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共 1490 条记录，以下是21-30 订阅

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3rd International conference on Emergent Converging Technologies and Biomedical Systems, ETBS 2023

3rd International Conference on Emergent Converging Technolo...

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3rd International conference on Emergent Converging Technologies and Biomedical Systems, ETBS 2023

ISBN: (纸本)9789819986453

The proceedings contain 56 papers. The special focus in this conference is on Emergent Converging Technologies and Biomedical Systems. The topics include: Smart Health Monitoring System for Elderly People;impact of Covid-19 and Subsequent Usage of IoT;design of Battery Monitoring System for Converted Electric Cycles;image Denoising Framework Employing Auto Encoders for image Reconstruction;server Access pattern analysis Based on Weblogs Classification Methods;multilingual Emotion recognition from Continuous Speech Using Transfer Learning;Violence Detection Using DenseNet and LSTM;financial Technology and Competitive Landscape in the Banking Industry of Bangladesh: An Exploratory Focus;on Parameterized Picture Fuzzy Discriminant Information Measure in Medical Diagnosis Problem;review on Deep Learning-Based Classification Techniques for Cocoa Quality Testing;a Curated Study on Machine Learning Based Algorithms and Sensors for Drone Technology in Various Application;automatic Detection of Coagulation of Blood in Brain Using Deep Learning Approach;deepPose: A 2D image Based Automated Framework for Human Pose Detection and a Trainer App Using Deep Learning;Phylogenetic Study of Surface Glycoprotein (S1 Spike Protein) Sequence of SARS-CoV-2 Virus;pervasive and Wearable Computing and Networks;power of image-Based Digit recognition with Machine Learning;open-Source Gesture-Powered Augmented Reality-Based Remote Assistance Tool for Industrial Application: Challenges and Improvisation;enhancing Biometric Performance Through Mitigation of Sleep-Related Breaches;Neural Network Based CAD System for the Classification of Textures in Liver Ultrasound images;fuzzy Vendor–Buyer Trade Credit Inventory Model-Pentagonal Numbers in Permissible Limits Delay in Account Settlement with Supervised Learning;a Comparative Survey on Histogram Equalization Techniques for image Contrast Enhancement.

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Interactive Segmentation of Art images based on Point Cloud Pre-Training 3

Interactive Segmentation of Art Images based on Point Cloud ...

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3rd International conference on Sentiment analysis and Deep Learning, ICSADL 2024

作者： Tian, Yuan Tao, Yiran Nanhang Jincheng College Jiangsu Province Nanjing City210000 China

ISBN: (纸本)9798350396157

This study presents an innovative interactive segmentation algorithm for fine art images using point cloud pre-Training principles. With increasing demands for precision and variety in image processing, conventional methods are proving inadequate. image segmentation, a central aspect of visual data manipulation, involves dividing an image into distinct regions based on static or dynamic features. This study reviews supervised and unsupervised segmentation strategies, emphasizing the importance of fuzzy clustering algorithms in practical applications. Despite advances in medical image segmentation, challenges remain due to the complex nature of image processing. A universally applicable segmentation method and standardized evaluation criteria are elusive. To address these challenges, the proposed algorithm combines Local Binary pattern (LBP) feature extraction with a point cloud pre-Training model, utilizing the U-net architecture for accurate segmentation. Experiments conducted on an Ubuntu 14.04 64-bit OS using C++ and Python demonstrate the effectiveness of the algorithm. The visualized results show its potential for practical applications and lay the foundation for future advances in image segmentation. © 2024 IEEE.

关键词： image segmentation

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3rd International conference on Information Technologies and Intelligent Decision Making Systems, ITIDMS 2023

3rd International Conference on Information Technologies and...

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3rd International conference on Information Technologies and Intelligent Decision Making Systems, ITIDMS 2023

ISBN: (纸本)9783031603174

The proceedings contain 18 papers. The special focus in this conference is on Information Technologies and Intelligent Decision Making Systems. The topics include: Comparative analysis of Traditional Machine Learning Approaches for Time Series Clustering Under Colored Noise;on the Open Transport Data analysis Platform;investigation of the Characteristics of a Frequency Diversity Array Antenna;comparative analysis of Fuzzy Controllers in a Truck Cruise Control System;implementation of a Blockchain-Based Software Tool to Verify the Authenticity of Paper Documents;development of Methods and Algorithms for Dimension Reduction of Space Description for pattern recognition Problem;service for Checking Students’ Written Work Using a Neural Network;implementing a Jenkins Plugin to Visualize Continuous Integration Pipelines;elimination of Optical Distortions Arising from In Vivo Investigation of the Mouse Brain;quantum Fourier Transform in image Processing;choosing an Information Protection Mechanism Based on the Discrete Programming Method;application of Machine Learning Methods for Annotating Boundaries of Meshes of Perineuronal Nets;diagnostics of Animals Diseases Based on the Principles of Neutrosophic Sets and Sugeno Fuzzy Inference;the Technique of Processing Non-Gaussian Data Based on Artificial Intelligence;development of Automation and Control System of Waste Gas Production Process Based on Information Technology;machine Learning and Data Mining.

