检索结果-南通市图书馆

XMe - Xiamen Molecular Electronics Code:An Intelligent and Open-Source Data Analysis Tool for Single-Molecule Conductance Measurements

引用

Chinese Journal of Chemistry 2024年第3期42卷 317-329页

作者： Zhichao Pan Gang Dong Chi Shang Ruihao Li Tengyang Gao Luchun Lin Huicong Duan Xiaohui Li Jie Bai Yilin Lai Wenfeng Wu Jia Shi Junyang Liu Wenjing Hong State Key Laboratory of Physical Chemistry of Solid Surfaces College of Chemistry and Chemical Engineering & Institute of Artificial IntelligenceXiamen UniversityXiamenFujian361005 China School of artificial intelligence Guilin University of Electronic TechnologyGuilinGuangxi541004 China

Charge transport characterization of single-molecule junctions is essential for the fundamental research of single-molecule physical chemistry and the development towards single-molecule electronic devices and circuits. Among the single-molecule conductance characterization techniques,the single-molecule break junction technique is widely used in tens of worldwide research laboratories which can generate a large amount of experimental data from thousands of individual measurement cycles. However,data interpretation is a challenging task for researchers with different research backgrounds,and the different data analysis approaches sometimes lead to the misunderstanding of the measurement data and even reproducibility issues of the measurement. It is thus a necessity to develop a user-friendly all-in-one data analysis tool that automatizes the basic data analysis in a standard and widely accepted way. In this work,we present the XMe Code (Xiamen Molecular Electronics Code),an intelligent all-in-one data analysis tool for the comprehensive analysis of single-molecule break junction data. XMe code provides end-to-end data analysis that takes in the original experimental data and returns electronic characteristics and even charge transport mechanisms. We believe that XMe Code will promote the transparency of the data analysis in single-molecule electronics and the collaborations among scientists with different research backgrounds.

关键词： Molecular electronics Single-molecule studies Break junction Data science Software

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Grasp Detection with Hierarchical Multi-Scale Feature Fusion and Inverted Shuffle Residual

引用

Tsinghua Science and Technology 2024年第1期29卷 244-256页

作者： Wenjie Geng Zhiqiang Cao Peiyu Guan Fengshui Jing Min Tan Junzhi Yu State Key Laboratory of Multimodal artificial intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of artificial intelligence University of Chinese Academy of SciencesBeijing 100049China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China

Grasp detection plays a critical role for robot *** pixel-wise grasp detection networks with encoder-decoder structure receive much attention due to good accuracy and ***,they usually transmit the high-level feature in the encoder to the decoder,and low-level features are *** is noted that low-level features contain abundant detail information,and how to fully exploit low-level features remains ***,the channel information in high-level feature is also not well ***,the performance of grasp detection is *** solve these problems,we propose a grasp detection network with hierarchical multi-scale feature fusion and inverted shuffle *** low-level and high-level features in the encoder are firstly fused by the designed skip connections with attention module,and the fused information is then propagated to corresponding layers of the decoder for in-depth feature *** a hierarchical fusion guarantees the quality of grasp ***,an inverted shuffle residual module is created,where the high-level feature from encoder is split in channel and the resultant split features are processed in their respective *** such differentiation processing,more high-dimensional channel information is kept,which enhances the representation ability of the ***,an information enhancement module is added before the encoder to reinforce input *** proposed method attains 98.9%and 97.8%in image-wise and object-wise accuracy on the Cornell grasping dataset,respectively,and the experimental results verify the effectiveness of the method.

关键词： grasp detection hierarchical multi-scale feature fusion skip connections with attention inverted shuffle residual

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Unsupervised Multi-Expert Learning Model for Underwater Image Enhancement

引用

IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 708-722页

作者： Hongmin Liu Qi Zhang Yufan Hu Hui Zeng Bin Fan the School of intelligence Science and Technology and the institute of artificial intelligence University of Science and Technology BeijingBeijing 100083China the School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China IEEE

Underwater image enhancement aims to restore a clean appearance and thus improves the quality of underwater degraded *** methods feed the whole image directly into the model for ***,they ignored that the R,G and B channels of underwater degraded images present varied degrees of degradation,due to the selective absorption for the *** address this issue,we propose an unsupervised multi-expert learning model by considering the enhancement of each color ***,an unsupervised architecture based on generative adversarial network is employed to alleviate the need for paired underwater *** on this,we design a generator,including a multi-expert encoder,a feature fusion module and a feature fusion-guided decoder,to generate the clear underwater ***,a multi-expert discriminator is proposed to verify the authenticity of the R,G and B channels,*** addition,content perceptual loss and edge loss are introduced into the loss function to further improve the content and details of the enhanced *** experiments on public datasets demonstrate that our method achieves more pleasing results in vision *** metrics(PSNR,SSIM,UIQM and UCIQE) evaluated on our enhanced images have been improved obviously.

