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The improvement of hand gesture recognition based on sEMG by moving average filtering for features 3

The improvement of hand gesture recognition based on sEMG by...

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3rd international conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021

作者： Chen, Cai Li, Lijuan Zhang, Xikun Wang, Xingwei Han, Changming Xia, Tian Li, Wenchao Peng, Fulai Shen, Yang An, Jianpeng Shandong Institute of Advanced Technology Chinese Academy of Sciences Jinan China School of Public Health Tongji Medical College Huazhong University of Science and Technology Wuhan China Integrated Traditional Chinese and Western Medicine Hospitial of Tongzhou District Beijing China

ISBN: (纸本)9781450385046

Surface electromyographic signal (sEMG) is a kind of bioelectrical signal, which records the data of muscle activity intensity. Hand gesture recognition based on sEMG plays an important role in the hand rehabilitation robotics. Improving the recognition accuracy of hand gesture is the goal always pursued by researchers. This study purposes to evaluate the performance of moving average filtering for features in improving the accuracy of hand gesture recognition based on sEMG. Firstly, empirical mode decomposition was applied on the effective motion segments extracted by sliding windows with different size and stride. Afterward, 21 features were extracted from original signal and each of the intrinsic mode function. Subsequently, moving average filtering with different orders were used to further suppress the noise in each feature series to improve the recognition performance. Finally, two representative machine learning methods (including decision tree and K nearest neighbor) were used to evaluate the performance. Compared with the original features, the intra-subject recognition accuracy rate after feature processing for KNN and DT increase by 17%, and 6%, respectively. The accuracy of the inter-subject across five subjects after feature processing increase by 28% (KNN), and 12% (DT), respectively. The above results prove that the moving average filtering for features could effectively improve the performance of hand gesture recognition. © 2021 ACM.

关键词： machine learning

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3rd international conference on Intelligent Technologies and Applications, INTAP 2020

3rd International Conference on Intelligent Technologies and...

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3rd international conference on Intelligent Technologies and Applications, INTAP 2020

ISBN: (纸本)9783030717100

The proceedings contain 34 papers. The special focus in this conference is on Intelligent Technologies and Applications. The topics include: Interpretable Option Discovery Using Deep Q-learning and Variational Autoencoders;evaluating Predictive Deep learning Models;Pre-trained CNN Based Deep Features with Hand-Crafted Features and Patient Data for Skin Lesion Classification;data-Driven machine learning Approach for Human Action Recognition Using Skeleton and Optical Flow;multilingual Voice Impersonation Dataset and Evaluation;a Survey on Unknown Presentation Attack Detection for Fingerprint;hierarchical Interpolation of Imagenet Features for Cross-Dataset Presentation Attack Detection;cross-lingual Speaker Verification: Evaluation on X-Vector Method;fusion of Texture and Optical Flow Using Convolutional Neural Networks for Gender Classification in Videos;exploring Circular Hough Transforms for Detecting Hand Feature Points in Noisy Images from Ghost-Circle Patterns;A PM 2.5 Forecasting Model Based on Air Pollution and Meteorological Conditions in Neighboring Areas;the Aquatic Surface Robot (AnSweR), a Lightweight, Low Cost, Multipurpose Unmanned Research Vessel;empirical Analysis of Data Mining Techniques in Network Intrusion Detection Systems;deep Neural Network Based Malicious Network Activity Detection Under Adversarial machine learning Attacks;towards Low Cost and Smart Load Testing as a Service Using Containers;securityGuard: An Automated Secure Coding Framework;the Multi-objective Feature Selection in Android Malware Detection System;border Management Systems: How Can They Help Against Pandemics;translating Ethical Theory into Ethical Action: An Ethic of Responsibility Approach to Value-Oriented Design;An Example of Privacy and Data Protection Best Practices for Biometrics Data processing in Border Control: Lesson Learned from SMILE;protecting IoT Devices with Software-Defined Networks.

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Facial expression recognition using convolutional neural network with weighted loss function 3

Facial expression recognition using convolutional neural net...

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3rd IEEE international conference on Information Communication and signal processing (ICICSP)

作者： Luan, Jiawei Southwest Minzu Univ Chengdu Sichuan Peoples R China

ISBN: (数字)9781728188232

ISBN: (纸本)9781728188232

Facial expression is an important content in human communication as it is participating in nearly half of the human interaction. The recognition of facial expression has been applied in security, criminal research, entertainment applications, and other human-computer-interaction fields. Facial expression recognition is being extensively studied in recent years and have reached satisfactory results. However, the type of images of expressions in the commonly used datasets are unbalanced and cause the recognition of one to two facial expressions are harder than others, which affects the accuracy of the whole, Therefore, we create a loss function aim to decrease the effect of this unbalance. With the combination of the state-of-art convolutional neural network and our loss function, the accuracy on the FER-2013 dataset has raised about 2%.

