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检索条件"任意字段=International Conference on Soft Computing and Pattern Recognition"

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26th international conference on pattern recognition, ICPR 2022

26th International Conference on Pattern Recognition, ICPR 2...

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26th international conference on pattern recognition, ICPR 2022

ISBN: (纸本)9783031376597

The proceedings contain 49 papers. The special focus in this conference is on . The topics include: Toward Surroundings-Aware Temporal Prediction of 3D Human Skeleton Sequence;MTGR: Improving Emotion and Sentiment Analysis with Gated Residual Networks;a Computational Approach for Analysing Autistic Behaviour During Dyadic Interactions;region-Based Trajectory Analysis for Abnormal Behaviour Detection: A Trial Study for Suicide Detection and Prevention;automated Behavior Labeling During Team-Based Activities Involving Neurodiverse and Neurotypical Partners Using Multimodal Data;emergence of Collaborative Hunting via Multi-Agent Deep Reinforcement Learning;computational Multimodal Models of Users’ Interactional Trust in Multiparty Human-Robot Interaction;an Exploratory Study on Group Potency Classification from Non-verbal Social Behaviours;multi-Channel Time-Series Person and soft-Biometric Identification;to Invest or Not to Invest: Using Vocal Behavior to Predict Decisions of Investors in an Entrepreneurial Context;appearance-Independent Pose-Based Posture Classification in Infants;enhancing the Linear Probing Performance of Masked Auto-Encoders;involving Density Prior for 3D Point Cloud Contrastive Learning;joint Masked Autoencoding with Global Reconstruction for Point Cloud Learning;understanding the Properties and Limitations of Contrastive Learning for Out-of-Distribution Detection;deep Learning Architectures for Pain recognition Based on Physiological Signals;Egocentric Hand Gesture recognition on Untrimmed Videos Using State Activation Gate LSTMs;representation Learning for Tablet and Paper Domain Adaptation in Favor of Online Handwriting recognition;active Learning Monitoring in Classroom Using Deep Learning Frameworks;pain Detection in Biophysiological Signals: Transfer Learning from Short-Term to Long-Term Stimuli Based on Signal Segmentation;leveraging Sentiment Analysis Knowledge to Solve Emotion Detection Tasks;emotion, Age and Gender Prediction Through Ma

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ISM 2022 - 4th international conference on Industry 4.0 and Smart Manufacturing

ISM 2022 - 4th International Conference on Industry 4.0 and ...

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4th international conference on Industry 4.0 and Smart Manufacturing, ISM 2022

The proceedings contain 199 papers. The topics discussed include: infrastructure network support and leapfrogging Africa to Industry 4.0: the case of Tanzania;comparison of energy-use efficiency for lettuce plantation under nutrient film technique and deep-water culture hydroponic systems;an edge-cloud based reference architecture to support cognitive solutions in process industry;logistics 4.0 in intermodal freight transport;analysis of sustainable concrete obtained from the by-products of an industrial process and recycled aggregates from construction and demolition waste;intelligent concrete surface cracks detection using computer vision, pattern recognition, and artificial neural networks;spatial change recognition model using artificial intelligence to remote sensing;smart trip prediction model for metro traffic control using data mining techniques;encryption and generation of images for privacy-preserving machine learning in smart manufacturing;and using analytical and data-driven methods to develop a soft-sensor for flow rate monitoring in tube extrusion.

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Application and effectiveness of weighted KNN in pattern recognition of communication modulated signals 4

Application and effectiveness of weighted KNN in pattern rec...

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4th IEEE international conference on Civil Aviation Safety and Information Technology, ICCASIT 2022

作者： Li, Yulin Hong, Guihang Feng, Congran Beijing Jiaotong University Beijing China Sun Yat-sen University Guangzhou China Hainan University Haikou China

ISBN: (数字)9781665467667

ISBN: (纸本)9781665467667

Modulation pattern recognition of communication signals is a key technology in wireless communication, and the continuous complexity of the channel environment has put forward higher requirements on the communication signal modulation capability. This paper proposes a pattern recognition method of communication modulated signal based on weighted KNN. Firstly, signals of different modulation modes were generated in MATLAB. Then, the modulated signal features in the time and frequency domain were extracted, and the information entropy was included. Secondly, the extracted features were used to train and test the weighted KNN algorithm. By comparing the recognition effect of the modulated signals before and after signal feature extraction, it is concluded that feature extraction has a substantial improvement on the recognition accuracy and computing efficiency of weighted KNN, and different features have a significant effect on the recognition. © 2022 IEEE.

