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检索条件"任意字段=Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition"

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Scalable parallel processing design for real time handwritten OCR

Scalable parallel processing design for real time handwritte...

引用

international conference on pattern recognition

作者： A. Cuhadar A.C. Downton Electronic Systems Engineering Department University of Essex Colchester UK

this paper presents a generalised technique for parallelising embedded computer vision and pattern recognition applications and shows how it has been applied to the recognition of handwritten postcodes on envelopes. the technique is based upon the utilisation of pipelines of processor farms (PPF), and is applicable to any embedded system with continuous input/output data streams. the postcode recogniser combines temporal multiplexing and data parallelism to achieve a speedup of 21.4 compared with the original sequential application, using a total of 52 transputers.

关键词： Parallel processing Process design Optical character recognition software Pipelines Dictionaries Handwriting recognition Concurrent computing throughput Systems engineering and theory Computer vision

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Reservoir computing in Rehabilitation Video Analyses 10

Reservoir Computing in Rehabilitation Video Analyses

引用

10th IEEE international conference on Cybernetics and Intelligent Systems and IEEE conference on Robotics, Automation and Mechatronics, CIS-RAM 2023

作者： Yang, Dongping Xu, Tie Lin, Feng Zhejiang Lab Research Institute for Artificial Intelligence Hangzhou China

ISBN: (纸本)9798350303087

Spatio-temporal information processing is fundamental in rehabilitation video analyses. Current strategies for spatio-temporal pattern recognition usually involve explicit feature extraction followed by feature aggregation, which requires a large amount of labeled data. there are two major challenges for recognizing complex spatio-temporal patterns. One is on extracting the representative features;and the other is on extracting the temporal structure, in particular, the temporal order, of image sequences. Reservoir computing (RC) offers a promising tool by enabling automatic and accurate analyses of complex movement patterns in rehabilitation videos. Unlike traditional machine learning techniques, RC does not require explicit training of the reservoir connections, which is less data- demanding, more resistant to overfilling and easier to implement. the unique properties make it an attractive option for analyzing rehabilitation video data, where patients may experience changes in their movement patterns over time with a large data flow for processing. By analyzing new video data, the reservoir can adapt and refine its output to reflect the patient's current conditions. © 2023 IEEE.

关键词： Machine learning

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Control of Hand Prostheses using EMG based pattern recognition: A Review of Existing Classification Techniques and Future Implementation 5

Control of Hand Prostheses using EMG based Pattern Recogniti...

引用

5th international conference on Inventive Research in computing Applications, ICIRCA 2023

作者： Emayavaramban, G. Santhosh Kumar, T. Amudha, A. Siva Ramkumar, M. Selvaganapathi, T. Sivaraju, S. Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore India Rvs College of Engineering and Technology Department of Electrical and Electronics Engineering Coimbatore India

ISBN: (纸本)9798350321425

Electromyography (EMG) signal is a type of biological signal that comes from the activity of nerves and muscles. Most of the time, an EMG device is used to record the EMG data. these signs are used to check for medical problems, find out how active an animal is, and figure out how it moves. Hand prosthesis is a device which used to replace the missing part of human parts. It enables amputees to perform their daily activity without anyone supports. this research provides a quick overview on how EMG classification methods work for hand prosthesis. Finally, this study found that 80% to 99% of the times, the present technologies are good enough to pick up and classify the EMG signals. Once the signal is recorded, the accuracy of recognition is based on the classification algorithms used. Signals are then decoded for their intended use, such as moving a robotic arm, recognizing speech, analyzing gait, etc. the accuracy of decoding the EMG signal has already gone above 99%, and it will get even better with the new deep learning technology. this review study helps to understand how well new methods are suitable for classifying EMG signals. © 2023 IEEE.

关键词： Deep learning

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Estimating pre-term birth using a hybrid pattern classification system

Estimating pre-term birth using a hybrid pattern classificat...

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12th Mediterranean conference on Medical and Biological Engineering and computing, MEDICON 2010

作者： Frize, M. Yu, N. Systems and Computer Engineering Carleton University Ottawa Canada School of Information Technology and Engineering University of Ottawa Ottawa Canada

ISBN: (纸本)9783642130380

In this work, pre-term birth (PTB) was estimated with an accuracy as high as that of the invasive and expensive fibronectin test, yet produced these results only using data acquired before week 23 of gestation. We were able to estimate PTB for both parous and nulliparous women and expanded the model to all North America from a previous model valid for USA only. © 2010 international Federation for Medical and Biological Engineering.