关键词： machine learning facial expression recognition convolutional neural network

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Accurate Brain Tumor Detection Using Laplacian Based GAN Model

Accurate Brain Tumor Detection Using Laplacian Based GAN Mod...

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Disruptive Technologies (ICDT), international conference on

作者： Mayank Raj Arun Kumar Sachin Bansal Neeru Singh Megha Jain Sreenu Banoth Department of Information Technology Jss Academy of Technical Education Noida Uttar Pradesh India Department of Computer Science Engineering GL Bajaj Institute of Technology and Management Greater Noida Uttar Pradesh India Department of Computer Sceince DataSceince Jss Academy of Technical Education Noida Uttar Pradesh India School of Computer Science and Engineering IILM Univeristy Greater Noida Uttar Pradesh India

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

The very complexity of the brain and the processes it operates with makes its tumors one of the most complicated malignancies that are difficult to detect and heal. Both benign and malignant kinds of tumors could seriously impair ordinary brain function. Improved results entail early, accurate diagnoses but traditional methods of biopsies and X-rays have disadvantages and risks. Improvements in deep learning (DL) and machine learning (ML) have helped diagnose brain tumors using non-invasive methods like magnetic resonance imaging (MRI). This paper applies Graph Neural Networks (GNN) and Laplacian-based image processing to propose an automated brain tumor recognition system depend on the MRI data from the BraTS 2020 dataset to classify brain lesions as benign or malignant. Before segmenting the images with a U-Net-based model to delineate brain lesions, the technique pre-processed MRI images using Laplacian filtering for better edge identification and noise reduction. Data imbalance was handled with a hybrid Laplacian-based U-Net GAN model, and a Fast Graph Convolutional Network (GCN) was applied to identify malignant cells. To improve generalization and avoid overfitting, dropout layers and data augmentation were applied. The model succeeded in identifying the tumor with a 90% accuracy on 1000 datasets, but when it was increased to 1500 datasets, the overfitting caused the result to decrease to 75% and stabilize at 70%. Although the issue is still being faced with bigger datasets, the findings show promise for early timely detection of tumors.

关键词： Accuracy Laplace equations Graph convolutional networks Magnetic resonance imaging Brain tumors Brain modeling Biomedical image processing Lesions Overfitting Cancer

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Human-machine Interactions for on the Fly Free Text Input processing 3rd

Human-Machine Interactions for on the Fly Free Text Input Pr...

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3rd international conference on Human Systems Engineering and Design: Future Trends and Applications, IHSED 2020

作者： Dyck, Sergius Hoffmann, Almuth Fraunhofer Institute of Optronics System Technologies Image Exploitation IOSB Fraunhoferstr. 1 Karlsruhe76131 Germany

ISBN: (纸本)9783030582814

Information in machine-readable form has to be entered by users of information systems in various situations. In the input process, forms with a number of individual fields are commonly used. For the creator, this input can be cumbersome and potentially counterintuitive. For this reason, free text components are becoming increasingly important. Information in the form of free text is not machine-readable as such, and extracting information is complex. The accuracy of existing approaches used to extract information from free text components depends directly on the quality of the used internal model. These models have to be created by experts or trained in advance using the appropriate machine learning methods. The main objective presented in this paper is extracting information as well as enhancing the underlying model on the fly. This implies that the information extraction algorithms apply directly to the user’s input and that the user is enabled to correct possible deficiencies in the model as they arise. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Text processing

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Electric Power Forecasting Based on Logistic Regression and Gradient Boost Regression Tree 2021

Electric Power Forecasting Based on Logistic Regression and ...

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3rd international conference on Image, Video and signal processing, IVSP 2021

作者： Chen, Jichang Lu, Kelin Nanning University Nanning Guangxi530200 China Guangxi Industrial Technician College Nanning Guangxi530200 China

ISBN: (纸本)9781450388917

With the gradual marketization of power industry, power output forecasting is becoming more and more important in the power industry. The accurate power output of the power plant can be more reasonable for the power plant to make relevant decisions ensure the safe operation of the power plant. At the same time, the cost savings for the power plant to obtain more profits. In order to achieve the prediction of power output of the power plant, this paper uses logistics regression and gradient boosting regression tree on the basis of comprehensive analysis of the characteristics cause the power output to predict the power output of the public data set provided by a power plant. In the end, the average percentage error, root mean square error and relative value evaluation indexes is used to quantitatively analyze the prediction results and to evaluate the achievement of the two models in the prediction of electric energy output. © 2021 ACM.

关键词： machine learning

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A Survey of the Development of Artificial Intelligence Technology 3

A Survey of the Development of Artificial Intelligence Techn...

