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ویرایش: 1st ed. 2022 نویسندگان: Akram Bennour (editor), Tolga Ensari (editor), Yousri Kessentini (editor), Sean Eom (editor) سری: ISBN (شابک) : 3031082761, 9783031082764 ناشر: Springer سال نشر: 2022 تعداد صفحات: 417 زبان: English فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) حجم فایل: 56 مگابایت
در صورت تبدیل فایل کتاب Intelligent Systems and Pattern Recognition: Second International Conference, ISPR 2022, Hammamet, Tunisia, March 24–26, 2022, Revised Selected Papers ... in Computer and Information Science, 1589) به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب سیستم های هوشمند و تشخیص الگو: دومین کنفرانس بین المللی، ISPR 2022، Hammamet، تونس، 24 تا 26 مارس 2022، مقالات منتخب اصلاح شده ... در علوم کامپیوتر و اطلاعات، 1589) نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
این جلد شامل مقالات منتخبی است که در دومین کنفرانس
بینالمللی سیستمهای هوشمند و تشخیص الگو، ISPR 2022، در همامت،
تونس، در مارس 2022 برگزار شد. به دلیل همهگیری COVID-19،
کنفرانس به صورت آنلاین برگزار شد.
22 مقاله کامل و 10 مقاله کوتاه ارائه شده به طور کامل بررسی و از
بین 91 مقاله ارسالی انتخاب شدند. مقالات در بخش های موضوعی زیر
سازماندهی شده اند: بینایی کامپیوتر. داده کاوی؛ الگو شناسی؛
ماشین و یادگیری عمیق.
This volume constitutes selected papers presented during
the Second International Conference on Intelligent Systems
and Pattern Recognition, ISPR 2022, held in Hammamet, Tunisia,
in March 2022. Due to the COVID-19 pandemic the conference was
held online.
The 22 full papers and 10 short papers presented were
thoroughly reviewed and selected from the 91 submissions. The
papers are organized in the following topical sections:
computer vision; data mining; pattern recognition; machine and
deep learning.
Preface Organization Contents Computer Vision 3D Dense & Scaled Reconstruction Pipeline with Smartphone Acquisition 1 Introduction 2 Related Work 3 3D Reconstruction Pipeline 3.1 Data Capture 3.2 Feature Points Extraction and Correspondence 3.3 Triangulation 3.4 Pose Estimation 3.5 Bundle Adjustment 3.6 Point Cloud Densification 3.7 Mesh Reconstruction 3.8 Texture Mapping 3.9 Scaling 3.10 Model Cleaning 4 Experimental Results and Limitations 4.1 Results 4.2 Limitations 5 Conclusion and Future Work References A Genetic Model for Medical Images Reproduction 1 Introduction 2 Proposed Method 2.1 Principle 2.2 Modeling Steps 3 Results and Discussion 4 Conclusion References A New Study of Needs and Motivations Generated by Virtual Reality Games and Factor Products for Generation Z in Bangkok 1 Introduction 1.1 Desire and Motivations for Playing Virtual Reality Games 1.2 Generation Z in Bangkok 2 Theoretical Framework and Bases for Study Measures 2.1 Uses and Gratifications 2.2 Concepts of Game Types Affecting Gaming Motivation 2.3 Demographic Concepts that Affecting the Gaming Motivation 3 Research Questions 4 Methods 4.1 Prototype 4.2 Survey Design 4.3 Sampling Frame 4.4 Sampling Techniques 4.5 Variables 5 Results 6 Discussion 7 Conclusion and Future Work References A Hybrid Method for Window Detection on High Resolution Facade Images 1 Introduction 2 Related Work 3 Dataset 4 Window Detection Network 5 Refinement of the Windows by Finding the Edges 6 Evaluation 7 Conclusion and Future Work References Neuro-Fuzzy Predictive Approach for Visual Analytics Evaluation of Medical Data 1 Introduction 2 Visual Analytics Evaluation 3 Learning Phase 3.1 Vague Nature of