检索结果-内蒙古大学图书馆

4th Multimodal Sentiment Analysis Challenge and Workshop, MuSe 2023, In conjunction with ACM Multimedia 2023

作者： Xie, Heng Cui, Jizhou Cao, Yuhang Chen, Junjie Tao, Jianhua Fan, Cunhang Liu, Xuefei Wen, Zhengqi Lu, Heng Yang, Yuguang Lv, Zhao Li, Yongwei Anhui Province Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei China School of Information Science and Technology ShanghaiTech University Shanghai China Ximalaya Inc. Shanghai China College of Computer and Information Engineering Tianjin Normal University Tianjin China Department of Automation Tsinghua University Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798400702709

Sentiment analysis plays a crucial role in interpreting human interactions across different modalities. This paper addresses the Cross-Cultural Multilingual Humour Detection Sub-Challenge in the MuSe 2023 Multi-modal Sentiment Analysis Challenge, which aims to identify humor instances in cross-cultural situations using multimodal data. In this paper, we explore the unique window length processing of audio data to more accurately and fully capture humor information. Furthermore, we employ a data augmentation technique for text to bridge the gap between the train set and the test set. This augmentation involves converting German and English samples in the database to each other, as well as translating both languages into Chinese. These techniques aim to enhance the model's generalization across different languages and alleviate the scarcity of humor samples. For multimodal fusion, we use the late fusion technique applied to different Gated Recurrent Unit (GRU) models with modality-specific weights obtained through gradient descent. Experimental results demonstrate the effectiveness of our approach, achieving an Area Under the Curve (AUC) score of 0.872 on the MuSe-Humor test set. This performance ranked second place in the sub-challenge. © 2023 ACM.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Impact of Adverse Weather on Commercial Helicopter Pilot Decision-Making and Standard Operating Procedures

Impact of Adverse Weather on Commercial Helicopter Pilot Dec...

引用

AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2021

作者： Speirs, Andrew H. Ramée, Coline Payan, Alexia P. Mavris, Dimitri N. Feigh, Karen M. Aerospace Systems Design Laboratory School of Aerospace Engineering Georgia Institute of Technology AtlantaGA30332-0150 United States Cognitive Engineering Center School of Aerospace Engineering Georgia Institute of Technology AtlantaGA30332-0150 United States

ISBN: (数字)9781624106101

ISBN: (纸本)9781624106101

Helicopter pilots face unique challenges with regard to adverse weather when compared to fixed-wing pilots. Rotorcraft typically operate at lower altitudes in off-field areas that are not always well covered by weather reporting stations. Although recent technological advances have increased the amount of weather data that pilots can access in the cockpit, weather remains a factor in 28% of fatal helicopter accidents. In this work, commercial helicopter pilots were surveyed and interviewed to better understand how they gather and process weather information, what the perceived limitations of current weather tools are, and how their decision-making process is affected by the information they gather and/or receive. Pilots were found to use a wide variety of weather sources for their initial go or no-go decision during the preflight phase, but use fewer weather sources in the cockpit while in-flight. Pilots highlighted the sparsity and sometimes inaccuracy of the weather information available to them in their prototypical operational domain. To compensate, they are forced to rely on local and experiential weather knowledge to supplement weather reports while still working to mitigate other external pressures. Based on the literature and on results from this work, recommendations are made to address the weather-related gaps faced by the rotorcraft community. © 2021, American Institute of Aeronautics and Astronautics Inc.. All rights reserved.

