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Artificial Intelligence : Proceedings of AITA 2023, Volume 2
| Artificial Intelligence : Proceedings of AITA 2023, Volume 2 |
| Autore | Sharma Harish |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2024 |
| Descrizione fisica | 1 online resource (531 pages) |
| Altri autori (Persone) |
ChakravortyAntorweep
HussainShahid KumariRajani |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 981-9984-79-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- Spam Email Image Detection Using Convolution Neural Network and Convolutional Block Attention Module -- 1 Introduction -- 2 Related Works -- 3 Convolution Neural Network -- 4 Convolutional Block Attention Model -- 5 Experimental Result -- 5.1 Dataset -- 5.2 Evaluation Metrics -- 5.3 Discussion -- 6 Conclusion -- References -- Identifying Fake Twitter Trends with Deep Learning -- 1 Introduction -- 2 Related Work -- 2.1 PolitiFact Dataset -- 2.2 PHEME Dataset -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Modeling -- 3.4 Experiments -- 4 Results and Analysis -- 5 Conclusion and Future Work -- References -- An Intelligent Agent Framework for Resilient Deployment in the Internet of Things Environment -- 1 Introduction -- 2 Intelligent Agent Framework -- 3 Proposed Deployment Algorithm -- 4 Results and Discussion -- 5 Conclusions -- References -- The Impact of Financial Ratios and Pandemic on Firm Performance: An Indian Economic Study -- 1 Introduction -- 2 Literature Review and Hypotheses Development -- 2.1 Debt and Firm Performance -- 2.2 Working Capital and Firm Performance -- 2.3 Financial Autonomy and Firm Performance -- 2.4 Quick Ratio and Firm Performance -- 3 Sample -- 4 Research Methodology -- 5 Results -- 5.1 Trend Analysis -- 5.2 Regression Results -- 6 Conclusion -- References -- An Enhanced BERT Model for Depression Detection on Social Media Posts -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Enhanced BERT Classical -- 4 Results and Discussion -- 4.1 Dataset -- 4.2 Comparison with the Existing System -- 5 Conclusion -- References -- Quality Prediction of a Stack Overflow Question Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Techniques -- 3.1 Naïve Bayes (NB) -- 3.2 Support Vector Classifier (SVC).
3.3 Decision Tree (DT) -- 3.4 Logistic Regression (LR) -- 3.5 K-Nearest Neighbors (KNN) -- 3.6 Random Forest (RF) -- 3.7 Natural Language Processing (NLP) -- 3.8 Bag of Words (BoW) -- 3.9 Word Cloud Analysis -- 4 Proposed Methodology and Implementation -- 4.1 Importing Libraries -- 4.2 Description of Dataset -- 4.3 Cleaning Textual Data -- 4.4 Tokenization, Lemmatization, and PoS Tagging -- 4.5 Lexicon-Based Sentiment Analysis -- 4.6 Word Embedding -- 4.7 Splitting the Dataset -- 4.8 Model Building and Performance Evaluation -- 5 Experimental Results and Analysis -- 6 Conclusion -- References -- Decision-Making Framework for Supplier Selection Using an Integrated Approach of Dempster-Shafer Theory and Maximum Entropy Principle -- 1 Introduction -- 2 Preliminaries -- 2.1 Dempster-Shafer Evidence Theory -- 2.2 Cobb-Douglas Utility Function -- 2.3 Maximum Entropy Method -- 3 Proposed Methodology -- 3.1 Evaluate Criteria Weights -- 3.2 Evaluate Alternative Ranking -- 4 Numerical Example -- 4.1 Problem Description -- 4.2 Evaluation of Criteria Weights -- 4.3 Ranking of Alternatives -- 5 Comparative Analysis and Discussions -- 5.1 Comparative Analysis of Weight Determination Method -- 5.2 Comparative Analysis of Ranking Method -- 6 Sensitivity Analysis -- 7 Conclusions -- References -- Improved Accuracy of Robotic Arm Using Virtual Environment -- 1 Introduction -- 2 Literature Review and Related Work -- 3 Proposed Method, Tools, and Techniques Used -- 3.1 Forward Kinematics -- 3.2 Inverse Kinematics -- 3.3 Technique -- 4 Methodology -- 4.1 Design of the Robotic Arm -- 4.2 Addition of Revolute Joints -- 4.3 Importing the Model to MATLAB -- 4.4 Defining the Robot Environment -- 4.5 Defining the Desired Trajectory -- 4.6 Working of Inverse Kinematic Block -- 4.7 Working of Forward Kinematic Block -- 4.8 Data Collection and Analysis -- 5 Result -- 6 Conclusion. References -- Human Activity Recognition a Comparison Between Residual Neural Network and Recurrent Neural Network -- 1 Introduction -- 2 HAR Using ResNet50 -- 3 HAR Using RNN -- 4 Conclusion -- References -- Using AI Planning to Automate Cloud Infrastructure -- 1 Introduction -- 2 Related Work -- 2.1 Cloud Infrastructure -- 2.2 Prototype Model -- 3 Problem Formulation -- 4 Proposed Solution -- 5 Testing and Result Evaluations -- 5.1 Test Case 1: Empty Environment -- 5.2 Test Case 2: No Application Module -- 5.3 Test Case 3: Neither the Database nor the Application Module -- 5.4 Test Case 4: Inconsistent Database -- 5.5 Test Case 5: Application Module in Unhealthy Status -- 5.6 Test Case 6: Application Out of Capacity -- 6 Conclusions and Future Scope -- References -- Using Historical Trip Information to Determine the Waiting Time Required for Taxi Services -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 4 Proposed Solution: Design and Implementation -- 5 Results' Evaluation -- 6 Conclusions and Future Scope -- References -- The Impact of Cesarean Section Trends and Associated Complications in the Current World: A Comprehensive Analysis Using Machine Learning Techniques -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Decision Tree (DT) -- 3.2 Random Forest (RF) -- 3.3 K-Nearest Neighbour (KNN) -- 3.4 Support Vector Machine (SVM) -- 3.5 AdaBoost (AB) -- 4 Results -- 4.1 Decision Tree -- 4.2 Random Forest -- 4.3 K-Nearest Neighbour -- 4.4 Support Vector Machine -- 4.5 AdaBoost -- 5 Conclusion -- References -- Novel Hybrid Methods for Journal Article Summarization Combining Graph Method and Rough Set TFIDF Method with Pegasus Model -- 1 Introduction -- 2 Related Works and Summarization Datasets -- 3 Motivation and Challenges in Article Summarization -- 4 Methodology -- 4.1 Extractive Summarization Methods. 4.2 Abstractive Summarization Methods -- 4.3 Hybrid Summarization Methods -- 5 Results and Discussion -- 5.1 Rouge Score for Word Overlap over Annotated Summary -- 5.2 BERT Score for Similarity Score -- 6 Conclusion and Future Scope -- References -- Differential Evolution Wrapper-Based Feature Selection Method for Stroke Prediction -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 Proposed System -- 4 Result Analysis -- 5 Discussion -- 6 Conclusion -- References -- Parkinson's Disease Identification from Speech Signals Using Machine Learning Models -- 1 Introduction -- 2 Literature Review -- 2.1 Machine Learning and Neural Network Techniques for PD Classification -- 2.2 Hybrid Models with Machine Learning Techniques and Neural Network -- 3 System Architecture -- 3.1 Dataset Details -- 3.2 Proposed Approach -- 4 Results and Discussions -- 4.1 Performance Matrices -- 4.2 Experimental Analysis -- 5 Conclusion -- References -- Performance Analysis of Deep CNN, YOLO, and LeNet for Handwritten Digit Classification -- 1 Introduction -- 2 Literature Review -- 3 Objective, Motivation and Challenges -- 4 Methodology -- 4.1 Dataset Description -- 5 Implementation -- 5.1 Convolution Neural Network -- 5.2 Convolutional Layer -- 5.3 Pooling Layer -- 5.4 Fully Connected Layer -- 5.5 Creating a CNN Model -- 5.6 You Only Look Once (YOLO) -- 5.7 LeNet -- 6 Result and Discussion -- 7 Conclusions -- References -- Data-Driven Decision Support Systems in E-Governance: Leveraging AI for Policymaking -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Research Objectives -- 3.2 Research Methodology -- 3.3 Proposed Contributions -- 4 Experimental Results -- 4.1 Accuracy -- 4.2 Precision -- 4.3 Recall (Sensitivity) -- 4.4 F1 Score -- 4.5 Mean Absolute Error (MAE) -- 4.6 Root Mean Square Error (RMSE) -- 5 Conclusions. References -- The Infrastructure Development of Contemporary Medical Devices Based on Internet of Things Technology -- 1 Introduction -- 2 IoT Infrastructure in Health Care -- 3 IoT Wireless Standards -- 4 IoT Network Architecture -- 4.1 Availability -- 4.2 Scalability -- 4.3 Network Performance -- 4.4 Manageability -- 4.5 Affordability -- 4.6 Adaptability -- 4.7 Usability -- 5 Cloud Computing in IoT -- 6 Contemporary Applications of IoT -- 6.1 Smart IoT Sensors -- 6.2 Smart Pill Containers -- 6.3 Smart Hospital Beds -- 6.4 Temperature Sensors -- 6.5 Wearable Devices -- 6.6 Future of IoT Medical Instruments -- 7 Conclusions -- References -- Business Intelligence System Adoption Project in the Area of Investments in Financial Assets -- 1 Introduction -- 2 Understanding the Significance and Functionality of Business Intelligence Systems -- 3 Review of Business Intelligence Literature -- 4 Traditional Information Systems on Investments in Financial Assets -- 5 Business Intelligence for Investments in Financial Assets-The Case of an IT Industry Organization -- 5.1 Preliminary Information -- 5.2 Original Business Intelligence System Employed in the Organization -- 6 Conclusions -- References -- Feature Selection Techniques to Enhance Prediction of Clinical Appointment No-Shows Using Neural Network -- 1 Introduction -- 2 Related Studies -- 3 Model Development -- 4 Analysis of Performance Measures -- 5 Conclusion -- References -- A Simple Recommendation Model Using the Item's Global Popularity and Frequency-Based User Preference -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Formalizations -- 3.2 Model -- 4 Experimental Results -- 5 Conclusion -- References -- An Early Detection of Autism Spectrum Disorder Using PDNN and ABIDE I& -- II Dataset -- 1 Introduction. 2 The Next Step in Comprehending the Brain and Psychiatric Diseases is Machine Learning, Deep Learning, and Predicting Disease States. |