User’s Language 3.2 Fuzzy Intensifier Learning Process 3.3 Known Terms Learning Process 3.4 SOM Creation 3.5 Learning Phase 3.6 Execution Phase 4 Experimentation and Results 4.1 Step 1: Evaluation Questionnaire 4.2 Step 2: Fuzzy Logic Application 5 Conclusion References Improved Cerebral Images Semantic Segmentation Using Advanced Approaches of Deep Learning 1 Introduction 2 Related Work 3 Used Concepts 4 Proposed Approach 4.1 GAN for Generating Synthesis Images of the Minority Data Class 4.2 CycleGAN and UNet for Data Segmentation 5 Experiments and Results 5.1 Dataset 5.2 Augmentation of the Minority Data Class Using GAN 5.3 Data Segmentation Using CycleGAN and U-Net 5.4 Evaluation 5.5 Discussion 6 Conclusion References Self-supervised Learning for COVID-19 Detection from Chest X-ray Images 1 Introduction 2 Related Work 3 Method 3.1 Self-supervised Pre-training Based on Contrastive Learning 3.2 Supervised Fine-Tuning 4 Experiments and Results 4.1 Dataset 4.2 Implementation Details and Evaluation Metric 4.3 Experimental Results 5 Conclusion References Data Mining Deep Learning-Based Segmentation of Connected Components in Arabic Handwritten Documents 1 Introduction 2 Related Works 3 Proposed Use of AR2U-Net 3.1 AR2U-Net Architecture 3.2 Post-processing 4 Experimental Results and Discussion 4.1 The Used Database 4.2 AR2U-Net Training 4.3 Analysis 5 Conclusion and Prospects References Classifying the Human Activities of Sensor Data Using Deep Neural Network 1 Introduction 2 Related Work 3 DNN Structure 3.1 Multilayer Perceptron (MLP) 3.2 MLP Training 4 Methodology 5 Data Set Description 6 Evaluation Metrics 7 Results 8 Conclusion References Exploratory Analysis of Driver and Vehicle Factors Associated with Traffic Accidents in Morocco 1 Introduction 2 Study Methodology 2.1 Exploratory Data Analysis 2.2 Data Preparation 2.3 Descriptive Analysis 2.4 Exploratory Analysis 3 Results and Discussion 4 Conclusion and Perspective References Building a Multilingual Corpus of Tweets Relating to Algerian Higher Education 1 Introduction 2 Data Source 3 Data Collection 4 Data Preprocessing 5 Sentiment Polarity Annotation 6 Conclusion and Future Work References Recursive Feature Elimination Technique for Technical Indicators Selection 1 Introduction 2 Related Work 3 Proposed Method 4 Experimental Results 5 Conclusion References Document-Based Knowledge Discovery with Microservices Architecture 1 Introduction 2 Research Context 2.1 Example Scenario 2.2 Research Questions 3 Background and Related Works 4 Conceptual Approach 4.1 The Microservices Specification 4.2 Data Model 4.3 Communication 5 Evaluation and Assessment 5.1 Implementation 5.2 Evaluation 6 Conclusion References Pattern Recognition Feature Selection for Credit Risk Classification 1 Introduction 2 Related Literature 2.1 Feature Selection 2.2 Feature Selection for Credit Risk Classification 3 Methodology 3.1 Wrapper Algorithm Based on Importance Measure by Permutation 3.2 Logistic Regressiom with LASSO Regularization 3.3 Classification Based Measures 4 Experiments and Results 4.1 Data Pre-processing 4.2 Data Transformation 4.3 Subdivision into ``Training-Test'' Datasets 4.4 Results 4.5 Classification Accuracy 5 Conclusion and Future Work References Parameter Identification and Validation of Multi-innovation Least Squares Lithium Battery for Second-Order Battery Model 1 Introduction 2 Lithium-Ion Battery Model 2.1 Second-Order RC Equivalent Circuit Model 