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A vision-based sign language recognition system using tied-mixture density HMM 04

A vision-based sign language recognition system using tied-m...

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ICMI'04 - Sixth International Conference on Multimodal Interfaces

作者： Zhang, Liang-Guo Chen, Yiqiang Fang, Gaolin Chen, Xilin Gao, Wen Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Department of Computer Science Harbin Institute of Technology Harbin 150001 China Graduate School Chinese Academy of Sciences Beijing 100080 China

ISBN: (纸本)1581139543

In this paper, a vision-based medium vocabulary Chinese sign language recognition (SLR) system is presented. The proposed recognition system consists of two modules. In the first module, techniques of robust hands detection, background subtraction and pupils detection are efficiently combined to precisely extract the feature information with the aid of simple colored gloves in the unconstrained environment. Meanwhile, an effective and efficient hierarchical feature description scheme with different scale features to characterize sign language is proposed, where principal component analysis (PCA) is employed to characterize the finger features more elaborately. In the second part, a Tied-Mixture Density Hidden Markov Models (TMDHMM) framework for SLR is proposed, which can speed up the recognition without the significant loss of recognition accuracy compared with the continuous hidden Markov models (CHMM). Experimental results based on 439 frequently used Chinese sign language (CSL) words show that the proposed methods can work well for the medium vocabulary SLR in the environment without special constraints and the recognition accuracy is up to 92.5%. Copyright 2004 ACM.

关键词： Character recognition

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A Method Based on Deep Neural Network for Instance Segmentation of Retinal Lesions Caused by Diabetic Retinopathy

A Method Based on Deep Neural Network for Instance Segmentat...

引用

2022 International Conference on Computational science and Computational Intelligence, CSCI 2022

作者： Santos, Carlos Aguiar, Marilton Welfer, Daniel Silva, Marcelo Pereira, Alejandro Ribeiro, Marcelo Belloni, Bruno Computer Center Federal Institute of Education Science and Technology Farroupilha Alegrete Brazil Postgraduate Program in Computing Federal University of Pelotas Pelotas Brazil Postgraduate Program in Computer Science Federal University of Santa Maria Santa Maria Brazil Federal University of Pelotas Pelotas Brazil Federal Institute of Education Science and Technology Sul-Rio-Grandense Passo Fundo Brazil

ISBN: (纸本)9798350320282

Diabetic Retinopathy is one of the main causes of vision loss and can be identified through ophthalmological exams that aim to locate the presence of retinal lesions such as microaneurysms, hemorrhages, soft exudates, and hard exudates. The development of computerized methods to perform the instance segmentation of lesions may support in the early diagnosis of the disease. However, the instance segmentation of retinal artifacts is a complex task due to factors such as the size of objects and their morphological characteristics. This article proposes a method based on a Mask R-CNN neural network architecture to perform instance segmentation of lesions associated with diabetic retinopathy. The proposed method was trained, adjusted, and tested using the public DDR and IDRiD Diabetic Retinopathy datasets, and implemented with the Detectron2 and OpenCV libraries. The proposed method reached in the DDR dataset, using the SGD optimizer, the mAP of 0.2660 for the limit of I oU of 0.5 in the validation step. The results obtained in the experiments demonstrate that the proposed method showed promising results in the instance segmentation of fundus lesions. © 2022 IEEE.

关键词： Deep neural networks

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Identifying machine query for an intelligent web browser system

Identifying machine query for an intelligent web browser sys...

引用

IEEE Symposium on Web Society

作者： Zhu, Tingshao Xu, Xinguo Liu, Guohua Graduate University of Chinese Academy of Sciences Beijing China National Computer System Engineering Research Institute of China Beijing China Department of Computing Science University of Alberta Edmonton Canada

ISBN: (纸本)9781424463572

This paper describes our research on learning browsing behavior model for predicting the current information need of a web user. This inference is based on a parameterized model of how the sequence of browsing behavior indicates the degree to which page content satisfies the user's information need, and the model parameters can be estimated using standard methods from a labelled corpus. Data from lab experiments demonstrate that the prediction model can effectively identify the information needs of new users, browsing previously unseen pages. The paper concludes with an overview of our WebIC which integrates the model into a web browser, to help the user find the relevant information effectively from the web. © 2010 IEEE.