| Record Nr. | UNINA-9910799221503321 |
Sharma Harish
|
||
| Singapore : , : Springer Singapore Pte. Limited, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Intelligence : Proceedings of AITA 2023, Volume 1
| Artificial Intelligence : Proceedings of AITA 2023, Volume 1 |
| Autore | Sharma Harish |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (495 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
ChakravortyAntorweep
HussainShahid KumariRajani |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 981-9984-76-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- Control Techniques for Vision-Based Autonomous Vehicles for Agricultural Applications: A Meta-analytic Review -- 1 Introduction -- 2 State-of-The Art Studies -- 2.1 Target Detection in Autonomous Vehicle System -- 2.2 Vision-Based System -- 3 Mathematical Modeling of Autonomous System -- 4 Conclusion -- References -- Co-GA: A Bio-inspired Semi-supervised Framework for Fake News Detection on Scarcely Labeled Data -- 1 Introduction -- 2 Related Work -- 2.1 Supervised Fake News Detection Using Linguistic Content -- 2.2 Semi-supervised Fake News Detection Using Linguistic Content -- 2.3 Metaheuristics-Based Approaches for Feature Selection -- 2.4 Metaheuristics-Based Fake News Detection -- 3 Data -- 4 Proposed Methodology -- 4.1 Pre-processing -- 4.2 Feature Extraction -- 4.3 Bio-inspired Feature Selection -- 4.4 Multi-view Co-training Model -- 5 Results and Analysis -- 6 Future Research Directions -- 7 Conclusion -- References -- Kernel Methods for Conformal Prediction to Detect Botnets -- 1 Introduction -- 2 Related Works -- 2.1 Signature-Based and Heuristic-Based Botnet Detection -- 2.2 Machine Learning for Botnet Detection -- 2.3 Kernel Methods -- 2.4 Conformal Prediction -- 2.5 Deep Learning and Graph-Based Approaches -- 2.6 Challenges and Limitations -- 2.7 Motivation for the Proposed Approach -- 2.8 Emerging Trends and Research Directions -- 3 Methodology -- 3.1 Kernel Methods -- 3.2 Conformal Prediction -- 3.3 Proposed Approach: Kernel Methods for Conformal Prediction -- 3.4 Evaluation Metrics -- 3.5 Experimental Setup -- 4 Results -- 4.1 Dataset Description -- 4.2 Experimental Setup -- 4.3 Experimental Results -- 4.4 Analysis of Results -- 5 Conclusion -- References -- Biogas Generation from Animal Waste: A Case Study of Village Wazirpur -- 1 Introduction.
2 Biogas Production from Animal Waste -- 2.1 Factors Affecting Biogas Production -- 2.2 Sensors for Determining the Parameters Affecting Biogas Production -- 3 Area Under Study -- 4 Cost Analysis and Electricity Production -- 5 Conclusion -- References -- Volume of Imbalance Container Prediction using Kalman Filter and Long Short-Term Memory -- 1 Introduction -- 2 Problem Statement -- 3 Research Questions -- 4 KALSTM: A Hybrid Model -- 5 Results and Limitations -- 6 Conclusion -- References -- Modelling Stock Prices Prediction with Long Short-Term Memory (LSTM): A Black Box Approach -- 1 Introduction -- 2 Methodology Based on LSTM -- 3 Description of Datasets -- 4 Results and Discussions -- 5 Conclusion and Future Work -- References -- Agricultural Crop Yield Prediction for Indian Farmers Using Machine Learning -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Dataset -- 3.2 Methodology -- 4 Architecture -- 5 Result Analysis -- 6 Conclusion -- References -- Application of Artificial Intelligence on Camera-Based Human Pose Prediction for Yoga: A Methodological Study -- 1 Introduction -- 1.1 Scope -- 1.2 Challenges -- 1.3 Impact of Yoga [1] -- 2 Literature Review -- 3 Methodology -- 3.1 Research Process -- 3.2 Key Point Detection Methods -- 3.3 Implementation Methodology [12, 13] -- 4 Datasets and Metrics -- 5 Results -- 6 Conclusion -- 7 Future Potential Development -- References -- Predicting of Credit Risk Using Machine Learning Algorithms -- 1 Introduction -- 2 Review of Literature -- 2.1 Machine Learning Algorithms -- 2.2 Development of Credit Risk Model -- 3 Data and Methodology -- 3.1 Data -- 3.2 Variables -- 3.3 Machine Learning Models and Evaluation Parameters -- 3.4 Evaluation Parameters -- 3.5 Methodology -- 4 Empirical Findings -- 5 Conclusions and Implications -- References -- Study of Various Text Summarization Methods. 