2.2 System Equation of State 2.3 Lithium Battery Identifiable Model 3 Multi-innovation Least Squares 3.1 Experimental Validation and Analysis 3.2 Experimental Platform 3.3 Experimental Procedure 3.4 Experimental Results and Analysis 4 Conclusion References Bat Echolocation Call Detection and Species Recognition by Transformers with Self-attention 1 Introduction 2 Related Work 3 Methods 3.1 Bat Echolocation Call Detection 3.2 Bat Species Recognition 4 Experiments 4.1 Quality Metrics 4.2 Data 4.3 Results 5 Conclusion References Scheduling Techniques for Liver Segmentation: ReduceLRonPlateau vs OneCycleLR 1 Introduction 2 Related Work 3 Methodology 3.1 Dataset and Pre-processing Techniques 3.2 Training Environment and Parameters 3.3 Test Records and Evaluation Metrics 4 Results and Discussion 5 Conclusion and Future Work References An Explainable Predictive Model for the Geolocation of English Tweets 1 Introduction 2 Theoretical Background 2.1 Overview of the DeepGeoloc Model 2.2 Overview of Explainable Artificial Intelligence for Natural Language Processing 3 Methodology 4 Results and Discussion 5 Conclusion References Removing Redundancies in Binary Images 1 Introduction 2 Motivations and Definitions 2.1 Graph-Based Representation 2.2 Image Pyramid 2.3 Combinatorial Pyramid 3 Structurally Redundant Edges 3.1 Selecting the Contraction Kernel 3.2 Redundant Edges 3.3 Removing Redundant Edges in Parallel 4 Memory Consumption 5 Comparisons and Results 6 Conclusion and Future Works References Neural Machine Translation of Low Resource Languages: Application to Transcriptions of Tunisian Dialect 1 Introduction 2 Related Work 3 PARASAR: PARAllel Speech Corpus of ARabic Language 3.1 PARASAR TD Data 3.2 TD-MSA Parallel Corpus 3.3 Data Preprocessing 3.4 TD-MSA Transcriptions Distribution 4 TD-MSA NMT Models 4.1 Seq2seq Models 4.2 Transformer Models 5 Experimental Results and Discussion 5.1 Data Augmentation 5.2 NMT Experiments 5.3 Discussion 6 Conclusion References SPIRAL: SPellIng eRror Parallel Corpus for Arabic Language 1 Introduction 2 Why Building a Corpus is Important in NLP? 3 Related Work 4 The Main Guidelines for Building the SPIRAL Corpus 4.1 Collecting Digital Arabic Words 4.2 Process of Error Generation 5 Results and Discussion 6 Conclusion References Machine and Deep Learning VMs Migration Mechanism for Underloaded Machines in Green Cloud Computing 1 Introduction 2 Related Work 3 VMs Migration Mechanism 3.1 Case 1: An Underloaded Resource 3.2 Case 2: All Resources are Underloaded 3.3 Case 3: Large Number of Underloaded Resources 3.4 Case 4: Resources with Load = Max and Others with Loads < Min 3.5 Case 5: Independent Requests 3.6 Case 6: Dependent Requests 3.7 Case 7: Free Load not Available on the Activated Resources 3.8 Case 8: Overloaded Resources After Migration 3.9 Case 9: Part of Load will be Released 3.10 Case 10: The Resource will not be Underloaded 3.11 Case 11: VMs with Similar Execution Time 4 Comparison Between Related Work and our Mechanism 5 Experimentation 6 Conclusion References TunBERT: Pretrained Contextualized Text Representation for Tunisian Dialect 1 Introduction 2 Related Works 3 TunBERT 3.1 Training Setup 3.2 Pre-training Dataset 4 Evaluation 4.1 Sentiment Analysis 4.2 Tunisian Dialect Identification 4.3 Reading Comprehension Question-Answering 5 Experiments and Discussion 5.1 Tunisian Sentiment Analysis 5.2 Tunisian Dialect Identification 5.3 Reading Comprehension