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Person recognition using Gait Energy image, MobileNetV3Small and Machine Learning 3

Person Recognition using Gait Energy Image, MobileNetV3Small...

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3rd IEEE International conference on Technology, Engineering, Management for Societal Impact using Marketing, Entrepreneurship and Talent, TEMSMET 2023

作者： Suthar, Omprakash Katkar, Vijay Vaghela, Krunal Marwadi University Department of Computer Engineering Rajkot India Marwadi University Department of Information Technology Rajkot India

ISBN: (纸本)9798350397819

In the past few decades, gait as a biometric attribute has garnered a lot of attention for its application in a broad variety of security and privacy-related scenarios, including identity recognition and authentication. The deployment of surveillance cameras allows for the collection of Gait data, which is a non-invasive form of identification that is based on a biometric trait that can be seen from a distance and can be utilized for identifying reasons. It is difficult to create reliable automatic gait identification systems since Gait can be modified by several covariate parameters. Some of these covariate elements include garments, walking tempo, camera view angle. In this work, a method for recognizing people with a high degree of accuracy is demonstrated. This paper makes use of the Gait Energy image, MobileNetV3Sma11 model, and Machine Learning to develop an approach to recognize person using Gait pattern. The paper includes experimental findings, including precision, recall, f1-score, and classification accuracy, all of which point to the effectiveness of the suggested method. © 2023 IEEE.

关键词： Gait analysis

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3rd World conference on Intelligent and 3D Technologies, WCI3DT 2024

3rd World Conference on Intelligent and 3D Technologies, WCI...

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3rd World conference on Intelligent and 3D Technologies, WCI3DT 2024

ISBN: (纸本)9789819791279

The proceedings contain 45 papers. The special focus in this conference is on Intelligent and 3D Technologies. The topics include: Multi-scale Point Cloud Shape Completion Network Based on Deep Learning;research on Application and Effect Evaluation of Product Innovation Management Based on Deep Learning;study on Deep Learning-Based Personalised Product Recommendation Model for Autonomous Question-and-Answer Robot;application of image Watermarking Technology Based on Deep Learning in Copyright Protection;research on the Combination of Building Structural Health Monitoring and Deep Learning image Processing;electrical Equipment Prediction in a Variable Electromagnetic Field Using Deep Learning;state Monitoring and Fault Prediction of Wind Farm Transmission and Transformation Equipment Based on Deep Learning;application of Deep Learning Algorithms in the Innovation Ecosystem of Electric Power;optimization Strategy for Inventory Management Based on Machine Learning;intelligent Design and Evaluation of Aging Adaptable Public Spaces Based on Deep Learning;performance Optimization and Acceleration of Machine Learning Algorithms in Task Allocation of Mine Maintenance Robots;Application of Deep Learning to Improve the Performance of Automotive Electronic Control Unit (ECU);deep Learning-Based Scene Classification for Remote Sensing images;Improved Swarm Intelligence Optimization Algorithm Based on SL-Relu Activation Function Improvement Strategy and Its Application in Price Forecasting;Automatic Segmentation of Traumatic Penumbra in Rat Brain Based on Improved UNet++;A Brain Tumor Classification Method Based on ResNeXt-SESA Network;A LSTM Algorithm for Coastal City Cultural Scene Value Sustainable Development Forecast Improvement;pattern recognition in Archive analysis Using Data Mining;building Crack Detection Method Based on Convolutional Neural Network.

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3rd World conference on Intelligent and 3D Technologies, WCI3DT 2024

3rd World Conference on Intelligent and 3D Technologies, WCI...

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3rd World conference on Intelligent and 3D Technologies, WCI3DT 2024

ISBN: (纸本)9789819791231

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Research on deep learning-based facial expression recognition and its application in online learning state monitoring 3

Research on deep learning-based facial expression recognitio...

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3rd International conference on Advanced Algorithms and Signal image Processing, AASIP 2023

作者： Wang, Qisheng Yan, Xiaofei Wang, Yanqiu College of Information Science and Engineering Zaozhuang University Zaozhuang277160 China

ISBN: (纸本)9781510668522

This paper aims to research and develop a facial expression recognition algorithm based on convolutional neural networks (CNN) and apply it to a real-Time facial expression recognition system. Firstly, we introduce the Local Binary pattern (LBP) and CNN as commonly used facial recognition algorithms, discussing their characteristics and application areas. We then describe the experimental process in detail, conducting emotion recognition experiments using the FER2013 dataset and performing data preprocessing and augmentation steps. We design a CNN-based model architecture and set the parameters of the model. In the results and analysis section, we compare the performance of our model with other baseline models and discuss possible directions for improvement. Finally, we conclude that our algorithm achieves high accuracy in the experiments and provide prospects for future research and applications. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Local binary pattern

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Collation of Face recognition Techniques: image Registration and Dimension Reduction Approaches 3

Collation of Face Recognition Techniques: Image Registration...