1 Introduction -- 2 Literature Review -- 3 Overview of Proposed Model -- 3.1 Proposed Methodology -- 3.2 Design of Model Architecture -- 3.3 Model Evaluation -- 4 Results -- 5 Conclusion -- References -- Investigations on Deep Learning Pre-trained Model VGG-19 Using Transfer Learning for Remote Sensing Image Classification on Benchmark Datasets -- 1 Introduction -- 2 Literature Review -- 3 Comparison of Performance Metrics of Machine Learning Methods on the PatterNet Dataset -- 4 Utilizing Pre-trained Models for Transfer Learning -- 5 Transfer Learning with Pre-trained Models Based on the Baseline ImageNet Dataset -- 6 Overview of VGG-19 -- 7 Enabling Efficient Feature Reuse and Information Flow in Deep Neural Networks for Superior Performance -- 8 Deep Learning Surpassing Traditional Machine Learning Techniques -- 9 Setting Up Experiments: Feature Extraction and Classification for Remote Sensing Images with a Pre-trained VGG-19 Model -- 9.1 Dataset Description -- 9.2 Assessment Metrics Utilized for Model Evaluation in Image Classification and Retrieval -- 9.3 Research Findings: Investigating Test Accuracy and Test Loss Scores on Benchmark Datasets Using VGG-19 Pre-trained Model -- 10 Summarizing the Feature Extraction with Transfer Learning Approach in Deep Learning -- References -- Complexity Analysis of Legal Documents -- 1 Introduction -- 2 Related Works -- 2.1 NER for Indian Legal Documents -- 2.2 Information Extraction -- 2.3 Summarising in Legal Domain -- 2.4 Complexity of Legal Documents -- 3 Methodology -- 3.1 Proposed Model -- 3.2 Analysis of Complexity -- 4 Result Analysis -- 5 Conclusion and Future Works -- References -- Predicting Virality of Tweets Using ML Algorithms and Analyzing Key Determinants of Viral Tweets -- 1 Introduction -- 2 Theoretical Background and Related Work -- 3 Methodology -- 4 Results and Discussion. 5 Conclusion, Limitations, and Future Scope -- References -- Review of Classification and Detection for Insects/Pests Using Machine Learning and Deep Learning Approach -- 1 Introduction -- 1.1 Pictorial Representation of Classification and Detection of Pests and Comparison Between ML and DL -- 2 Material -- 2.1 Dataset Collection -- 3 Literature Work -- 3.1 Review of Different Machine Learning and Deep Learning Techniques for the Classification of Pests -- 4 Conclusion -- References -- Sentiment Analysis of Product Reviews Using Deep Learning and Transformer Models: A Comparative Study -- 1 Introduction -- 2 Literature Review -- 3 Sentiment Analysis -- 3.1 Sentiment Analysis Based on Machine Learning -- 3.2 Sentiment Analysis Based on Deep Learning -- 3.3 Sentiment Analysis Based on Transformer-Based Models -- 4 Implementation -- 4.1 Dataset -- 4.2 Data Pre-processing -- 4.3 Classification Models -- 5 Results and Discussions -- 5.1 Hyper Parameters Used -- 5.2 Performance Evaluation -- 6 Conclusion -- References -- Effect of Variation in Pause Times Over MANET Routing Protocols -- 1 Introduction -- 2 MANET Routing Protocols and Literature Review -- 3 Environment Setup -- 4 Performance Metrics -- 5 Conclusions and Future Scope -- References -- DDCMR2: A Deep Detection and Classification Model with Resizing and Rescaling for Plant Disease -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology and Implementation -- 3.1 Data Collection -- 3.2 Data Cleaning, Preprocessing, and Visualization -- 3.3 Cache, Shuffle, and Prefetch -- 3.4 Model Building -- 3.5 Hyperparameters Choice -- 4 Results and Discussion -- 5 Conclusion and Future Scope -- References -- Leveraging Natural Language Queries for Effective Video Analysis -- 1 Introduction -- 2 Related Work -- 3 Methodology and Models -- 3.1 Uni-Modal Encoder -- 3.2 Cross-Modal Encoder. 3.3 Query Generator -- 3.4 Query Decoder -- 4 Experimental Analysis and Outcomes -- 5 Conclusion -- References -- An Experimental Study to Perform Bioinformatics Based on Heart Disease Case Study Using Supervised Machine Learning -- 1 Introduction -- 2 Preliminaries -- 2.1 Machine Learning -- 2.2 Logistic Regression -- 2.3 Decision Tree -- 2.4 Support Vector Machine -- 3 Experimentation -- 3.1 Data Provenance -- 3.2 Flow Diagram of This Study -- 3.3 Correlation Matrix -- 3.4 Logistic Regression -- 3.5 Support Vector Machine (SVM) -- 3.6 Decision Tree -- 4 Results and Analysis -- 5 Conclusion -- References -- Empirical Analysis of Denoising Algorithms for CCTV Face Images -- 1 Introduction -- 2 Related Work -- 3 BM3D (Block-Matching and 3D Filtering) -- 3.1 Collaborative Filtering: It Takes Four Steps -- 3.2 Aggregation -- 3.3 Wiener Filtering Step -- 4 KSVD (k-Singular Value Decomposition) -- 5 WNNM (Weighted Nuclear Norm Minimization) -- 6 Results and Discussion -- 7 Conclusion -- References -- Content-Based Tagging and Recommendation System for Tamil Songs Based on Text and Audio Input -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Music Segmentation -- 3.2 Instrument Recognition -- 3.3 Lyric Collection and Translation -- 3.4 Lyric Tagging -- 3.5 Audio Prompt -- 3.6 Similarity-Based Retrieval -- 4 Datasets -- 4.1 MUSDB18 Dataset -- 4.2 Tamil Songs -- 4.3 AudioSet -- 5 Outcomes -- 5.1 Metrics for Evaluation -- 5.2 Summary of Metrics -- 6 Conclusions and Future Work -- References -- Multimodal Face and Ear Recognition Using Feature Level and Score Level Fusion Approach -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Preprocessing -- 3.2 Feature Extraction (BSIF) -- 3.3 Feature Level Fusion -- 3.4 Score Level Fusion -- 4 Experimental Results and Discussion -- 4.1 GTAV Dataset. 4.2 FEI Face Database. |