关键词： Web browsers

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A multi-criteria programming model for intelligent tutoring planning

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10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006

作者： Ruihong, Shi Peng, Lu Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China Graduate School Chinese Academy of Sciences China College of Computer Science and Technology Beijing Institute of Technology China

ISBN: (纸本)3540465359

This paper proposed a practical approach to personalized tutoring planning by exploiting existing tutoring resources (e.g., a book, a courseware). More exactly, it does not build an instructional course from scratch - from the domain curriculum, as most Intelligent Tutoring Systems (ITS) do. Instead, information in the curriculum model is used as metadata, together with other metadata, to describe tutoring resources. Given a learning requirement (learning objectives and/or constraints), it finds out the most appropriate tutoring resource(s) and proposes a proper learning sequence of them. Based on the proposed fuzzy instructional model and learner model, the tutoring planning problem is defined as a multi-criteria programming (MCP) model. © Springer-Verlag Berlin Heidelberg 2006.

关键词： computer programming

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Mobile Apps for Healthy Life Education for Young People 2

Mobile Apps for Healthy Life Education for Young People

引用

2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Suwandi, Benedictus Evan Warnars, Diana Teresia Spits Warnars, Harco Leslie Hendric Spits Utomo, Wiranto Herry Ramadhan, Arief Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Information Systems Information System Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Computing President University Department of Magister Science of Information Technology Bekasi17550 Indonesia

ISBN: (纸本)9781665400527

Health education is crucial for the community, especially the younger generation, because adolescent behavior/lifestyle will carry over into adulthood, and it is difficult to change it. This paper proposes designing and implementing a mobile application for young people for healthy lifestyle education. This mobile application implemented with the android studio is designed using use case diagrams to describe the business processes of this mobile application. In addition, activity diagrams describe the process details of each activity use case, and class diagrams describe the design of the database model, which is implemented using a MySQL database. © 2022 IEEE.

关键词： Mobile computing

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Concurrency control protocol for parallel B-tree structures that improves the efficiency of request transfers and SMOs within a node

Concurrency control protocol for parallel B-tree structures ...

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作者： Yoshihara, Tomohiro Kobayashi, Dai Yokota, Haruo Research and Development Group Hitachi Ltd. Yokohama-shi244–0817 Japan Department of Computer Science Graduate School of Information Science and Engineering Tokyo Institute of Technology Tokyo152–8552 Japan Department of Computer Science School of Computing Tokyo Institute of Technology Tokyo152–8552 Japan

Many concurrency control protocols for B-trees use latch-coupling because its execution is efficient on a single machine. Some studies have indicated that latch-coupling may involve a performance bottleneck when using multicore processors in a shared-everything environment, but no studies have considered the possible performance bottleneck caused by sending messages between processing elements (PEs) in shared-nothing environments. We propose two new concurrency control protocols, "LCFB" and "LCFB-link", which require no latch-coupling in optimistic processes. The LCFB-link also innovates B-link approach within each PE to reduce the cost of modifications in the PE, as a solution to the difficulty of consistency management for the side pointers in a parallel B-tree. The B-link algorithm is well known as a protocol without latch-coupling, but Blink has the difficulty of guaranteeing the consistency of the side pointers in a parallel B-tree. Experimental results in various environments indicated that the system throughput of the proposed protocols was always superior to those of the conventional protocols, particularly in large-scale configurations, and using LCFB-link was effective for higher update ratios. In addition, to mitigate access skew, data should migrate between PEs. We have demonstrated that our protocols always improve the system throughput and are effective as concurrency controls for data migration. Copyright © 2018 The institute of Electronics, Information and Communication Engineers

关键词： Concurrency control

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Hierarchical voting classification scheme for improving visual sign language recognition

Hierarchical voting classification scheme for improving visu...

引用

13th ACM International Conference on Multimedia, MM 2005

作者： Zhang, Liang-Guo Chen, Xilin Wang, Chunli Gao, Wen Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Department of Computer Science Harbin Institute of Technology Harbin 150001 China Graduate School of the Chinese Academy of Sciences Beijing 100080 China

ISBN: (纸本)1595930442

As one of the important research areas of multimodal interaction, sign language recognition (SLR) has attracted increasing interest. In SLR, especially on medium or large vocabulary, it is usually difficult or impractical to collect enough training data. Thus, how to improve the recognition on the limited training samples is a significant issue. In this paper, a simple but effective hierarchical voting classification (HVC) scheme for improving visual SLR, which makes efficient use of limited training data, is proposed. The key idea of HVC scheme is similar to but not the same as Bagging technique. Firstly, it constructs several training sets from the original training set in a combinatorial fashion to generate the corresponding continuous hidden Markov models (CHMM) ensemble. Then, it determines the ensemble output by appropriate local voting strategy. Finally, it obtains the final recognition result by the global voting. Experimental results show that the HVC scheme outperforms the conventional single CHMM approach in terms of recognition accuracy on the limited training data. Copyright © 2005 ACM.