关键词： Neural networks

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12th IFIP WG 12.5 international conference and Workshops on Artificial Intelligence Applications and Innovations, AIAI 2016

12th IFIP WG 12.5 International Conference and Workshops on ...

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12th IFIP WG 12.5 international conference and Workshops on Artificial Intelligence Applications and Innovations, AIAI 2016

ISBN: (纸本)9783319449432

the proceedings contain 62 papers. the special focus in this conference is on Medical Artificial Intelligence Modeling, Classification - pattern recognition, Ontology-Web and Social Media AI Modeling, Environmental AI Modeling, Machine Learning-Learning, Optimization-SVM, Agents-Robotics-Control, Artificial Neural Network Modeling and New Methods and Tools for Big Data wokshop. the topics include: A cumulative training approach to schistosomiasis vector density prediction;mobile and evolving tool to predict colorectal cancer survivability;machine learning preprocessing method for suicide prediction;increasing diversity in random forests using naive bayes;identifying asperity patterns via machine learning algorithms;combining prototype selection with local boosting;modeling economic open data;web image indexing using wice and a learning-free language model;an intelligent internet search assistant based on the random neural network;deep neural networks for web page information extraction;environmental impact on predicting olive fruit fly population using trap measurements;a hybrid soft computing approach producing robust forest fire risk indices;applying artificial neural networks to short-term pm2.5 forecasting modeling;convolutive audio source separation using robust ica and reduced likelihood ratio jump;use of flight simulators in analyzing pilot behavior;active learning algorithms for multi-label data;design of an advanced smart forum for tesys e-learning platform;efficient support vector machine classification using prototype selection and generation;genetic search of pickup and delivery problem solutions for self-driving taxi routing and introducing chemotaxis to a mobile robot.

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12th international Workshop of Advanced Manufacturing and Automation, IWAMA 2022

12th International Workshop of Advanced Manufacturing and Au...

引用

12th international Workshop of Advanced Manufacturing and Automation, IWAMA 2022

ISBN: (纸本)9789811993374

the proceedings contain 100 papers. the special focus in this conference is on Advanced Manufacturing and Automation. the topics include: Analysis of the Uniformity of Flow Field Inside the Bulk Curing Barn During the Yellowing Period on CFD;design of an Automated Stereoscopic Warehouse Device Applied in Experimental Teaching;optimization Design of Mobile Offline Data Acquisition Terminal for Mechanical Equipment;optimization Design of Server for Mobile Offline Data of Mechanical Equipment;design of a Trajectory Tracking Controller for Precision Motion Platform;effect of Cerium Size and Content on Friction Properties of MoS2 Coatings;a Review of Data-Driven Techniques for Neuromarketing;camera Parameter Calibration Based on the Correction of Center Positioning Deviation in Machine Vision;An Unmanned Ground System Based on ROS;A Named Entity recognition Method for Cigarette Production Process Standard Based on BERT-BiLSTM-CRF Model;Optimization of Pneumatic Separating Process Parameters Based on BP Neural Network;influences of Process Parameters of threshing Drumon Leaf threshing Quality on First Stage threshing;analysis of the Flow Field in the Lower Air-Inlet Drying Area of the Tobacco Baking Equipment;research on Long and Short Stem recognition and Calculation of Long and Short Stem Rate Based on Machine Vision;reconstructed Algorithm of Temperature Field of Leaf Moistening Machine Rotary Roller Based on Spatial Interpolation;numerical Simulation and Analysis of Material Movement in Composite Air Separator;design of Data Acquisition System for Hybrid Vehicle Based on Internet of things;edge computing Algorithm Analysis for Predictive Maintenance of Hydraulic Station;preface;research on Driverless Vehicle.

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A vision method for computing 3-D location and shape parameters of a cone

A vision method for computing 3-D location and shape paramet...

引用

international conference on pattern recognition

作者： Tsorng-Lin Chia Zen Chen Department of Electrical Engineering Cheng Institute of Technology Taoyuan Taiwan Institute of Computer Science and Information Engineering National Chiao Tung University Hsinchu Taiwan

ISBN: (纸本)0818662654

A simple vision method to determine the 3-D location and shape parameters of a cone by using structured light is presented. the key concept in the proposed method is to convert the complex curved stripe pattern to an equivalent, but simpler, linear stripe pattern. the conic surface patch lying between the two visible silhouette edges is replaced by the plane defined by the two silhouette edges that cuts the cone. the appropriate geometric models are given to compute the cone axis and shape parameters representing the height of the cone and the radius of the cone base.