| Record Nr. | UNINA-9910841868303321 |
|
Sharma Harish
|
||
| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Communication and Intelligent Systems : Proceedings of ICCIS 2023, Volume 2
| Communication and Intelligent Systems : Proceedings of ICCIS 2023, Volume 2 |
| Autore | Sharma Harish |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2024 |
| Descrizione fisica | 1 online resource (462 pages) |
| Altri autori (Persone) |
ShrivastavaVivek
TripathiAshish Kumar WangLipo |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 981-9720-79-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- Multilingual Speech Recognition: An In-Depth Review of Applications, Challenges, and Future Directions -- 1 Introduction -- 1.1 Automatic Speech Recognition -- 1.2 Multilingual Speech-to-Text Conversion -- 2 Techniques and Approaches -- 2.1 Acoustic Model Sharing -- 2.2 Code-Switching Models -- 2.3 Language-Specific Models -- 3 Feature Extraction Techniques and Toolkit/Software -- 4 Applications of Multilingual Speech Recognition -- 5 Challenges and Limitations -- 6 Future Directions -- 7 Conclusions -- References -- Performance Evaluation of Job Shop Scheduling Problem Using Proposed Hybrid of Black Hole and Firefly Algorithms -- 1 Introduction -- 1.1 Proposed Approaches for Solving Scheduling Problem -- 2 Related Work -- 3 Job Shop Scheduling Problem -- 4 Proposed Methodology -- 4.1 Firefly Algorithm -- 4.2 Black Hole Algorithm -- 5 Hybrid Approach -- 6 Computational Results -- 6.1 Discussion on the Obtained Results -- 7 Conclusion and Future Works -- References -- Machine Learning and Healthcare: A Comprehensive Study -- 1 Introduction -- 2 Machine Learning in Healthcare -- 2.1 Random Forest -- 2.2 Gradient Boosting -- 2.3 Convolutional Neural Networks (CNNs) -- 2.4 Recurrent Neural Networks (RNNs) -- 3 Application of ML in Healthcare -- 3.1 Cancer Detection -- 3.2 Diabetes Detection -- 3.3 Heart Disease Detection -- 3.4 Autism Spectrum Disorder Detection -- 3.5 Parkinson's Disease Detection -- 4 Assessment of Model Performance -- 4.1 Accuracy -- 4.2 Precision -- 4.3 F1-Score -- 4.4 Specificity -- 4.5 Mean Squared Error (MSE) -- 5 Challenges and Limitations -- 6 Discussion -- 6.1 Research Gaps -- 6.2 Findings -- 7 Conclusion -- References -- Evolutionary Algorithms for Fibers Upgrade Sequence Problem on MB-EONs -- 1 Introduction -- 1.1 Studied Problem -- 2 Related Works -- 2.1 MB-EONs.
2.2 MB-EON Upgrade Problem -- 3 Problem Formulation -- 3.1 Notations -- 3.2 Assumptions -- 3.3 Concept of Network Upgrade -- 3.4 Objective Function -- 4 Proposed Algorithms -- 4.1 Genetic Algorithm -- 4.2 Simulated Annealing -- 5 Simulation Results -- 6 Conclusions -- References -- Exploring the Potential of Deep Learning Algorithms in Medical Image Processing: A Comprehensive Analysis -- 1 Introduction -- 2 Literature Review -- 2.1 Deep Learning Techniques in MIA -- 2.2 Applications of DL in Medical Imaging -- 2.3 Emerging Trends and Future Side -- 3 Research Challenges -- 4 Methodology for Literature Review and Data Collection -- 4.1 Literature Collection and Selection -- 4.2 Data Extraction and Categorization -- 5 DL Applications in MIP -- 6 Discussion -- 7 Applications and Use Cases -- 7.1 COVID-19 Detection -- 8 Future Scope -- 9 Conclusion -- References -- Comparative Analysis of Image Enhancement Techniques: A Study on Combined and Individual Approaches -- 1 Introduction -- 2 Literature Survey -- 2.1 Related Work -- 3 Overview of Methods -- 4 Proposed Methodology -- 5 Basis of Analysis -- 6 Comparative Analysis -- 7 Conclusion -- References -- Smishing: A SMS Phishing Detection Using Various Machine Learning Algorithms -- 1 Introduction -- 2 Motivation -- 3 Related Work -- 4 Proposed Work -- 5 Implementation and Result Analysis -- 6 Conclusion and Future Work -- References -- Convolution Neural Network (CNN)-Based Live Pig Weight Estimation in Controlled Imaging Platform -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Process Flow -- 3.2 Model Architecture -- 3.3 Experimental Details -- 4 Results and Discussion -- 5 Conclusion -- References -- A Novel Image Encryption Technique Based on DNA Theory and Chaotic Maps -- 1 Introduction -- 2 Background -- 2.1 Chaos Theory -- 2.2 DNA Encoding Technique -- 3 Proposed Method. 