关键词： Fixed wings

来源：评论

学校读者我要写书评

暂无评论

Resource-Efficient Affordance Grounding with Complementary Depth and Semantic Prompts

arXiv

引用

arXiv 2025年

作者： Huang, Yizhou Yang, Fan Zhu, Guoliang Li, Gen Shi, Hao Zuo, Yukun Chen, Wenrui Li, Zhiyong Yang, Kailun School of Robotics and the National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University China School of Informatics University of Edinburgh United Kingdom State Key Laboratory of Extreme Photonics and Instrumentation Zhejiang University China

Affordance refers to the functional properties that an agent perceives and utilizes from its environment, and is key perceptual information required for robots to perform actions. This information is rich and multimodal in nature. Existing multimodal affordance methods face limitations in extracting useful information, mainly due to simple structural designs, basic fusion methods, and large model parameters, making it difficult to meet the performance requirements for practical deployment. To address these issues, this paper proposes the BiT-Align image-depth-text affordance mapping framework. The framework includes a Bypass Prompt Module (BPM) and a Text Feature Guidance (TFG) attention selection mechanism. BPM integrates the auxiliary modality depth image directly as a prompt to the primary modality RGB image, embedding it into the primary modality encoder without introducing additional encoders. This reduces the model’s parameter count and effectively improves functional region localization accuracy. The TFG mechanism guides the selection and enhancement of attention heads in the image encoder using textual features, improving the understanding of affordance characteristics. Experimental results demonstrate that the proposed method achieves significant performance improvements on public AGD20K and HICO-IIF datasets. On the AGD20K dataset, compared with the current state-of-the-art method, we achieve a 6.0% improvement in the KLD metric, while reducing model parameters by 88.8%, demonstrating practical application values. The source code will be made publicly available at https://***/DAWDSE/BiT-Align. Copyright © 2025, The Authors. All rights reserved.

关键词： Image coding

来源：评论

学校读者我要写书评

暂无评论

LanCOPE: Language-Guided Category-Level Object Pose Estimation from a Single RGB Image

引用

IEEE robotics and Automation Letters 2025年第7期10卷 7555-7562页

作者： Yang, Hui Sun, Wei Liu, Jian Zheng, Jin Dai, Zhenqi Mian, Ajmal Hunan University National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Changsha 410082 China Central South University School of Architecture and Art Changsha 410082 China The University of Western Australia Department of Computer Science and Software Engineering 6009 WA Australia

Monocular RGB-based category-level object pose estimation is more practical and cost-effective for robotics. However, existing methods do not fully exploit the rich semantic and contextual information in multimodal data (e.g. language) that provides additional object attributes to guide the model in extracting category features more reliably. We propose a language-guided category-level object pose estimation method (LanCOPE), taking a single RGB image as input. Our method uses DINOv2 to recover depth from a single RGB image and converts it into point cloud to perceive the object's geometry. We then introduce language descriptions for the RGB image, estimated point cloud and overall scene to better guide the point cloud encoder and image encoder in learning category features. We develop a cross-modal differential perception feature fusion network to fuse multimodal features. This network employs a differential perception module to eliminate redundant information across different modalities, highlighting signifcant semantic differences and similarities. Furthermore, it uses a cross-attention mechanism to fuse the semantic information of the language and vision features, improving the overall perception. Finally, we design a denoising network based on the skip fusion transformer to recover the object pose accurately. Extensive experiments on REAL275 and Wild6D datasets show that LanCOPE achieves state-of-the-art performance. Our code is available at LanCOPE. © 2016 IEEE.

关键词： category-level object pose estimation languag RGB image

来源：评论

学校读者我要写书评

暂无评论

Mechanically and Conductively Robust Eutectogel Fiber Produced by Continuous Wet Spinning Enables Epidermal and Implantable Electrophysiological Monitoring

引用

Advanced Fiber Materials 2024年第6期6卷 1980-1991页

作者： Shufeng Hu Jingya Song Qiong Tian Chen Zeng Yuchen Jiang Qihua Li Jun Xu Wei Yan Jun Li Zhiyuan Liu Weiqing Kong Meifang Zhu State Key Laboratory of Pulp and Paper Engineering Plant Fiber Materials Science Research CenterSouth China University of TechnologyGuangzhou 510006China State Key Laboratory for Modification of Chemical Fibers&Polymer Materials College of Materials Science and EngineeringDonghua UniversityShanghai 201620China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligent-Systems Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Standard Robots Co. LtdRoom 405Building DHuafeng International Robot Fusen Industrial ParkHangcheng AvenueGuxing CommunityXixiang StreetBaoan DistrictShenzhen 518000China Research Center for Neural Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China