关键词： Multi-expert learning underwater image enhancement unsupervised learning

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

EmotionIC: emotional inertia and contagion-driven dependency modeling for emotion recognition in conversation

引用

Science China(Information Sciences) 2024年第8期67卷 130-146页

作者： Yingjian LIU Jiang LI Xiaoping WANG Zhigang ZENG School of artificial intelligence and Automation Huazhong University of Science and Technology Hubei Key Laboratory of Brain-inspired Intelligent Systems Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control (Huazhong University of Science and Technology) Ministry of Education institute of artificial intelligence Huazhong University of Science and Technology

Emotion recognition in conversation(ERC) has attracted growing attention in recent years as a result of the advancement and implementation of human-computer interface technologies. In this paper,we propose an emotional inertia and contagion-driven dependency modeling approach(EmotionIC) for ERC tasks. Our EmotionIC consists of three main components, i.e., identity masked multi-head attention(IMMHA), dialogue-based gated recurrent unit(DiaGRU), and skip-chain conditional random field(SkipCRF).Compared to previous ERC models, EmotionIC can model a conversation more thoroughly at both the feature-extraction and classification levels. The proposed model attempts to integrate the advantages of attention-and recurrence-based methods at the feature-extraction level. Specifically, IMMHA is applied to capture identity-based global contextual dependencies, while Dia GRU is utilized to extract speaker-and temporal-aware local contextual information. At the classification level, SkipCRF can explicitly mine complex emotional flows from higher-order neighboring utterances in the conversation. Experimental results show that our method can significantly outperform the state-of-the-art models on four benchmark *** ablation studies confirm that our modules can effectively model emotional inertia and contagion.

关键词： conditional random field emotion recognition in conversation emotional inertia and contagion gated recurrent unit multi-head attention

来源：

同方期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

A hybrid attention model based on first-order statistical features for smoke recognition

引用

Science China(Technological Sciences) 2024年第3期67卷 809-822页

作者： GUO Nan LIU JiaHui DI KeXin GU Ke QIAO JunFei Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent SystemBeijing Artificial Intelligence InstituteBeijing 100124China Faculty of Information Technology Beijing University of TechnologyBeijing 100124China

Smoke and fire recognition are of great importance on foreseeing fire disasters and preventing environmental pollution by monitoring the burning process of objects(e.g., straw, fuels). However, since fire images suffer from problems like the variability of the features, complexity of scenarios, interference from background, changeable weather conditions as well as image quality problems, identifying smoke and fire accurately and promptly from a given image still remains a substantial challenge. Automatically learning the features of smoke images by CNNs has improved the target recognition ability compared to traditional approaches,nonetheless, convolutions and pooling operations in CNNs may cause severe information loss which may lead to *** tackle the above problems, this paper proposed a hybrid attention model based on the characteristics of smoke images. This model adopted multiple optimized attention mechanism in several stages to quickly and precisely capture the important features,achieving state-of-the-art performance on smoke and fire recognition in terms of accuracy and speed. Our proposed module mainly consists of two stages: pooling and attention. In the first stage, we conducted several newly proposed first-order pooling methods. Through traversing the data space in a larger scope, features are better reserved, thus constructing a more intact feature space of smoke and fire in an image. In the second stage, feature maps are aggregated together to perform channel and spatial attention. The channel and spatial dependencies allow us to quickly catch the important features presented in an image. By fully exploring the feature space and prominent salient features, characteristics of smoke and fire are better presented so as to obtain better smoke and fire detection results. Experiments have been conducted on public smoke detection dataset and new proposed fine-grained smoke and fire detection database. Experimental results revealed that the propose

关键词： hybrid attention first-order pooling smoke and fire detection deep convolutional neural networks

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Human-robot object handover:Recent progress and future direction

引用

Biomimetic intelligence & Robotics 2024年第1期4卷 1-13页

作者： Haonan Duan Yifan Yang Daheng Li Peng Wang institute of Automation Chinese Academy of SciencesBeijing 100190China School of artificial intelligence University of Chinese Academy of SciencesBeijing 100049China Centre for artificial intelligence and Robotics Hong Kong Institute of Science and InnovationChinese Academy of SciencesHong Kong 999077China

Human-robot object handover is one of the most primitive and crucial capabilities in human-robot *** is of great significance to promote robots to truly enter human production and life scenarios and serve human in numerous *** progressions in the field of human-robot object handover have been made by *** article reviews the recent literature on human-robot object *** this end,we summarize the results from multiple dimensions,from the role played by the robot(receiver or giver),to the end-effector of the robot(parallel-jaw gripper or multi-finger hand),to the robot abilities(grasp strategy or motion planning).We also implement a human-robot object handover system for anthropomorphic hand to verify human-robot object handover *** review aims to provide researchers and developers with a guideline for designing human-robot object handover methods.