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3rd international conference on Unmanned Systems (ICUS)

作者： Li, Zhi Wang, Yilin Ji, Yunfang Yang, Wenyu Beijing HIWING Sci & Technol Informat Inst Beijing Peoples R China

ISBN: (纸本)9781728180250

Artificial intelligence technology is currently a hot spot for research and application, and the new cross-technology formed by artificial intelligence and multiple technologies has been widely used in Internet, finance, security and other industries. This paper first introduces the development of artificial intelligence, and then analyzes the key technologies of artificial intelligence, including computer vision, machine learning, natural language processing, human-computer exchange, virtual reality, biometric recognition, etc. Finally, the development trend of artificial intelligence technology is described.

关键词： artificial intelligence computer vision machine learning natural language processing virtual reality

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3rd international conference on Computer Science, Engineering and Education Applications, ICCSEEA 2020

3rd International Conference on Computer Science, Engineerin...

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3rd international conference on Computer Science, Engineering and Education Applications, ICCSEEA 2020

ISBN: (纸本)9783030555054

The proceedings contain 59 papers. The special focus in this conference is on Computer Science, Engineering and Education Applications. The topics include: Construction of Individual learning Scenarios;technology-Enhanced Financial Education and Sustainability Goals;health Status Recognition System for Communication Equipment Based on Data Mining;use of Sustainable Innovation in Information System: Integrate Individual’s Spirit and Team Climate;relations of the Genetic Code with Algebraic Codes and Hypercomplex Double Numbers;research on Logistics Center Location-Allocation Problem Based on Two-Stage K-Means Algorithms;operational Intelligence Software Concepts for Continuous Healthcare Monitoring and Consolidated Data Storage Ecosystem;method of Recognition and Indexing of People’s Faces in Videos Using Model of machine learning;deduplication Method for Ukrainian Last Names, Medicinal Names, and Toponyms Based on Metaphone Phonetic Algorithm;two-Layer Perceptron for Voice Recognition of Speaker’s Identity;significant Parameters of the Keystroke for the Formation of the Input Field of a Convolutional Neural Network;detection of Ventricular Late Potentials in Electrocardiograms Using machine learning;smart Prothesis: Sensorization, Humane Vibration and Processor Control;optimization of Stock Basing on Improved Grey Prediction Model: A Case Study on Garment Supply Chain;improved Post-quantum Merkle Algorithm Based on Threads;improvement of Merkle Signature Scheme by Means of Optical Quantum Random Number Generators;integrated Water Management and Environmental Rehabilitation of River Basins Using a System of Non-linear Criteria;distribution of Resources Between Composite Applications in a Hyperconverged System;the Possibilistic Gustafson-Kessel Fuzzy Clustering Procedure for Online Data processing;information System Penetration Testing Using Web Attack Automated Simulation.

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3rd international conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2020

3rd International Conference on Futuristic Trends in Network...

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3rd international conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2020

ISBN: (纸本)9789811614798

The proceedings contain 80 papers. The special focus in this conference is on Futuristic Trends in Network and Communication Technologies. The topics include: Unmanned Vehicles: Safety Management Systems and Safety Functions;probabilistic Characteristics of a Two-Channel Detector with Two Inertial Single-Photon Photoemission Devices and an Electronic Adder;energy and Spectrum-Aware Cluster-Based Routing in Cognitive Radio Sensor Networks;The Hybrid Approach for the Partitioning of VLSI Circuits;maximization of IoT Network Lifetime Using Efficient Clustering Technique;a Hybrid Metaheuristic to Solve Capacitated Vehicle Routing Problem;Energy Conservation in IOT: A Survey;identification of Implicit Threats Based on Analysis of User Activity in the Internet Space;EERO: Energy Efficient Route Optimization Technique for IoT Network;representing a Quantum Fourier Transform, Based on a Discrete Model of a Quantum-Mechanical System;forecasting Non-Stationary Time Series Using Kernel Regression for Control Problems;A Smart Waste Management System Based on LoRaWAN;simulation of the Semantic Network of Knowledge Representation in Intelligent Assistant Systems Based on Ontological Approach;A Deep learning Approach for Autonomous Navigation of UAV;framework for processing Medical Data and Secure machine learning in Internet of Medical Things;path Planning for Autonomous Robot Navigation: Present Approaches;Development of a Routing Protocol Based on Clustering in MANET;threat Model for Trusted Sensory Information Collection and processing Platform;autonomous Navigation of Mobile Robot with Obstacle Avoidance: A Review;Design of a Distributed Debit Management Network of Operating Wells of Deposits of the CMW Region;design of U-Shaped Multiline Microstrip Patch Antenna for Advanced Wireless Applications.

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3rd international conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2020

3rd International Conference on Futuristic Trends in Network...

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3rd international conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2020

ISBN: (纸本)9789811614828

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