In recent years,the collection and monitoring of human physiological signals have garnered increasing attention due to their wide-ranging applications in healthcare,human-machine interaction,sports,and other ***,the continuous fabrication of flexible gel fiber electrodes with high mechanical performance,high conductivity,and durability for extreme environments using a simple,efficient,and universal strategy remains challenging for physiological signal ***,we have employed a strategy of solvent replacement and multi-level hydrogen bond enhancement to construct eutectogel fibers with continuous solid-liquid structure,achieving continuous production of fibers with high strength,high conductivity,and low-temperature *** the fiber,PVA serves as the solid-state elastic phase,DES as the liquid ionic conductive phase,and CNF as the reinforcement *** resulting eutectogel fibers exhibit excellent tensile strength(37.3 MPa),good elongation(>700%),high electrical conductivity(0.543 S/m),and resistance to extreme dry and-60°C low-tem-perature ***,these eutectogel fibers demonstrate high sensitivity for monitoring joint movements and effectively detecting in vitro and in vivo signals,show casing their potential for wearable strain sensors and monitoring physiological signals.

关键词： Eutectogel fibers Wet spinning Hydrogen-bond networks Sensing

来源：评论

学校读者我要写书评

暂无评论

Research on Biomimetic Design Methods for Humanoid robot Thigh*

Research on Biomimetic Design Methods for Humanoid Robot Thi...

引用

IEEE International Conference on robotics and Biomimetics

作者： Daming Nie Anhuan Xie Lingyu Kong Yu Zhang Gang Zheng Yili Fu Jason Gu Intelligent Robot Research Center Zhejiang Laboratory Hangzhou China School of Mechanical and Energy Engineering Zhejiang University of Science and Technology Hangzhou China Department of Electrical and Computer Engineering Dalhousie University Halifax Canada

Human bones have formed the preferred configuration for high-strength and lightweight after long-time evolution. Taking human’s longest and strongest bone - the femur - as an example, it is consist of two characteristic layers, i.e. the substantia compacta and the substantia spongiosd. This article innovatively imitates the structural characteristics of human femur, the thigh of humanoid robot is designed in form of "variable thickness shell + variable density lattice". The thickness of shell and the density of lattice are adjusted by the initial stress distribution individually. Results show that the weight of shell and lattice of the thigh structure can be reduced by 20% under reasonable mapping relationship of "stress - shell thickness" and "stress - lattice rod diameter", while the structural stiffness meets the application requirements. Finally, the limiting factors of the "variable thickness shell + variable density lattice" structure designing approach are analyzed, and potential measures for optimizing the design method of the humanoid robot thigh in the future are described.

关键词：

来源：评论

学校读者我要写书评

暂无评论

GIFT: Graph-Induced Fine-Tuning for Multi-Party Conversation Understanding

arXiv

引用

arXiv 2023年

作者： Gu, Jia-Chen Ling, Zhen-Hua Liu, Quan Liu, Cong Hu, Guoping National Engineering Research Center of Speech and Language Information Processing University of Science and Technology of China Hefei China State Key Laboratory of Cognitive Intelligence China iFLYTEK Research Hefei China

Addressing the issues of who saying what to whom in multi-party conversations (MPCs) has recently attracted a lot of research attention. However, existing methods on MPC understanding typically embed interlocutors and utterances into sequential information flows, or utilize only the superficial of inherent graph structures in MPCs. To this end, we present a plug-and-play and lightweight method named graph-induced fine-tuning (GIFT) which can adapt various Transformer-based pre-trained language models (PLMs) for universal MPC understanding. In detail, the full and equivalent connections among utterances in regular Transformer ignore the sparse but distinctive dependency of an utterance on another in MPCs. To distinguish different relationships between utterances, four types of edges are designed to integrate graph-induced signals into attention mechanisms to refine PLMs originally designed for processing sequential texts. We evaluate GIFT by implementing it into three PLMs, and test the performance on three downstream tasks including addressee recognition, speaker identification and response selection. Experimental results show that GIFT can significantly improve the performance of three PLMs on three downstream tasks and two benchmarks with only 4 additional parameters per encoding layer, achieving new state-of-the-art performance on MPC understanding. Copyright © 2023, The Authors. All rights reserved.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

Transform-domain Image Enhancement for Underwater Visual SLAM based on Homomorphic Filter 3

Transform-domain Image Enhancement for Underwater Visual SLA...