关键词： Human-robot interactions Object handover

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Robust Regularization Design of Graph Neural Networks Against Adversarial Attacks Based on Lyapunov Theory

引用

Chinese Journal of Electronics 2024年第3期33卷 732-741页

作者： Wenjie YAN Ziqi LI Yongjun QI School of artificial intelligence Hebei University of Technology School of Computer Science and Engineering of North China institute of Aerospace Engineering

The robustness of graph neural networks（GNNs） is a critical research topic in deep *** researchers have designed regularization methods to enhance the robustness of neural networks,but there is a lack of theoretical analysis on the principle of *** order to tackle the weakness of current robustness designing methods,this paper gives new insights into how to guarantee the robustness of GNNs.A novel regularization strategy named Lya-Reg is designed to guarantee the robustness of GNNs by Lyapunov *** results give new insights into how regularization can mitigate the various adversarial effects on different graph *** experiments on various public datasets demonstrate that the proposed regularization method is more robust than the state-of-theart methods such as L1-norm,L2-norm,L2-norm,Pro-GNN,PA-GNN and GARNET against various types of graph adversarial attacks.

关键词： Training Deep learning Garnets Robustness Graph neural networks

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Ensemble successor representations for task generalization in offline-to-online reinforcement learning

引用

Science China(Information Sciences) 2024年第7期67卷 240-255页

作者： Changhong WANG Xudong YU Chenjia BAI Qiaosheng ZHANG Zhen WANG Space Control and Inertial Technology Research Center Harbin Institute of Technology Shanghai artificial intelligence Laboratory Shenzhen Research institute of Northwestern Polytechnical University School of Cybersecurity Northwestern Polytechnical University

In reinforcement learning(RL), training a policy from scratch with online experiences can be inefficient because of the difficulties in exploration. Recently, offline RL provides a promising solution by giving an initialized offline policy, which can be refined through online interactions. However, existing approaches primarily perform offline and online learning in the same task, without considering the task generalization problem in offline-to-online adaptation. In real-world applications, it is common that we only have an offline dataset from a specific task while aiming for fast online-adaptation for several tasks. To address this problem, our work builds upon the investigation of successor representations for task generalization in online RL and extends the framework to incorporate offline-to-online learning. We demonstrate that the conventional paradigm using successor features cannot effectively utilize offline data and improve the performance for the new task by online fine-tuning. To mitigate this, we introduce a novel methodology that leverages offline data to acquire an ensemble of successor representations and subsequently constructs ensemble Q functions. This approach enables robust representation learning from datasets with different coverage and facilitates fast adaption of Q functions towards new tasks during the online fine-tuning *** empirical evaluations provide compelling evidence showcasing the superior performance of our method in generalizing to diverse or even unseen tasks.

关键词： offline reinforcement learning online fine-tuning task generalization successor representations ensembles

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Vector field path following for a micro flapping-wing robot

引用

Science China(Information Sciences) 2024年第6期67卷 442-444页

作者： Haifeng HUANG Yingte LIU Tao NIU Chang WANG Yao ZOU Wei HE School of intelligence Science and Technology University of Science and Technology Beijing institute of artificial intelligence University of Science and Technology Beijing Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of EducationUniversity of Science and Technology Beijing

Flapping-wing robots mimic the flight patterns of natural flying creatures,granting them natural *** hold promising applications in the military reconnaissance,urban surveillance,and various other fields[1–3].However,the current limitations in size often restrict the suitability of existing bird-like flapping-wing robots,

关键词：

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

A Knowledge-enhanced Two-stage Generative Framework for Medical Dialogue Information Extraction

引用

Machine intelligence Research 2024年第1期21卷 153-168页

作者： Zefa Hu Ziyi Ni Jing Shi Shuang Xu Bo Xu School of artificial intelligence University of Chinese Academy of SciencesBeijing 100049China institute of Automation Chinese Academy of SciencesBeijing 100190China

This paper focuses on term-status pair extraction from medical dialogues(MD-TSPE),which is essential in diagnosis dia-logue systems and the automatic scribe of electronic medical records(EMRs).In the past few years,works on MD-TSPE have attracted increasing research attention,especially after the remarkable progress made by generative ***,these generative methods output a whole sequence consisting of term-status pairs in one stage and ignore integrating prior knowledge,which demands a deeper un-derstanding to model the relationship between terms and infer the status of each *** paper presents a knowledge-enhanced two-stage generative framework(KTGF)to address the above *** task-specific prompts,we employ a single model to com-plete the MD-TSPE through two phases in a unified generative form:We generate all terms the first and then generate the status of each generated *** this way,the relationship between terms can be learned more effectively from the sequence containing only terms in the first phase,and our designed knowledge-enhanced prompt in the second phase can leverage the category and status candidates of the generated term for status ***,our proposed special status"not mentioned"makes more terms available and en-riches the training data in the second phase,which is critical in the low-resource *** experiments on the Chunyu and CMDD datasets show that the proposed method achieves superior results compared to the state-of-the-art models in the full training and low-re-sourcesettings.

关键词： Medical dialogue understanding information extraction text generation knowledge-enhanced prompt low-resource setting dataaugmentation

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

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：