检索结果-南通市图书馆

Boosting Multi-modal Ocular recognition via Spatial Feature Reconstruction and Unsupervised Image Quality Estimation

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Machine Intelligence Research 2024年第1期21卷 197-214页

作者： Zihui Yan Yunlong Wang Kunbo Zhang Zhenan Sun Lingxiao He Center for Research on Intelligent Perception and Computing National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing 100190China JD AI Research Beijing 100176China

In the daily application of an iris-recognition-at-a-distance(IAAD)system,many ocular images of low quality are *** the iris part of these images is often not qualified for the recognition requirements,the more accessible periocular regions are a good complement for *** further boost the performance of IAAD systems,a novel end-to-end framework for multi-modal ocular recognition is *** proposed framework mainly consists of iris/periocular feature extraction and matching,unsupervised iris quality assessment,and a score-level adaptive weighted fusion ***,ocular feature reconstruction(OFR)is proposed to sparsely reconstruct each probe image by high-quality gallery images based on proper feature ***,a brand new unsupervised iris quality assessment method based on random multiscale embedding robustness is *** from the existing iris quality assess-ment methods,the quality of an iris image is measured by its robustness in the embedding *** last,the fusion strategy exploits the iris quality score as the fusion weight to coalesce the complementary information from the iris and periocular *** experi-mental results on ocular datasets prove that the proposed method is obviously better than unimodal biometrics,and the fusion strategy can significantly improve therecognition performance.

关键词： Iris recognition periocular recognition spatial feature reconstruction fully convolutional network flexible matching unsupervised iris quality assessment adaptive weight fusion

CASIA-Iris-Africa:A Large-scale African Iris Image Database

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Machine Intelligence Research 2024年第2期21卷 383-399页

作者： Jawad Muhammad Yunlong Wang Junxing Hu Kunbo Zhang Zhenan Sun School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Center for Research on Intelligent Perception and Computing National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing 100190China

Iris biometrics is a phenotypic biometric trait that has proven to be agnostic to human natural physiological *** on iris biometrics has progressed tremendously,partly due to publicly availab.e iris *** databases have been availab.e to researchers that address pressing iris biometric challenges such as constraint,mobile,multispectral,synthetics,long-distance,contact lenses,liveness detection,***,these databases mostly contain subjects of Caucasian and Asian docents with very few *** many investigative studies on racial bias in face biometrics,very few studies on iris biometrics have been published,mainly due to the lack of racially diverse large-scale databases containing sufficient iris samples of Africans in the public ***,most of these databases contain a relatively small number of subjects and lab.lled *** paper proposes a large-scale African database named Chinese Academy of Sciences institute of automation(CASIA)-Iris-Africa that can be used as a complementary database for the iris recognition community to mediate the effect of racial biases on *** database contains 28717 images of 1023 African subjects(2046 iris classes)with age,gender,and ethnicity attributes that can be useful in demographically sensitive studies of *** of specific application protocols are incorporated with the database to ensure the database’s variability and *** results of some open-source state-of-the-art(SOTA)algorithms on the database are presented,which will serve as baseline *** relatively poor performances of the baseline algorithms on the proposed database despite better performance on other databases prove that racial biases exist in these iris recognition algorithms.

关键词： African iris recognition racial bias iris image database biometrics iris recognition

Comprehensive Relation Modelling for Image Paragraph Generation

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Machine Intelligence Research 2024年第2期21卷 369-382页

作者： Xianglu Zhu Zhang Zhang Wei Wang Zilei Wang automation Department University of Science and Technology of ChinaHefei 230027China Center for Research on Intelligent Perception and Computing National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100864China

Image paragraph generation aims to generate a long description composed of multiple sentences,which is different from traditional image captioning containing only one *** of previous methods are dedicated to extracting rich features from image regions,and ignore modelling the visual *** this paper,we propose a novel method to generate a paragraph by modelling visual relationships ***,we parse an image into a scene graph,where each node represents a specific object and each edge denotes the relationship between two ***,we enrich the object features by implicitly encoding visual relationships through a graph convolutional network(GCN).We further explore high-order relations between different relation features using another graph convolutional *** addition,we obtain the linguistic features by projecting the predicted object lab.ls and their relationships into a semantic embedding *** these features,we present an attention-based topic generation network to select relevant features and produce a set of topic vectors,which are then utilized to generate multiple *** evaluate the proposed method on the Stanford image-paragraph dataset which is currently the only availab.e dataset for image paragraph generation,and our method achieves competitive performance in comparison with other state-of-the-art(SOTA)methods.