3.1 Encryption -- 3.2 Decryption -- 4 Results and Discussion -- 4.1 Information Entropy (Ien) -- 4.2 Histogram Analysis -- 4.3 Correlation Analysis -- 5 Conclusions -- References -- An Empirical Study on Comparison of Machine Learning Algorithms for Eye-State Classification Using EEG Data -- 1 Introduction -- 2 Literature Survey -- 3 Proposed System -- 4 Experimental Results -- 4.1 Dataset Description -- 4.2 Data Preprocessing -- 4.3 Algorithm Implementation -- 5 Conclusion -- References -- Decoding the UK's Stance on AI: A Deep Dive into Sentiment and Topics in Regulations -- 1 Introduction -- 2 Literature Studies -- 3 Data and Methodology -- 4 Results -- 5 Discussions and Conclusions -- References -- Latest Trends on Satellite Image Segmentation -- 1 Introduction -- 1.1 Satellite Imaging and Remote Sensing -- 1.2 Spectral Bands -- 1.3 Multispectral and Hyperspectral Imaging -- 1.4 Datasets: Challenges and Opportunities -- 2 Relevant Studies in Image Segmentation -- 3 Techniques Used in Satellite Image Segmentation -- 3.1 Transductive SVM -- 3.2 U-Net -- 3.3 Random Walker -- 4 Future Scope in Satellite Imaging Segmentation -- 5 Conclusion -- References -- Landmark Detection Using Convolutional Neural Network: A Review -- 1 Introduction -- 2 Review Process -- 2.1 Data Collection and Preparation -- 2.2 CNN's Network Architecture -- 2.3 Training the CNN Dataset -- 2.4 Landmark Localization -- 2.5 Post-preprocessing -- 3 Background Study -- 3.1 Early Approaches to Landmark Detection -- 3.2 CNN-Based Landmark Detection -- 3.3 Popular CNN Architectures -- 3.4 Data Augmentation and Preprocessing -- 3.5 Loss Functions and Training Strategies -- 3.6 Benchmark Datasets -- 3.7 Domain-Specific Applications -- 4 Literature Review -- 4.1 Landmark Detection Method -- 4.2 CNN Algorithms -- 4.3 Optimization Techniques -- 4.4 Applications -- 5 Result Analysis. 5.1 Periodic 3D CNN for Mitral Annulus Segmentation and Anatomical Orientation Detection in TEE Images [8] -- 5.2 Deep Convolutional Neural Networks for Sagittal Cervical Spine Landmark Point Detection in X-Ray Images [9] -- References -- An Efficient Illumination Invariant Tiger Detection Framework for Wildlife Surveillance -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 EnlightenGAN -- 3.2 YOLOv8 -- 4 Results and Discussion -- 5 Conclusion -- References -- An Innovative Frequency-Limited Interval Gramians-Based Model Order Reduction Method Using Singular Value Decomposition -- 1 Introduction -- 1.1 Literature Review -- 1.2 Paper Organization and Contribution -- 2 Methodology -- 2.1 Algorithm -- 3 Numerical Analysis and Simulation -- 4 Conclusion -- References -- Contrast Enhancement of Medical Images Using Otsu's Double Threshold -- 1 Introduction -- 2 State of the Art -- 3 Methodology -- 3.1 Segmentation Using Otsu's Double Threshold Method -- 3.2 Weighted Distribution Model -- 3.3 Histogram Equalization -- 3.4 Adaptive Gamma Correction Process -- 3.5 Homomorphic Filtering -- 4 Experimental Results -- 5 Comparative Analysis -- 5.1 Qualitative Analysis -- 5.2 Quantitative Analysis -- 6 Conclusion -- References -- Recognizing Hate Speech on Twitter with Feature Combo -- 1 Introduction -- 2 Literature Survey -- 2.1 Hate Speech -- 2.2 Stance Features -- 2.3 Similarity Measure-Based Features -- 2.4 Research Gaps -- 3 Methodology -- 3.1 Dataset and Pre-processing -- 3.2 Feature Generation -- 3.3 Model Architecture -- 4 Results and Evaluation -- 5 Conclusion and Future Enhancements -- References -- Agriculture Yield Forecasting via Regression and Deep Learning with Machine Learning Techniques -- 1 Introduction -- 1.1 Research Contributions -- 1.2 Article Organization -- 2 Literature Review -- 3 Proposed Work -- 3.1 Study Area. 3.2 Data Sources -- 3.3 Methods -- 4 Discussion -- 5 Conclusion and Future Scope -- References -- Performance Comparison of M-ary Phase Shift Keying and M-ary Quadrature Amplitude Modulation Techniques Under Fading Channels -- 1 Introduction -- 2 Proposed Method -- 2.1 BER of Digital Modulations Over AWGN -- 2.2 BER of Digital Modulations over Rayleigh Fading Channel -- 2.3 BER of Digital Modulations Over Nakagami Fading Channel -- 2.4 BER of Digital Modulations over Rician Fading Channel -- 3 Result and Discussions -- 3.1 Results -- 3.2 Discussion -- 4 Conclusion -- References -- Conception of Indian Monsoon Prediction Methods -- 1 Introduction -- 1.1 Present Monsoon Scenario -- 2 Related Work -- 3 Categorization of Monsoon Forecasting Techniques -- 3.1 Methodology-Based Monsoon Forecasting -- 3.2 Duration-Based Monsoon Forecasting -- 4 Comparative Analysis -- 4.1 Comparative Analysis of Methodology-Based Forecasts -- 4.2 Comparative Analysis of Duration-Based Forecast -- 4.3 Comparative Analysis of Machine Learning Algorithms