference stages. This paper introduces a novel solution to the underexplored VSF problem, seamlessly integrating with existing variate-wise attention architectures. Our approach features two key innovations: (1) a global context-enriched attention mechanism maintaining a holistic data perspective with incomplete variable sets, and (2) a random group mechanism simulating missing data scenarios during training. These innovations effectively address the challenges of maintaining variable correlations under variable stochastic absence and adapting to dynamic input variate without retraining. Experiments demonstrate that our approach improves predictive performance by an average of 16%, with gains of up to 40% in particularly challenging scenarios involving significant variable absence, while adding only a 1% computational overhead. This substantial performance boost, coupled with adaptability to various architectures, positions our approach as a robust solution for real-world MTSF applications facing variable unavailability and domain shifts. © 2025 IEEE.

关键词： Multivariate time series forecasting Variable subset Variate-wise attention

来源：评论

学校读者我要写书评

暂无评论

Improving Pedestrian Attribute Recognition with Dense Feature Pyramid and Mixed Pooling 13th

Improving Pedestrian Attribute Recognition with Dense Featur...

引用

13th EAI International Conference on Mobile Networks and Management, MONAMI 2023

作者： Xiao, He Zou, Chen Chen, Yaosheng Gong, Sujia Dong, Siwen School of Software Engineering Jiangxi University of Science and Technology Jiangxi Nanchang330013 China Nanchang Key Laboratory of Virtual Digital Factory and Cultural Communications Nanchang330013 China

ISBN: (纸本)9783031554704

In the field of computer vision, pedestrian attribute recognition plays a crucial role in pedestrian detection and pedestrian re-identification. However, this task faces challenges such as blurry images, difficulty in recognizing fine-grained features, and overlooking relationships between pedestrian attributes. To address these challenges, we propose a novel method for pedestrian attribute recognition. Our method is based on convolutional neural networks and incorporates a feature pyramid structure that is specifically designed for the task of pedestrian attribute recognition (PAR). Additionally, we enhance feature information by employing multi-scale feature fusion. Furthermore, our proposed AIIM module facilitates interactions between different attributes by establishing both remote dependencies and short-range dependencies. Through comprehensive experimentation, we have validated the effectiveness of our method and achieved state-of-the-art results. Specifically, our method has achieved impressive average accuracies (mA) of 86.27%, 83.45%, and 81.56% on well-known datasets such as PETA, RAP, and PA100k, respectively. © ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

LightDeblur: A Lightweight Image Deblurring Network via CNN-Transformer Hybrid Architecture

LightDeblur: A Lightweight Image Deblurring Network via CNN-...

引用

2024 International Symposium on Digital Home, ISDH 2024

作者： Li, Haoran He, Qian Guo, Biao School of Computer Science and Information Insecurity Guilin University of Electronic Technology Guilin China Guilin University of Electronic Technology Guangxi Key Laboratory of Trusted Software Guilin China

ISBN: (纸本)9798331509873

Single image deblurring aims to restore a sharp image by removing blurred areas in the single image. Although existing deblurring methods achieve significant progress, these approaches tend to require lots of network parameters and huge computational costs, which limits their practical applications. This work proposes a lightweight image deblurring net-work that integrates Convolutional Neural Networks (CNNs) and Transformers, which is based on an encoder-decoder architecture. Specifically, we propose the inverted residual fast fourier transformation (IRFFT) to reduce model complex-ity. Furthermore, we developed a sparse global self-attention (SGSA) that leverages the most useful global features for image reconstruction while reducing computational complexity. Finally, we also proposed a lightweight feed-forward network (LFFN) to generate better features for image deblurring. Experimental results on benchmark tests indicate that our method achieves competitive performance while maintaining a lightweight structure. Additionally, it demonstrates superior generalization and robustness, producing deblurred images that are visually more realistic. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Sybil attack simulation on Enhanced IdAPoS protocol with different network topology 12

Sybil attack simulation on Enhanced IdAPoS protocol with dif...

引用

12th IEEE International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2024

作者： Chen, Shengyu Jin, Shenghao Wei, Yigang Zhang, Hui Beihang University State Key Laboratory of Complex & Critical Software Environment School of Computer Science & Engineering Beijing China Beihang University School of economics and management Beijing China

ISBN: (纸本)9798331510633

This study mainly focus on Sybil attacks with the Identity-Augmented Proof-of-Stake (IdAPoS) protocol under different network topologies, including random, scale-free, and hierarchical networks. The study finds that scale-free networks are more resistant to Sybil attacks, delaying their effects. Furthermore, the research improves the IdAPoS protocol by introducing active strategies for honest nodes, which improves the behaviours of this protocol, and by enabling them to dynamically assess and update their trusted and suspicious authority lists based on on-ledger data, which improves the completeness of this protocol. © 2024 IEEE.

