Measuring remote photoplethysmography (rPPG), a contactless facial video-based PPG estimation, requires a large amount of labeled data via supervised methods, leading to significantly increased labor and costs. Existi...
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Multi-modality (MM) semi-supervised learning (SSL) based medical image segmentation has recently gained increasing attention due to its ability to utilize MM data and low dependency on labeled images. However, current...
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This event aims to enable synergy between these areas and provide a leading forum for researchers, developers, practitioners, and professionals from public sectors and industries to meet and share the latest solutions...
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ISBN:
(数字)9783031160356
ISBN:
(纸本)9783031160349
This event aims to enable synergy between these areas and provide a leading forum for researchers, developers, practitioners, and professionals from public sectors and industries to meet and share the latest solutions and ideas in solving cutting-edge problems in the modern information society and the economy. The conference focuses on specific challenges in deep (and machine) learning, big data and blockchain. Some of the key topics of interest include (but are not limited to):;Blockchain security and trust
The proceedings contain 44 papers. The special focus in this conference is on machinelearning and Big data Analytics. The topics include: Bilingual Documents Text Lines Extraction Using Conditional GANs;Performance C...
ISBN:
(纸本)9783031151743
The proceedings contain 44 papers. The special focus in this conference is on machinelearning and Big data Analytics. The topics include: Bilingual Documents Text Lines Extraction Using Conditional GANs;Performance Comparison of YOLO Variants for Object Detection in Drone-Based Imagery;a Microservice Architecture with Load Balancing Mechanism in Cloud Environment;an IoT Application for Detection and Monitoring of Manhole;resource Allocation in 5G and Beyond Edge-Slice Networking Using Deep Reinforcement learning;preface;a Comprehensive Analysis on Mobile Edge Computing: Joint Offloading and Resource Allocation Perspective;the Important Influencing Factors in machine Translation;damaged Units Return Investigation in Printer-Producing Industry Utilizing Big data;colorization of Grayscale Images: An Overview;evolutionary Approaches Toward Traditional to Deep learning-Based Chatbot;analysis of machinelearning Algorithms for Detection of Cyberbullying on Social Networks;sentiment Analysis of Political Tweets for Israel Using machinelearning;a Novel Approach for Real-Time Vehicle Re-identification Using Content-Based Image Retrieval with Relevance Feedback;Extractive and Abstractive Text Summarization Model Fine-Tuned Based on BERTSUM and Bio-BERT on COVID-19 Open Research Articles;RevCode for NLP in Indian Languages;Application for Mood Detection of Students Using TensorFlow and Electron JS;finding Significant Project Issues with machinelearning;Using CNN Technique and Webcam to Identify Face Mask Violation;a Review on Internet of Things-Based Cloud Architecture and Its Application;prediction of Maneuvering Status for Aerial Vehicles Using Supervised learning Methods;HRescue: A Modern ML Approach for Employee Attrition Prediction;using machinelearning to Detect Botnets in Network Traffic.
In scientific research, charts are usually the primary method for visually representing data. However, the accessibility of charts remains a significant concern. In an effort to improve chart understanding pipelines, ...
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Super-resolution (SR) is the task of reconstructing visually natural high-resolution (HR) images from low-resolution (LR) images. This field has made significant advancements with the development of deep learning, and...
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The proceedings contain 20 papers. The special focus in this conference is on Applied machinelearning and data Analytics. The topics include: RU-Net: A Novel Approach for Gastro-Intestinal Tract Image Segmentati...
ISBN:
(纸本)9783031342219
The proceedings contain 20 papers. The special focus in this conference is on Applied machinelearning and data Analytics. The topics include: RU-Net: A Novel Approach for Gastro-Intestinal Tract Image Segmentation Using Convolutional Neural Network;a Credit Card Fraud Detection Model Using machinelearning Methods with a Hybrid of Undersampling and Oversampling for Handling Imbalanced datasets for High Scores;Implementation of YOLOv7 for Pest Detection;online Grocery Shopping: - Key Factors to Understand Shopping Behavior from data Analytics Perspective;a Novel Approach: Semantic Web Enabled Subject Searching for Union Catalogue;how People in South America is Facing Monkeypox Outbreak?;multilevel Classification of Satellite Images Using Pretrained AlexNet Architecture;handwriting Recognition for Predicting Gender and Handedness Using Deep learning;retrieval of Weighted Lexicons Based on Supervised learning Method;univariate Feature Fitness Measures for Classification Problems: An Empirical Assessment;performance Evaluation of Smart Flower Optimization Algorithm Over Industrial Non-convex Constrained Optimization Problems;securing Advanced Metering Infrastructure Using Blockchain for Effective Energy Trading;keratoconus Classification Using Feature Selection and machinelearning Approach;Semantic Segmentation of the Lung to Examine the Effect of COVID-19 Using UNET Model;SMDKGG: A Socially Aware Metadata Driven Knowledge Graph Generation for Disaster Tweets;Brain MRI Image Classification Using Deep learning;a Real-Time Face Recognition Attendance Using machinelearning;towards Abalone Differentiation Through machinelearning.
The medical knowledge graph (KG) constructed from electronic health records (EHR) offers a comprehensive understanding of patients as it facilitates interconnections among medical codes. While KG has been proven to im...
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Graph learning is the fundamental task of estimating unknown graph connectivity from available data. Typical approaches assume that not only is all information available simultaneously but also that all nodes can be o...
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Federated learning (FL) offers a privacy-preserving solution by enabling multiple clients to train a shared model collaboratively without centralizing data. However, the decentralized nature of FL presents challenges,...
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