关键词： Image paragraph generation visual relationship scene graph graph convolutional network(GCN) long short-term memory

Distinct but correct: generating diversified and entity-revised medical response

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2024年第3期67卷 94-113页

作者： Bin LI Bin SUN Shutao LI Encheng CHEN Hongru LIU Yixuan WENG Yongping BAI Meiling HU College of Electrical and Information Engineering Hunan University School of Mathematics Sun Yat-sen University JD Technology national lab.ratory of pattern recognition Institute of AutomationChinese Academy of Sciences Xiangya Hospital of Central South University Teaching and Research Section of Clinical Nursing Xiangya Hospital of Central South University

Medical dialogue generation(MDG) is applied for building medical dialogue systems for intelligent consultation. Such systems can communicate with patients in real time, thereby improving the efficiency of clinical diagnosis. However, predicting correct entities and correctly generating distinct responses remain a great challenge. Inspired by actual doctors’ responses to patients, we consider MDG a two-stage task: entity prediction and dialogue generation. For entity prediction, we design an ent-mac post pre-training strategy by leveraging external medical entity knowledge to enhance the pre-trained model. For dialogue generation, we propose an entity-aware fusion MDG method in which predicted entities are integrated into the dialogue generation model through different encoding fusion mechanisms, using information from different sources. Because the diverse beam search algorithm can produce responses with entities that deviate from the predicted entities, an entity-revised diverse beam search is proposed to correct the entities entailed in the generated responses and make the generated responses more distinct. The experimental results on the China Conference on Knowledge Graph and Semantic Computing 2021(A/B tests) and the International Conference on Learning Representations 2021(online test) datasets show that the proposed method outperforms several state-of-the-art methods, which demonstrates its practicability and effectiveness.

关键词： medical entity prediction ent-mac post pre-training strategy entity-aware fusion medical dialogue generation encoding fusion mechanism entity-revised diverse beam search

同方期刊数据库

Multimodal Fusion of Brain Imaging Data: Methods and Applications

在线全文

学校读者我要写书评

暂无评论

Machine Intelligence Research 2024年第1期21卷 136-152页

作者： Na Luo Weiyang Shi Zhengyi Yang Ming Song Tianzi Jiang Brainnetome Center and national lab.ratory of pattern recognition Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Center for Excellence in Brain Science and Intelligence Technology Institute of AutomationChinese Academy of SciencesBeijing 100190China Research Center for Augmented Intelligence Zhejiang LaboratoryHangzhou 311100China

Neuroimaging data typically include multiple modalities,such as structural or functional magnetic resonance imaging,dif-fusion tensor imaging,and positron emission tomography,which provide multiple views for observing and analyzing the *** lever-age the complementary representations of different modalities,multimodal fusion is consequently needed to dig out both inter-modality and intra-modality *** the exploited rich information,it is becoming popular to combine multiple modality data to ex-plore the structural and functional characteristics of the brain in both health and disease *** this paper,we first review a wide spectrum of advanced machine learning methodologies for fusing multimodal brain imaging data,broadly categorized into unsupervised and supervised learning *** by this,some representative applications are discussed,including how they help to under-stand the brain arealization,how they improve the prediction of behavioral phenotypes and brain aging,and how they accelerate the biomarker exploration of brain ***,we discuss some exciting emerging trends and important future ***,we intend to offer a comprehensive overview of brain imaging fusion methods and their successful applications,along with the chal-lenges imposed by multi-scale and big data,which arises an urgent demand on developing new models and platforms.

关键词： Multimodal fusion supervised learning unsupervised learning brain atlas cognition brain disorders

Sustainable Mining in the Era of Artificial Intelligence

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 1-4页

作者： Long Chen Yuting Xie Yutong Wang Shirong Ge Fei-Yue Wang IEEE the State Key lab.ratory for Management and Control of Complex Systems at the institute of automation Chinese Academy of SciencesBeijing 100190China the national lab.ratory of pattern recognition at the institute of automation and Waytous Ltd.China the School of Computer Science and Engineering Sun Yat-Sen UniversityGuangzhou 510275GuangdongChina the School of Mechanical Electronic and Information Engineering China University of Mining and Technology BeijingBejing 100083China the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100190China

The mining sector historically drove the global economy but at the expense of severe environmental and health repercussions,posing sustainability challenges[1]-[3].Recent advancements on artificial intelligence(AI)are revolutionizing mining through robotic and data-driven innovations[4]-[7].While AI offers mining industry advantages,it is crucial to acknowledge the potential risks associated with its widespread ***-reliance on AI may lead to a loss of human control over mining operations in the future,resulting in unpredictable consequences.