in Statistical Approach -- 4.4 Comparative Analysis of Deep Neural Networks in Statistical Approach -- 5 Conclusion -- References -- AI-Integrated Smart Toy for Enhancing Cognitive, Emotional, and Motor Skills in Toddlers -- 1 Introduction -- 2 Literature Review -- 2.1 Transformation of the Human Brain from Birth -- 2.2 Emotion-Cognitive-Motor Development -- 2.3 Activities for Early Childhood Development -- 2.4 Use of Technology for Tracking Toddler Development -- 3 Design Methodology -- 3.1 Online Survey -- 3.2 Competitor Benchmarking Study -- 3.3 Contextual Inquiry -- 4 Conceptualization and Ideation -- 5 Working of the Proposed Design Concept -- 5.1 Usability Testing -- 6 Discussion and Conclusion -- 7 Limitations and Future Scope -- References -- Thumbnail Personalization in Movie Recommender System -- 1 Introduction. 2 Literature Review. |
| Record Nr. | UNINA-9910857792203321 |
|
Sharma Harish
|
||
| Singapore : , : Springer Singapore Pte. Limited, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Communication and Intelligent Systems : Proceedings of ICCIS 2023, Volume 3
| Communication and Intelligent Systems : Proceedings of ICCIS 2023, Volume 3 |
| Autore | Sharma Harish |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2024 |
| Descrizione fisica | 1 online resource (486 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
ShrivastavaVivek
TripathiAshish Kumar WangLipo |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN |
9789819720828
9789819720811 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- Deep Learning-Based Attack Prediction for Returns in Supply Chain Management Systems -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Architecture and Statistics -- 3.1 Dataset -- 3.2 Data Prepossessing -- 3.3 Identification of Attributes Using the Recommended PCA-BSO -- 3.4 A Distributed Denial-of-Service Categorization Employing Deep Learning and Machine Learning Strategies -- 4 Result and Discussion -- 4.1 Evaluation Matrices -- 4.2 Examination Utilizing Chosen Features Algorithms -- 4.3 Analysis in the Means of Supervised Algorithm -- 4.4 Analysis in the Means of DL Algorithms -- 5 Conclusion -- References -- An Effective Framework for Early Detection and Classification of Cardiovascular Disease (CVD) Using Machine Learning Techniques -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Problem Statement -- 3.2 Proposed Methodology -- 4 Experimental Results and Analysis -- 4.1 Dataset Description -- 4.2 Exploratory Data Analysis -- 4.3 Performance Measures -- 4.4 Simulation Results of the Proposed GB Model -- 4.5 Simulation Results of the Proposed AB Model -- 4.6 Simulation Results of the Proposed MLP Model -- 5 Discussion -- 6 Conclusion and Future Work -- References -- A Coherent Ensemble Modeling Approach for Diabetic Retinopathy Using MIFNET Method -- 1 Introduction -- 2 Literature Survey -- 3 Research Methodology -- 3.1 Image Enhancement -- 3.2 Gray-Level Thresholding -- 3.3 Gradient-Based Segmentation -- 3.4 Boundary Tracking -- 3.5 Laplacian Edge Detection -- 3.6 Region Growing -- 3.7 Wavelet Transforms -- 3.8 Feature Extraction -- 3.9 Image Processing -- 3.10 Convolutional Neural Networks -- 4 Conclusion and Result -- References -- A Novel Approach for Agricultural Crop Classification with Incremental Learning -- 1 Introduction -- 2 Literature Review.
3 Methodology -- 3.1 Dataset and Pre-processing Techniques -- 3.2 Model Development -- 4 Results Assessment -- 5 Conclusion and Further Improvements -- References -- Coronary Vessel Segmentation in X-ray Using U-Net -- 1 Introduction -- 2 Literature Review -- 3 Dataset and Methodology -- 3.1 U-Net Architecture -- 4 Results and Discussion -- 5 Conclusion -- References -- Unveiling Clarity: A Survey on Haze Removal Techniques Using Deep Learning Approaches -- 1 Introduction -- 2 Technical Background -- 3 Literature Review -- 3.1 Artificial Neural Network (ANN) -- 3.2 Convolutional Neural Network (CNN) -- 3.3 Recurrent Neural Network (RNN) -- 3.4 Autoencoder -- 3.5 Generative Adversarial Network (GAN) -- 4 Datasets -- 5 Assessment Criteria -- 5.1 Mean Squared Error (MSE) -- 5.2 Peak Signal-to-Noise Ratio (PSNR) -- 5.3 Structural SIMilarity (SSIM) -- 6 Approach Analysis -- 7 Conclusion -- References -- Surveying Strategies: Detecting Sinkhole Attacks in IoT Networks -- 1 Introduction -- 2 Background Details -- 2.1 IoT Architecture -- 2.2 Network Connecting Technologies -- 2.3 Sinkhole Attack -- 3 Sinkhole Attack Detection Strategy -- 3.1 Anomaly Based Sinkhole Detection -- 3.2 Signature-Based Sinkhole Detection -- 3.3 Specification-Based Sinkhole Detection -- 3.4 Hybrid-Based Sinkhole Detection -- 3.5 Trust-Based Sinkhole Detection -- 3.6 Machine Learning-Based Sinkhole Detection -- 3.7 Deep Learning-Based Sinkhole Detection -- 3.8 Ensemble Learning-Based Sinkhole Detection -- 3.9 Blockchain-Based Sinkhole Detection -- 4 Prevention Strategies -- 4.1 Bypassing Sinkhole Attack -- 4.2 Mitigate Sinkhole Attack -- 4.3 Isolate Sinkhole Attack -- 4.4 Blacklist Sinkhole Attack -- 5 Performance Metrics -- 5.1 Packet Delivery Ratio (PDR) -- 5.2 True Positive Rate (TPR) -- 5.3 False Positive Rate (FPR) -- 5.4 False Negative Rate (FNR) -- 5.5 Accuracy. 