关键词： Computer vision Shape Cameras Surface fitting Computer science Solid modeling Inspection Manufacturing Calibration Stereo vision

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AGENTVERSE: FACILITATING MULTI-AGENT COLLABORATION AND EXPLORING EMERGENT BEHAVIORS 12

AGENTVERSE: FACILITATING MULTI-AGENT COLLABORATION AND EXPLO...

引用

12th international conference on Learning Representations, ICLR 2024

作者： Chen, Weize Su, Yusheng Zuo, Jingwei Yang, Cheng Yuan, Chenfei Chan, Chi-Min Yu, Heyang Lu, Yaxi Hung, Yi-Hsin Qian, Chen Qin, Yujia Cong, Xin Xie, Ruobing Liu, Zhiyuan Sun, Maosong Zhou, Jie Tsinghua University China Beijing University of Posts and Telecommunications China Pattern Recognition Center WeChat AI Tencent Inc. China

Autonomous agents empowered by Large Language Models (LLMs) have undergone significant improvements, enabling them to generalize across a broad spectrum of tasks. However, in real-world scenarios, cooperation among individuals is often required to enhance the efficiency and effectiveness of task accomplishment. Hence, inspired by human group dynamics, we propose a multi-agent framework AGENTVERSE that can effectively orchestrate a collaborative group of expert agents as a greater-than-the-sum-of-its-parts system. Our experiments demonstrate that AGENTVERSE can proficiently deploy multi-agent groups that outperform a single agent. Extensive experiments on text understanding, reasoning, coding, tool utilization, and embodied AI confirm the effectiveness of AGENTVERSE. Moreover, our analysis of agent interactions within AGENTVERSE reveals the emergence of specific collaborative behaviors, contributing to heightened group efficiency. We will release our codebase, AGENTVERSE, to further facilitate multi-agent research. © 2024 12th international conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Autonomous agents

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Graph computing and Graph Database Applications In Power System Online Dispatch 12

Graph Computing and Graph Database Applications In Power Sys...

引用

12th international conference on Renewable Power Generation, RPG 2023

作者： Wang, Yishen Wei, Renjie Lin, Siyan Tang, Zhuang State Grid Laboratory of Grid Advanced Computing and Applications Beijing China State Grid Smart Grid Research Institute Co. Ltd. Beijing China

In the new types of power systems, characterized by the dominance of renewable energies, uncertain resources such as wind and solar power will play a significant role in power generation. However, the inherent unpredictability and fluctuation of these renewable sources make the operating conditions complex and variable. To address this, intelligent online dispatch applications that integrate optimization and artificial intelligence techniques need to be implemented. In terms of online dispatch, estimating system states and optimizing resources require computing a large number of variables while adhering to operating constraints. Graph computing and graph database technologies have shown promising results in power system online analysis. this paper analyzes the applications of these graph computing techniques to enhance online dispatch and provides a graph computing based-grid online analysis architecture. this architecture offers a range of online situational awareness applications and decision-making support. © the Institution of Engineering & Technology 2023.

关键词： Information management

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POWERTEST: A tool for energy conscious weighted random pattern testing

POWERTEST: A tool for energy conscious weighted random patte...

引用

12th international conference on VLSI Design

作者： Zhang, XD Roy, K Bhawmik, S Purdue Univ W Lafayette IN 47907 USA

ISBN: (纸本)0769500137

Due to the increasing use of portable computing and wireless communications systems, energy consumption is of major concern in today's VLSI circuits. With that in mind we present an energy conscious weighted random pattern testing technique for Built-In-Self-Test (BIST) applications. Energy consumption during BIST operation can be minimized while achieving high fault coverage. Simple measures of observability and controllability of circuit nodes are proposed based on primary input signal probability (probability that a signal is logic ONE). Such measures help determine the testability of a circuit. We developed a tool, POWERTEST, which uses a genetic algorithm based search to determine optimal weight sets (signal probabilities or input signal distribution) at primary inputs to minimize energy dissipations. the inputs conforming to the primary input weight see can be generated using cellular automata or LFSR (Linear Feedback Shift Register). We observed that a single input distribution (or weights) may not be sufficient for some random-pattern resistant circuits, while multiple distributions consume larger area. As a trade-off, two distributions have been used in our analysis. Results on ISCAS benchmark circuits show that energy reduction of up to 97.82% can be achieved (compared to equi-probable random-pattern testing with identical fault coverage) while achieving high fault coverage.

关键词： testing random testing weighted random pattern testing energy conscious testing

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