关键词： Feature extraction

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Follicular Unit Registration Based on Binocular Stereo Vision for Hair Transplantation Surgery Robot 6

Follicular Unit Registration Based on Binocular Stereo Visio...

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6th international conference on Data Science and Information Technology, DSIT 2023

作者： Wang, Weiduo Liu, Jinfeng Yang, Jie Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Department of Automation China Shanghai Jiao Tong University Institute of Medical Robotics China

ISBN: (纸本)9798350304442

In this paper, we focus on the follicular unit registration problem for hair transplantation surgery robots based on binocular stereo vision system. The follicular units in both images are detected with YOLO V5 network. Because of the dull and similar pattern of the follicular units, previous regular methods which are pixel-based are reported with misalignment and poor accuracy. To solve this problem, we propose the context shape to describe the feature of the follicular unit. The distribution of units surrounding the target unit is estimated as the context shape. Then, Otsu's method is used to segment hairs and Hungarian algorithm is used to match the hairs in the matched follicular unit. Then, the hairs are projected to 3D coordinate system and reconstructed. The experiments on the generated hair dataset demonstrate that the proposed method achieves both high accuracy and speed. © 2023 IEEE.

关键词： Stereo vision

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pattern recognition on Railway Points with Machine Learning: A Real Case Study 2nd

Pattern Recognition on Railway Points with Machine Learning:...

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2nd international conference on Ubiquitous computing and Intelligent Information Systems (ICUIS)

作者： Munoz del Rio, Alba Ramirez, Isaac Segovia Garcia Marquez, Fausto Pedro Univ Castilla La Mancha Ingenium Res Grp Ciudad Real 13071 Spain

ISBN: (纸本)9789811925412;9789811925405

Railway points are crucial components to ensure the reliability of railway networks. Several types of condition monitoring systems are widely applied in the industry with the aim of early fault detection, since the presence of faults can cause reductions in operational safety, delays and increased maintenance costs. The application of fault detection systems and pattern recognition tools is essential to ensure new improvements in the industry. The novelty proposed in this work is the application of statistical analysis and Machine Learning techniques in power curves defined by the movement of the motors in the opening and closing movements. The Shapelets algorithm is selected for pattern recognition, analyzing curves with abnormal distribution that demonstrate the presence of faults. The results provide high accuracy with performance measures above 90%.

关键词： Machine learning pattern recognition Railway points Shapelets algorithm

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Application of Substring Search Algorithms to Hindi based on pattern recognition 1

Application of Substring Search Algorithms to Hindi based on...

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1st international conference on Applied Artificial Intelligence and computing, ICAAIC 2022

作者： Sahu, Barkha Joshi, Brijendra Kumar Military College of Telecommunication Engineering Mhow India

ISBN: (纸本)9781665497107

Substring search is a basic operation in all text processing applications. Among many algorithms for this purpose, there are three that are very common, namely Knuth-Morris-Pratt, Boyer-Moore and Rabin-Karp algorithms. All these are applied generally to English (byte-based text). This paper presents the experimental validation of these algorithms when they are applied to Hindi (UTF-8 encoded) text made up from 49000 unique Hindi words. © 2022 IEEE.

关键词： Text processing

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AI-Enabled Video Diagnosis and Assisted Walking with Exoskeleton for Parkinson’s Disease 7th

AI-Enabled Video Diagnosis and Assisted Walking with Exoskel...

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7th international conference on Innovative computing, IC 2024

作者： Tu, Cathy Qian, Chi Man Concordia International School Shanghai Shanghai201206 China

ISBN: (纸本)9789819741922

Parkinson’s disease is a chronic and progressive disease resulting from the lack of substantia nigra, or a specific type of nerve cell in the brain’s basal ganglia. The four major motor symptoms of Parkinson’s are bradykinesia, rigidity, tremor, and postural or gait instability. This paper seeks to innovate an artificial intelligence (AI) and engineering solution that involves diagnosing different stages of Parkinson’s disease and mediating the external effects of the symptoms on patients’ quality of life. An AI-based approach incorporating video-processing using MediaPipe and pattern recognition with a Long Short-Term Memory (LSTM) neural network diagnoses Parkinson’s patients when stationary. This method mainly focuses on identifying and measuring rest tremors, a typical symptom of Parkinson’s disease. With an analysis of the patient’s disease progression and specific external symptoms, we can assist and train the patient to mitigate the adverse effects of such symptoms. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Diagnosis

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Automatic Diagnosis and Grading of Diabetic Retinopathy using Bat Optimization Algorithm-Refined Deep Residual Network

Automatic Diagnosis and Grading of Diabetic Retinopathy usin...