关键词： Sustainable mining consequences

维普期刊数据库

Depth-Guided Vision Transformer With Normalizing Flows for Monocular 3D Object Detection

在线全文

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 673-689页

作者： Cong Pan Junran Peng Zhaoxiang Zhang the Center for Research on Intelligent Perception and Computing(CRIPAC) National Laboratory of Pattern Recognition(NLPR)Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190 the School of Future Technology University of Chinese Academy of Sciences(UCAS)Beijing 100049China the Huawei Inc. Beijing 100085China IEEE the institute of automation Chinese Academy of Sciences(CASIA)Beijing 100190 the University of Chinese Academy of Sciences(UCAS) Beijing 100049 the Centre for Artificial Intelligence and Robotics Hong Kong institute of Science&Innovation Chinese Academy of Sciences(HKISI CAS)Hong Kong 999077China

Monocular 3D object detection is challenging due to the lack of accurate depth *** methods estimate the pixel-wise depth maps from off-the-shelf depth estimators and then use them as an additional input to augment the RGB ***-based methods attempt to convert estimated depth maps to pseudo-LiDAR and then use LiDAR-based object detectors or focus on the perspective of image and depth fusion ***,they demonstrate limited performance and efficiency as a result of depth inaccuracy and complex fusion mode with *** from these approaches,our proposed depth-guided vision transformer with a normalizing flows(NF-DVT)network uses normalizing flows to build priors in depth maps to achieve more accurate depth *** we develop a novel Swin-Transformer-based backbone with a fusion module to process RGB image patches and depth map patches with two separate branches and fuse them using cross-attention to exchange information with each ***,with the help of pixel-wise relative depth values in depth maps,we develop new relative position embeddings in the cross-attention mechanism to capture more accurate sequence ordering of input *** method is the first Swin-Transformer-based backbone architecture for monocular 3D object *** experimental results on the KITTI and the challenging Waymo Open datasets show the effectiveness of our proposed method and superior performance over previous counterparts.

关键词： Monocular 3D object detection normalizing flows Swin Transformer

维普期刊数据库

Uncovering hidden nodes and hidden links in complex dynamic networks

在线全文

学校读者我要写书评

暂无评论

Science China(Physics,Mechanics & Astronomy) 2024年第4期67卷 51-63页

作者： Zhaoyang Zhang Xinyu Wang Haihong Li Yang Chen Zhilin Qu Yuanyuan Mi Gang Hu Department of Physics School of Physical Science and TechnologyNingbo UniversityNingbo 315211China School of Science Beijing University of Posts and TelecommunicationsBeijing 100876China Department of Medicine David Geffen School of MedicineUniversity of CaliforniaLos Angeles 90095USA Brainnetome Center and national lab.ratory of pattern recognition Institute of AutomationChinese Academy of SciencesBeijing 100190China Department of Psychology Tsinghua UniversityBeijing 100084China Department of Physics Beijing Normal UniversityBeijing 100875China

Inferring network structures from availab.e data has attracted much interest in network science;however,in many realistic networks,only some of the nodes are perceptible while others are hidden,making it a challenging *** this work,we develop a method for reconstructing the network with hidden nodes and links,taking account of fast-varying noise and time-delay *** calculating the correlations of availab.e data with different derivative orders for multiple pairs of accessible nodes,analyzing and integrating the relationships between different correlations,and defining diverse hidden-node-related reconstruction motifs,we can effectively identify the hidden nodes and hidden links in the network.

关键词： networks and genealogical trees stochastic analysis methods time series analysis

维普期刊数据库

同方期刊数据库

An adaptive large neighborhood search for the multi-point dynamic aggregation problem

在线全文

学校读者我要写书评

暂无评论

Control Theory and Technology 2024年第3期22卷 360-378页

作者： Shengyu Lu Bin Xin Jie Chen Miao Guo School of automation Beijing Institute of TechnologyBeijing 100081China national Key lab.of Autonomous Intelligent Unmanned Systems Beijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China

The multi-point dynamic aggregation(MPDA)problem is a challenging real-world *** the MPDA problem,the demands of tasks keep changing with their inherent incremental rates,while a heterogeneous robot fleet is required to travel between these tasks to change the time-varying state of each *** robots are allowed to collab.rate on the same task or work separately until all tasks are *** is challenging to generate an effective task execution plan due to the tight coupling between robots abilities and tasks'incremental rates,and the complexity of robot *** effectiveness consideration,we use the variable length encoding to avoid redundancy in the solution *** creatively use the adaptive large neighborhood search(ALNS)framework to solve the MPDA *** the proposed algorithm,high-quality initial solutions are generated through multiple problem-specific solution construction *** heuristics are also used to fix the broken solution in the novel integrated decoding-construction repair process of the ALNS *** results of statistical analysis by the Wilcoxon rank-sum test demonstrate that the proposed ALNS can obtain better task execution plans than some state-of-the-art algorithms in most MPDA instances.

关键词： Adaptive large neighborhood search(ALNS) Multi-point dynamic aggregation(MPDA) Heuristic solution construction Multi-robot collab.ration