Question-Answering 5.4 Discussion 6 Conclusion References Road Recognition for Autonomous Vehicles Based on Intelligent Tire and SE-CNN 1 Introduction 2 Related Works 3 Intelligent Tire System 4 Methods 4.1 Data Preprocessing 4.2 Squeezing-and-Excitation Block 4.3 Proposed SE-CNN 5 Experiment 6 Results and Discussion 6.1 Implementation Details 6.2 Performance Evaluation and Comparison 6.3 Ablation Study 6.4 Discussion 7 Conclusion References Malicious Packet Classification Based on Neural Network Using Kitsune Features 1 Introduction 2 Related Work 3 Preliminaries 3.1 Problem Setting 3.2 Feature Extraction of Kitsune 4 Methodology 5 Experiment 5.1 CSE-CIC-IDS2018 Dataset 5.2 Labeling and Feature Extraction 5.3 Experiments and Results 6 Discussion 7 Conclusion References An Hybrid Deep Learning Approach for Prediction and Binary Classification of Student’s Stress 1 Introduction 2 Related Works of Stress Prediction 3 Proposed Stress Prediction Framework 3.1 Data Pre-processing 3.2 Autoencoder Element Extraction for Classification 3.3 LSTM Anticipating Architecture 4 Experimental Outcomes 5 Conclusion References A Novel Deep Convolutional Neural Network Architecture for Customer Counting in the Retail Environment 1 Introduction 2 Related Work 3 Proposed Approach 3.1 Modified Residual Block 3.2 Transposed Convolution 3.3 Dilated Spatial Attention Block 3.4 Implementation Details 4 Experimental Corpus and Data Augmentation 5 Experimentation and Discussion 6 Conclusion and Future Work References Transfer Learning for the Classification of Small-Cell and Non-small-Cell Lung Cancer 1 Introduction 2 Lung Cancer 3 Related Works 4 Method 4.1 Dataset 4.2 Data Augmentation 4.3 Proposed Approach 5 Results and Evaluation 6 Conclusion References Attentional Conditional Generative Adversarial Network for Ambient Occlusion Approximation 1 Introduction 2 Related Works 3 Preliminaries 3.1 Adversarial Neural Network 3.2 Attention Mechanism 4 Proposed Method 4.1 Architecture 4.2 Attention Mechanism for Ambient Occlusion 4.3 Loss Function 5 Experiments 5.1 Data Preparation 5.2 Qualitative and Quantitative Evaluation 5.3 Ablation Stady 6 Conclusion and Future Works References An Improvement of CNN Model for Traffic Sign Recognition and Classification 1 Introduction 2 Literature Survey 3 The Proposed Model 3.1 Data Acquisition 3.2 The Model Description 3.3 Data Preprocessing 3.4 Compilation 3.5 Train and Evaluation of the Model 3.6 Evaluation of the Model 4 Discussion 5 Conclusion References Social Media Sentiment Classification for Tunisian Dialect: A Deep Learning Approach 1 Introduction 2 Related Work 2.1 The Lexicon Based Approach 2.2 Machine Learning Based Approach 2.3 The Hybrid Approach 3 Tunisian Dialect Description 3.1 Description 3.2 Difficulties and Challenges 4 Our Proposed Approach 4.1 Dataset Description 4.2 Transliteration from Tunisian Arabizi to Tunisian Arabic 4.3 Dataset Pre-processing 4.4 Dataset Annotation 4.5 Vectorization 4.6 Sentiment Classification with Deep Learning Techniques 5 Experiments and Discussion 5.1 Setting Parameters 5.2 Experiments 6 Conclusion and Perspectives References Soil Moisture Prediction Based on Satellite Data Using a Novel Deep Learning Model 1 Introduction 2 Related Work 3 Methods 3.1 Data 3.2 Model Architecture 3.3 Evaluation Metrics 3.4 Deployment 4 Experiments 4.1 Optimization 4.2 Model Training 4.3 Results and Discussion 5 Conclusion and Further Work References Author Index