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2023 international conference on Evolutionary Algorithms and soft computing Techniques, EASCT 2023

作者： Lakshmi, B. Haritha Kaneti, Venkata Ramana Soundariya, R.S. Nayak, Sanjib Kumar Rajesh, N. Malla Reddy Engineering College for Women It Department Hyderabad India Vnr Vignana Jyothi Institute of Engineering and Technology Department of Computer Science and Engineering Hyderabad India Bannari Amman Institute of Technology Department of Computer Technology Sathyamangalam India Hyderabad India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350313413

Diabetic Retinopathy (DR) is one of the most severe sight-threatening disorders resulting from diabetes, and can eventually lead to blindness and visual impairment. Early detection and medical therapy can assist in controlling and preventing DR progression. However, manual grading is extremely difficult and time-consuming because of the retina's complicated structure. In this research, the Bat Optimization Algorithm- Refined Deep Residual Network (BOA-RDRN) is proposed for automatic diagnosis and grading of DR. Initially, the DIARETDB0 dataset is employed for the proposed method, and then pre-processing is performed for image denoising which eliminates noise. The Attention-based Fusion Network (AFU-Net) is used to segment the lesion region. The Grey-Level Co-occurrence Matrix (GLCM) and Local Ternary pattern (LTP) are used to extract the features and BOA is employed to find an optimal subset of features in retinal images. Finally, the RDRN is utilized to classify the anomalies as normal or abnormal. The BOA-RDRN achieves an accuracy of 99.42% compared to the existing methods such as Tunicate Swarm Spider Monkey optimization-based Refined Deep Residual Network (TSSMO-RDRN), Weighted Kernel Fuzzy C-Means Clustering and Dilation-Based Function (WKFM-DBF), Improved Harris Hawk Optimization-based Convolution Neural Network (IHHO-CNN), and Enhanced Fuzzy C-Means Clustering-Resnet 152 respectively. © 2023 IEEE.

关键词： Bat Optimization Algorithm Diabetic Retinopathy Grey-Level Co-occurrence Matrix Local Ternary pattern Refined Deep Residual Network

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Performance Analysis of User Behavior pattern Mining Using Web Log Database for User Identification 8th

Performance Analysis of User Behavior Pattern Mining Using W...

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8th international conference on soft computing: Theories and Applications, SoCTA 2023

作者： Gokulapriya, R. Ganesh Kumar, R. Karnataka Bangalore India

ISBN: (纸本)9789811998577

User behavior analytics is a progressive research domain. Understanding the user’s behavior patterns and identifying their behavior patterns will provide solutions to many issues like identity theft and user authentication. So many research works are done in analyzing the frequent access patterns of the users by pre-processing access logs and applying various algorithms to understand the frequent access behavior of the user. From the literature, it founds that the frequent user access pattern identification needs improvement on prediction accuracy and the minimal false positives. To accomplish these, three different approaches were proposed to overcome the existing issues and intended to reduce false positives and improve the frequent pattern mining accuracy based on web access logs. Proposed methods were found to be good while compared with the existing works. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Authentication

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Hysteretic Oscillator-Based Reservoir computing for Audio Waveform pattern recognition

Hysteretic Oscillator-Based Reservoir Computing for Audio Wa...

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international Joint conference on Neural Networks (IJCNN)

作者： Reiji Ota Yuzuru Kato Yuichi Katori School of Systems Information Science Future University Hakodate Hakodate Japan

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Reservoir computing (RC), a framework for recurrent neural networks, is adept at learning the dynamics of time series data. RC, requiring less computational cost for training than traditional recurrent neural networks, is versatile in applications such as time series generation, prediction, pattern recognition, and robot control. Recently, the integration of physical system dynamics, particularly oscillatory phenomena, into RC has been explored. This study presents an RC model incorporating oscillators with hysteresis as network elements, focusing on their ubiquitous nature. In speech pattern recognition, the audio waveform, a complex vibration pattern of air, is typically preprocessed into a frequency component time series. This study, however, attempts pattern recognition by using the raw speech waveform as the direct input to the oscillator-based reservoir. The application of this model in recognizing and classifying time series vocal data is investigated, including an assessment of the oscillator elements’ bifurcation parameter on RC performance.

关键词： Error analysis Computational modeling Time series analysis Reservoir computing Speech recognition Bifurcation Reservoirs

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