关键词： Hidden Markov models

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A motion vector predictor architecture for AVS and MPEG-2 HDTV decoder

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PCM 2006: 7th Pacific Rim Conference on Multimedia

作者： Junhao, Zheng Di, Wu Lei, Deng Don, Xie Wen, Gao Institute of Computing Technology Chinese Academy of Sciences 100080 Beijing China Department of Computer Science Harbin Institute of Technology 150001 Harbin China Graduate University Chinese Academy of Sciences China Corporation China

ISBN: (纸本)3540487662

In the advanced Audio Video coding Standard (AVS), many efficient coding tools are adopted in motion compensation, such as new motion vector prediction, direct mode matching, variable block-sizes etc. However, these features enormously increase the computational complexity and the memory bandwidth requirement and make the traditional MV predictor more complicated. This paper proposes an efficient MV predictor architecture for both AVS and MPEG-2 decoder. The proposed architecture exploits the parallelism to accelerate the speed of operations and uses the dedicated design to optimize the memory access. In addition, it can reuse the on-chip buffer to support the MV error-resilience for MPEG-2 decoding. The design has been described in Verilog HDL and synthesized using 0.18μm CMOS cells library by Design Compiler. The circuit costs about 62k logic gates when the working frequency is set to 148.5MHz. This design can support the real-time MV predictor of HDTV 1080i video decoding for both AVS and MPEG-2. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Image coding

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Adult image detection combining BoVW based on region of interest and color moments

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作者： Yizhi, Liu Shouxun, Lin Sheng, Tang Yongdong, Zhang Laboratory of Advanced Computing Research Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University of the Chinese Academy of Sciences Beijing 100039 China Institute of Computer Science and Engineering Hunan University of Science and Technology Xiangtan 411201 China

ISBN: (纸本)3642163262

To prevent pornography from spreading on the Internet effectively, we propose a novel method of adult image detection which combines bag-of-visual-words (BoVW) based on region of interest (ROI) and color moments (CM). The goal of BoVW is to automatically mine the local patterns of adult contents, called visual words. The usual BoVW method clusters visual words from the patches in the whole image and adopts the weighting schemes of hard assignment. However, there are many background noises in the whole image and soft-weighting scheme is better than hard assignment. Therefore, we propose the method of BoVW based on ROI, which includes two perspectives. Firstly, we propose to create visual words in ROI for adult image detection. The representative power of visual words can be improved because the patches in ROI are more indicative to adult contents than those in the whole image. Secondly, soft-weighting scheme is adopted to detect adult images. Moreover, CM is selected by evaluating some commonly-used global features to be combined with BoVW based on ROI. The experiments and the comparison with the state-of-the-art methods show that our method is able to remarkably improve the performance of adult image detection. © 2010 IFIP.

关键词： Color

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Learning Adaptation and Generalization from Human-Inspired Meta-Reinforcement Learning Using Bayesian Knowledge and Analysis 6

Learning Adaptation and Generalization from Human-Inspired M...

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6th IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2023

作者： Ho, Joshua Wang, Chien-Min King, Chung-Ta You, Yi-Hsin Feng, Chi-Wei Chen, Yen-Min Kuo, Bo-Yi Institute of Information Science Academia Sinica Taipei11529 Taiwan Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Taiwan Institute of Information Systems and Applications National Tsing Hua University Hsinchu30013 Taiwan Department of Computer Science National Tsing Hua University Hsinchu30013 Taiwan Department of Computer Science National Taiwan University Taipei10631 Taiwan Center of Intelligent Healthcare National Taiwan University Hospital Taipei10022 Taiwan

ISBN: (纸本)9798350331288

Over the last decades, there has been growing interest in research in multiple and interdisciplinary fields of human-AI computing. In particular, approaches integrating the intersecting design with reinforcement learning (RL) have received more attention. However, the current research on RL may need to consider its enhancement from a humaninspired approach further. In the present work, we focus on enabling a meta-reinforcement learning (meta-RL) agent to achieve adaptation and generalization according to modeling Markov decision processes using Bayesian knowledge and analysis. By introducing a novel framework called human-inspired meta-RL (HMRL), we incorporate the agent performing resilient actions to leverage the dynamic dense reward based on the knowledge and prediction of a Bayesian analysis. The proposed framework can make the agent learn generalization and prevent the agent from failing catastrophically. The experimental results show that our approach helps the agent reduce computational costs with learning adaptation. Finally, we conclude and anticipate that integrating human-inspired meta-RL can enable learning more formulations relating to robustness and scalability, leading to promising directions and more complex AI goals in the future. © 2023 IEEE.

关键词： Reinforcement learning

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