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3rd International conference on Technological Advancements in Computational Sciences, ICTACS 2023

作者： Gupta, Gaurav Goel, Anuj Kumar Chandigarh University Apex Institute of Technology Computer Science Engineering Department Punjab Mohali India Chandigarh University Chandigarh University Electronics and Communication Engineering Department Punjab Mohali India

ISBN: (纸本)9798350342338

Faces must be present in images for intelligent vision-based human computer interaction to work. Since many years ago, face recognition research has been ongoing and significant. This procedure entails facial tracking, expression recognition, and many other things. It is crucial to first register the positions of the photos in this process. However, maintaining such a database is highly challenging because of pose invariance, illumination invariance, shift invariance, scale and noise invariance. The image Registration Algorithm will be used to register all of the unknown photos that are currently in the database. With the use of a reference, this registration technique tries to align a pattern image. This algorithm will produce features that are independent of translation, scaling and rotation. High dimension space, which must be decreased using a dimension reduction algorithm, is the primary challenge in face recognition. This low dimension subspace can be produced using dimension reduction methods like as Linear Discriminant analysis, Principal Component analysis and Locality Preserving Projection. In order to find the needed image from the given database, this study will first minimize the dimensions of every image that is now there. © 2023 IEEE.

关键词： Dimensions Eigen value Laplacian Faces Projection recognition

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Graptolite image Classification Based on Feature Transfer and Mixup Data Enhancement 3

Graptolite Image Classification Based on Feature Transfer an...

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3rd International conference on Computer Vision and pattern analysis, ICCPA 2023

作者： Xu, Xiaoxiao Li, Chaofeng Liu, Honglin Institute of Logistics Science & Engineering Shanghai Maritime University Shanghai China Sinopec Petroleum Exploration and Production Research Institute Beijing China

ISBN: (纸本)9781510667563

Aiming at the problem of special shape of graptolites, insufficient training samples and manual identification of graptolites consumes a lot of time and energy, a new Graptolite image classification based on feature transfer and mixup data enhancement is proposed. First, we expand graptolite dataset by using traditional data enhancement and mixup to generate mixed samples, then use the deep learning model pretrained on the large-scale imageNet dataset to construct a new transfer learning model through feature transfer. Finally, tenfold cross validation method is used to test the recognition accuracy of the model. The experimental results show that the classification accuracy of the proposed method on the graptolite dataset is 88.65%. Compared with the traditional data enhancement method and the pretrained model trained by imageNet directly, the classification accuracy of graptolites is improved by 1.19%, which shows that the method has better recognition effect. © 2023 SPIE.

关键词： image classification

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Analysing the Stage - Parkinson Disease with 'Abhita' Rating Scale 3

Analysing the Stage - Parkinson Disease with 'Abhita' Rating...

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3rd IEEE Delhi Section Flagship conference, DELCON 2024

作者： Banita Zaware, Sarika Dr. D.Y Patil Institute of Management Studies Pune India Aissms Institute of Information Technology Pune India

ISBN: (纸本)9798331518592

Electroencephalogram (EEG) is used to analyse the affected patient's which are suffering from any chronic disease's based on neurology. Study includes 3 methods to analyse the Parkinson Disease (PD) patients i.e. EEG, Questionnaire and hypophonia. Study focuses as to avoid Deep Brain Simulation which nowadays is the only solution for Parkinson disease patient to recover. Study also deals with a vision about Deep Brain simulation (DBS) which is the last solution to Parkinson disease patients to recover with. Study focus on the evaluation of the level at which Parkinson disease patient is suffering which results in the decision that whether DBS is required or not. It will be analysed using 'ABHITA' rating scale already done in 2020. One of the major findings about the study is to overcome patient suffering from PD up to an extent which results in minimizing the anxiety of patient. All the implications clearly detect stage of PD based on symptoms through which patient is suffering. image processing has also been used in this study to detect the severity of disease by using distance evaluation method. This study deals with the analysis of level of effectiveness in human body for which proper prescription will be given to PD patients. It includes a proposed rating scale which has not yet in use and is much helpful for accurate analysis of PD as it considers the symptom along with the motion of the body. Study also deals with questionnaire which help in manual analysis to detect the stage of Parkinson disease as per the proposed rating scale. © 2024 IEEE.

关键词： EEG Hypophonia pattern recognition Proposed Rating Scale Questionnaire

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