关键词： Network topology

来源：评论

学校读者我要写书评

暂无评论

HYBRID SHARING FOR MULTI-LABEL IMAGE CLASSIFICATION 12

HYBRID SHARING FOR MULTI-LABEL IMAGE CLASSIFICATION

引用

12th International Conference on Learning Representations, ICLR 2024

作者： Yin, Zihao Gan, Chen He, Kelei Gao, Yang Zhang, Junfeng Medical School of Nanjing University China State Key Laboratory for Novel Software Technology Nanjing University China National Institute of Healthcare Data Science Nanjing University China

Existing multi-label classification methods have long suffered from label heterogeneity, where learning a label obscures another. By modeling multi-label classification as a multi-task problem, this issue can be regarded as a negative transfer, which indicates challenges to achieve simultaneously satisfied performance across multiple tasks. In this work, we propose the Hybrid Sharing Query (HSQ), a transformer-based model that introduces the mixture-of-experts architecture to image multi-label classification. HSQ is designed to leverage label correlations while mitigating heterogeneity effectively. To this end, HSQ is incorporated with a fusion expert framework that enables it to optimally combine the strengths of task-specialized experts with shared experts, ultimately enhancing multi-label classification performance across most labels. Extensive experiments are conducted on two benchmark datasets, with the results demonstrating that the proposed method achieves state-of-the-art performance and yields simultaneous improvements across most labels. The code is available at this URL. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

Rainfall Process Similarity Algorithm Research Based on Deep Learning by Using Precipitation Images 7

Rainfall Process Similarity Algorithm Research Based on Deep...

引用

7th International Conference on Computer Information science and Application Technology, CISAT 2024

作者： Yu, Yufeng Wu, Panqi Cai, Difei Liu, Weifu Wang, Xuhang Hohai University College of Computer Science and Software Engineering Nanjing210098 China

ISBN: (纸本)9798350375107

Rainfall is the main cause of flood disasters, and analyzing its features plays a crucial role in preventing flood disasters. How to extract rainfall process features and conduct rainfall similarity analysis is a challenging work. Based on the similarity search method for daily precipitation images, this paper proposes a rainfall process similarity search method, which extracts rainfall duration, cumulative precipitation, temporal distribution, spatial distribution and center movement trajectory as the features of rainfall process, and defines a set-weighting method based on the Grey Wolf Optimization algorithm (IGWO) to weight and fuse the five extracted features as the similarity measure of rainfall process. The similarity search results of rainfall process images on the Jialing Basin illustrate that the method proposed in this paper can efficiently and accurately identify similar rainfall processes in historical scenes, thereby providing a new technical support for intelligent rainfall-flood forecasting. © 2024 IEEE.

关键词： Rain

来源：评论

学校读者我要写书评

暂无评论

Kinematic,Workspace and Force Analysis of A Five-DOF Hybrid Manipulator R(2RPR)R/SP+RR

引用

Chinese Journal of Mechanical Engineering 2022年第5期35卷 232-243页

作者： Yundou Xu Fan Yang Youen Mei Dongsheng Zhang Yulin Zhou Yongsheng Zhao Laboratory of Parallel Robot and Mechatronic System of Hebei Province Yanshan UniversityQinhuangdao 066004China Key Laboratory of Advanced Forging&Stamping Technology and Science of Ministry of National Education Yanshan UniversityQinhuangdao 006004China School of Mechanical Engineering Yanshan UniversityQinhuangdao 066004China Tencent Robotics X Tencent HoldingsShenzhen 518057China

In the present study,the over-constrained hybrid manipulator R(2RPR)R/SP+RR is considered as the research *** this paper,kinematics of the hybrid manipulator,including the forward and inverse position,are ***,the workspace is checked based on the inverse position solution to evaluate whether the workspace of the hybrid manipulator meets the requirements,and the actual workspace of the hybrid robot is *** that,the force analysis of the over-constrained parallel mechanism is carried out,and an ADAMS-ANSYS rigid-flexible hybrid body model is established to verify the *** on the obtained results from the force analysis,the manipulator structure is ***,the structure optimization is carried out to improve the robot ***,calibration and workspace verification experiments are performed on the prototype,cutting experiment of an S-shaped aluminum alloy workpiece is completed,and the experiment verifies the machining ability of the *** work conducts kinematics,workspace,force analyses,structural optimization design and experiments on the over-constrained hybrid manipulator R(2RPR)R/SP+RR,providing design basis and technical support for the development of the novel hybrid manipulator in practical engineering.

关键词： Hybrid manipulator Over-constrained Kinematic analysis Stiffness analysis

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：