引用

3rd International Conference on Image Processing, Computer Vision and Machine Learning, ICICML 2024

作者： Zhang, Shuo Zhang, Chaoyu Wang, Wei Zeng, Xinrui Luo, Bin Wuhan University State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan China China Nuclear Power Operation Technology Corporation LTD Wuhan China CNNC Engineering Research Center of Nuclear Industry Special Robot Wuhan China

ISBN: (纸本)9798350355413

Underwater visual SLAM algorithms play a vital role in autonomously localizing Autonomous Underwater Vehicles (AUV) in challenging underwater environments. The low-light conditions underwater necessitate the use of artificial lighting sources. However, this can lead to issues such as overexposed or underexposed images, resulting in reduced image contrast and information content. This study introduces a transform-domain image enhancement technique aimed at bolstering the resilience of underwater visual simultaneous localization and mapping (SLAM) systems. Specifically, a homomorphic filtering method is implemented to alleviate the impact of low-frequency lighting variations on images, thereby enhancing overall image clarity and bolstering the performance of visual SLAM systems. The efficacy of this filtering approach is validated through experiments conducted on the AQUALOC dataset. Our findings demonstrate that this method enhances the success rate of visual SLAM tracking, thereby enhancing its utility in AUV localization tasks. © 2024 IEEE.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

SHINE: Syntax-augmented Hierarchical Interactive Encoder for Zero-shot Cross-lingual Information Extraction

arXiv

引用

arXiv 2023年

作者： Ma, Jun-Yu Gu, Jia-Chen Ling, Zhen-Hua Liu, Quan Liu, Cong Hu, Guoping National Engineering Research Center of Speech and Language Information Processing University of Science and Technology of China Hefei China State Key Laboratory of Cognitive Intelligence China iFLYTEK Research Hefei China

Zero-shot cross-lingual information extraction (IE) aims at constructing an IE model for some low-resource target languages, given annotations exclusively in some rich-resource languages. Recent studies based on language-universal features have shown their effectiveness and are attracting increasing attention. However, prior work has neither explored the potential of establishing interactions between language-universal features and contextual representations nor incorporated features that can effectively model constituent span attributes and relationships between multiple spans. In this study, a syntax-augmented hierarchical interactive encoder (SHINE) is proposed to transfer cross-lingual IE knowledge. The proposed encoder is capable of interactively capturing complementary information between features and contextual information, to derive language-agnostic representations for various IE tasks. Concretely, a multilevel interaction network is designed to hierarchically interact the complementary information to strengthen domain adaptability. Besides, in addition to the well-studied syntax features of part-of-speech and dependency relation, a new syntax feature of constituency structure is introduced to model the constituent span information which is crucial for IE. Experiments across seven languages on three IE tasks and four benchmarks verify the effectiveness and generalization ability of the proposed method. Copyright © 2023, The Authors. All rights reserved.

关键词： Information retrieval

来源：评论

学校读者我要写书评

暂无评论

Transform-domain Image Enhancement for Underwater Visual SLAM based on Homomorphic Filter

Transform-domain Image Enhancement for Underwater Visual SLA...

引用

Image Processing, Computer Vision and Machine Learning (ICICML), International Conference on

作者： Shuo Zhang Chaoyu Zhang Wei Wang Xinrui Zeng Bin Luo State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan China China Nuclear Power Operation Technology Corporation LTD Wuhan China CNNC Engineering Research Center of Nuclear Industry Special Robot Wuhan China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

关键词： Location awareness Image quality Visualization Autonomous underwater vehicles Simultaneous localization and mapping Filtering Filtering algorithms Feature extraction Artificial light Image enhancement

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：