Kooperativer Bibliotheksverbund

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Format: 1 online resource (727 pages)

Edition: 1st ed.

ISBN: 9783031663291

Series Statement: Lecture Notes in Networks and Systems Series ; v.1065

Note: Intro -- Preface -- Contents -- FireNet: A Hybrid Deep Learning Approach for Enhanced Fire Detection in Remote Sensing Imagery -- 1 Introduction -- 1.1 Contributions and Paper Organisation -- 2 Method -- 2.1 Dataset Description and Preprocessing -- 2.2 Proposed Model: FireNet -- 3 Results and Discussion -- 3.1 Model Parameters -- 3.2 Simulation Results for Dataset -- 3.3 Comparative Analysis and Discussion -- 4 Conclusion -- 5 Future Work -- References -- Towards Enhanced Virtual Chronic Care: Artificial Intelligence-Human Computer Interaction Integration in Synchronous Virtual Consultations -- 1 Purpose -- 2 Background -- 3 Method -- 4 Results -- 5 Conclusions -- References -- Image Classification Method Considering Overlapping and Correlation Between Probability Density Functions of Features -- 1 Introduction -- 2 Related Research Works -- 3 Proposed Method -- 3.1 Theoretical Background -- 3.2 The Proposed Method -- 4 Experiment -- 4.1 The Data Used -- 4.2 Correlation Matrix -- 4.3 Probability Density Function: PDF in Feature Space -- 4.4 Classification Accuracy -- 5 Conclusion -- 6 Future Research Works -- References -- 3D Reconstruction in Crime Scenes Investigation: Impacts, Benefits, and Limitations -- 1 Introduction -- 2 Methods -- 2.1 Criteria for Selecting Studies -- 2.2 Benefits of 3D Reconstruction Techniques in Crime Investigations Process -- 2.3 Limitations of 3D Reconstruction Techniques in Crime Investigations Process -- 2.4 Implications of 3D Reconstruction Techniques in Crime Investigations Process -- 3 Results and Discussion -- 3.1 Results -- 3.2 Discussion -- 4 Conclusion -- References -- A Hybrid Technique for English to Urdu Machine Translation Using Transfer Learning -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Model Architecture -- 3.2 Word Embedding -- 3.3 Long Short-Term Memory (LSTM). , 3.4 Gated Recurrent Neural Network (GRU) -- 3.5 Encoder-Decoder Model -- 3.6 Convolutional Neural Networks (CNN) -- 4 Experimental Setup -- 4.1 Dataset -- 4.2 LSTM Setting -- 4.3 GRU Setting -- 4.4 CNN Setting -- 4.5 Activation Function -- 5 Results -- 6 Conclusion and Future Work -- References -- A Cross Platform Mobile Application for Indoor Navigation -- 1 Introduction -- 2 Related Works -- 2.1 Comparison of AR Frameworks -- 3 Proposed Pipeline -- 4 Experimental Results -- 5 Conclusions and Future Works -- References -- Empowering Deaf Individuals: Ecuadorian Sign Language Dictionary Integration via Technology -- 1 Introduction -- 2 Literature Review -- 3 Theoretical Framework -- 3.1 Sign Language for the Deaf Community in the Ecuadorian Context -- 3.2 Teaching-Learning Process for Deaf People -- 3.3 Using Technology to Improve Accessibility and Inclusion for Deaf People -- 4 Methodology -- 5 Results and Discussion -- 5.1 Gathering of Functional and Non-functional Requirements -- 5.2 Design and Creation of the Prototype -- 5.3 Correct and Refine the Initial Proposal -- 5.4 Application Deployment -- 6 Conclusions -- References -- New Integrations of Designers' Solutions for Images in the VIS/NIR Spectral Area -- 1 Introduction -- 2 Textile Jacket Design Integration for the VIS/NIR Spectral Range -- 3 Discussion -- 4 Conclusion -- References -- Towards Contextualizing Embodiment of Intelligent Systems -- 1 Purpose -- 2 Background and Significance -- 3 Methods -- 4 Results -- 5 Conclusion -- References -- Video Colorization Based on a Diffusion Model Implementation -- 1 Introduction -- 1.1 Colorization -- 1.2 Contributions -- 2 Diffusion Models -- 3 Related Work -- 4 Methodology -- 4.1 Datasets -- 4.2 Model -- 4.3 Training -- 4.4 Evaluation -- 5 Evaluation Metrics -- 5.1 Peak Signal-to-Noise Ratio -- 5.2 Structural Similarity Index Metric. , 5.3 Fréchet Inception Distance -- 5.4 Color Distribution Consistency -- 6 Experimental Results -- 6.1 Quantitative Evaluation -- 6.2 Qualitative Evaluation -- 7 Conclusions -- References -- Improving Replenishment for Retail: Utilizing Planogram Information -- 1 Introduction -- 2 Related Work -- 2.1 Related Work on Replenishment Systems -- 2.2 Related Work on Detection of Goods -- 2.3 Related Work on Improved Replenishment via Computer Vision -- 3 Our Replenishment Model for Retail Stores -- 3.1 Data -- 3.2 Forecast Models -- 3.3 Replenishment Model -- 4 Improving Replenishment Results with Planogram Information -- 4.1 Adjusting Replenishment Based on Real-Time Product Detection -- 5 Results and Discussion -- 5.1 Product Recognition Results -- 5.2 Our Replenishment Recommendation System -- 5.3 Evaluation of Performance Metrics for Recommended Replenishment Quantities -- 6 Conclusion -- References -- Evaluating and Improving Disparity Maps Without Ground Truth -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Unknown Regions -- 3.2 Occlusion Errors -- 3.3 Fusion Errors -- 3.4 Outlier Detection -- 3.5 Final Score -- 3.6 Correction via RANSAC Plane-Fitting -- 4 Evaluation -- 5 Results -- 6 Limitations and Future Work -- 7 Conclusion -- References -- JSTR: Judgment Improves Scene Text Recognition -- 1 Introduction -- 2 Related Works -- 3 Method -- 3.1 DTrOCR -- 3.2 Proposed Method -- 4 Experiments -- 4.1 Dataset and Evaluation -- 4.2 Implementation Details -- 4.3 Main Result -- 4.4 Detailed Analysis -- 5 Conclusion -- References -- Effectiveness and Acceptance of Conversational Agent-Based Psychotherapy for Depression and Anxiety Treatment: Methodological Literature Review -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Inclusion and Exclusion Criteria -- 3.2 Used Databases and Search Engines -- 3.3 Search Term Definition. , 3.4 Applied Search and Filter Strategy -- 4 Results -- 4.1 Publications on CA-Based Psychotherapy -- 4.2 Analysis of Methodologies and Results -- 4.3 Thematic Clustering and Reoccurring Concepts -- 5 Discussion -- 6 Conclusion -- References -- Common Components Framework (CCF) Enabled Intelligent Data Processing -- 1 Introduction -- 2 Background and Related Work -- 3 Methodology -- 3.1 Data Crawling Layer -- 3.2 Data Ingestion Layer -- 3.3 Feature Extraction Layer -- 3.4 Reporting Layer -- 3.5 Data Quality Management Checks -- 3.6 Graph Analytics -- 3.7 Semantic Search -- 4 Results -- 4.1 Exploring the Data -- 5 Discussion -- 5.1 Reporting -- 6 Conclusion -- References -- Risk Assessment of Data Science Projects: A Literature Review on Risk Identification -- 1 Introduction -- 2 Background -- 3 Research Method -- 4 Results -- 5 Conclusion and Outlook -- Appendix -- References -- Exploring the Integration of Data Science Competencies in Modern Automation Frameworks: Insights for Workforce Empowerment -- 1 Introduction -- 2 Data Science Competencies and AI -- 3 Research Methods -- 4 RESULTS: Automation Frameworks and Their Competencies -- 5 Conclusion -- References -- Enhanced MSME Support Allocation with Integrated K-means and Tukey's Outlier Detection -- 1 Introduction -- 2 Related Works -- 3 Method -- 3.1 Proposed Method -- 3.2 Data Collection -- 3.3 Preprocessing of Data -- 3.4 Outlier Removal -- 3.5 Elbow Method -- 3.6 K-Means Clustering -- 3.7 Validity Test Silhouette Coefficient -- 4 Result and Discussion -- 4.1 Data Collection -- 4.2 Data Preprocessing -- 4.3 Outlier Removal -- 4.4 Elbow Method -- 4.5 K-Means Clustering -- 4.6 Validity Tests of Silhouette Coefficient -- 4.7 Interpretation of Clusters -- 5 Conclusion -- References -- Advancing Mortality Prediction in Ecuador Through Machine Learning Techniques -- 1 Introduction -- 2 Background. , 2.1 Machine Learning -- 2.2 Time Series -- 2.3 Methods and Techniques for Time Series Forecasting -- 2.4 CRISP-DM -- 2.5 Data Science Tools -- 3 Research Approach -- 3.1 Business Understanding -- 3.2 Data Understanding -- 3.3 Data Preparation -- 3.4 Modeling -- 3.5 Evaluation of Models -- 3.6 Deployment -- 4 Discussion -- 5 Conclusions -- References -- Identification of Hidden Inheritance Patterns in a Relational Database Based on Ontologies -- 1 Introduction -- 2 Literature Review -- 3 IHI Model -- 3.1 Proposed Model -- 3.2 Data -- 3.3 Extraction of Data from Relational Databases -- 3.4 Preprocessing the Extracted Data -- 3.5 Algorithm Used in IHI Model -- 3.6 Mathematical Equation and Calculations of the Proposed IHI Model -- 4 Results -- 5 Discussion -- 6 Conclusion and Future Work -- References -- Predictive Analytics and AI-Driven Strategies for Enhanced Cash Flow Forecasting -- 1 Introduction -- 1.1 Research Gap -- 1.2 Purpose of Study -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Comparison -- 3.2 Proposed Architecture -- 3.3 Advantages -- 4 Model and Architecture -- 4.1 Dataset Overview and Pre-processing -- 4.2 Random Forest Model -- 4.3 Custom Neural Network Model -- 4.4 Architecture of Model Forecasting with Reinforcement Learning -- 5 Discussion and Analysis -- 6 Result -- 7 Conclusion -- 8 Future Scope -- References -- Embedding Inclusivity Design into the Data Science Curriculum -- 1 Introduction -- 1.1 Positioning of the Project -- 2 Literature Review: Technology Is not Neutral, Neither Is Data Science -- 2.1 Women Are not Invisible, They Are not Present-Looking to History to Understand Where We Are Now -- 3 The Intervention Project: Embedding Inclusivity Design, Inclusivity Awareness and Inclusivity Leadership into the Curriculum -- 3.1 Methodology and Approach. , 3.2 Curriculum Theme: Critically Thinking About Data, Design and Models.

Additional Edition: Print version: Arai, Kohei Intelligent Systems and Applications Cham : Springer,c2024 ISBN 9783031663284

Language: English