5.6 Precision -- 5.7 F1 Score -- 5.8 End-to-End Delay -- 5.9 Energy Consumption -- 5.10 Throughput -- 6 Comparative Analysis of Different Detection Strategies -- 7 Conclusion -- References -- Pattern of Lung Injury in CT/HRCT Using Deep Learning Techniques -- 1 Introduction -- 2 Literature Review -- 3 Dataset and Methodology -- 3.1 U-Net Architecture -- 3.2 MultiResUNet Architecture -- 4 Results and Discussion -- 5 Conclusion -- References -- Facial Expression Recognition in ATM Surveillance System -- 1 Introduction -- 2 Literature Survey -- 3 System Overview -- 3.1 Architecture of the Proposed System -- 3.2 Feature Extraction Using Local Binary Pattern (LBP) -- 3.3 Support Vector Machine (SVM) Classifier -- 4 Results and Discussion -- 4.1 Experimental Results of Facial Expression Inside ATM Cabin -- 5 Conclusion -- References -- Challenges, Communications, Routing Protocols and Applications of FANETs-A Systematic Review -- 1 Introduction -- 1.1 MANET -- 1.2 VANET -- 1.3 FANET -- 1.4 SANET -- 2 Communication Protocols -- 3 Routing Protocols -- 4 Challenges -- 5 Applications -- 6 Conclusion -- References -- Prediction of Chronic Venous Insufficiency Condition Using Infrared Thermography and Machine Learning -- 1 Introduction -- 1.1 Chronic Venous Insufficiency -- 1.2 Advancements in CVI Detection -- 2 Literature Review -- 3 Materials and Methods -- 3.1 Participants -- 3.2 Experimental Protocol -- 3.3 Implementation of Machine Learning Algorithms -- 3.4 Proposed Methodology -- 4 Results and Discussion -- 5 Conclusion -- References -- A Review of Brain Tumor MRI Classification and Feature Extraction Using Varying Methods -- 1 Introduction -- 1.1 Brain Tumor -- 1.2 Automatic Brain Tumor Identification System -- 2 Related Work -- 3 Analysis and Discussion -- 4 Conclusion -- References. Time Domain Specifications of Step Responses of Both Underdamped and Overdamped Systems: In Correction to MATLAB Inbuilt 'Stepinfo' Function -- 1 Introduction -- 2 Literature Review -- 3 Theoretical Background -- 3.1 Time Domain Specifications Formulas -- 4 Proposed Algorithm -- 5 Results and Discussion -- 5.1 Underdamped Response with No Steady State Error -- 5.2 Overdamped Response -- 5.3 Underdamped Response with Steady State Error -- 6 Conclusion -- References -- Transfer Learning-Based Speed Limit Traffic Sign Recognition with Multilingual Audio Alerts -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Dataset Description -- 3.2 Preprocessing -- 3.3 Algorithms and Techniques Used -- 3.4 Generation of Multilingual Audio Alerts -- 4 Results and Discussions -- 4.1 Evaluation Metrics -- 4.2 Performance Comparison -- 4.3 Confusion Matrix -- 4.4 Limitations -- 5 Conclusions and Future Work -- References -- Impact of the Use of Social Media Among University Students Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Proposed System -- 4 Dataset Description -- 4.1 Age -- 4.2 Number of Platform -- 4.3 Spend Time (Social Media vs Physical Activities) -- 4.4 Exposed to Inappropriate Content (1-10) -- 4.5 Victims of Cyber Crimes -- 4.6 Measurement Effect -- 5 Data Preprocessing -- 6 Used Model -- 7 Training and Evaluating Model -- 7.1 Cross Validation -- 7.2 Classification Evaluation -- 8 Result Analysis -- 8.1 Performance -- 8.2 ROC Curve -- 8.3 Confusion Matrix -- 8.4 Prediction -- 9 Future Scope and Conclusion -- References -- A Study on DL for Pulmonary Embolism Prediction Harnessing Multimodal Data -- 1 Introduction -- 2 Literature Review -- 3 Proposed Work -- 3.1 Input Data -- 3.2 Feature Fusion -- 3.3 DL Models -- 3.4 Softmax Classifier -- 4 Experimental Setup -- 4.1 Dataset Description -- 4.2 Performance Metrics. 5 Results and Discussions -- 6 Conclusion and Future Works -- References -- Performance Analysis of Machine Learning Algorithms Using Information Theoretic Class Based Multi-correlation Dependent Feature Selection -- 1 Introduction -- 1.1 Organization of the Paper -- 2 Literature Survey -- 3 Theoretical Background -- 3.1 Information Measuring Metrics -- 3.2 Feature Correlation Metrics -- 4 Proposed Method -- 5 Data Pre-processing -- 5.1 Dataset Details -- 5.2 Missing Values Removal -- 5.3 Imbalanced Dataset Handling -- 5.4 Feature Selection -- 6 Result Analysis -- 6.1 Without Feature Selection (FS) -- 6.2 With Proposed Feature Selection (FS) Technique -- 7 Conclusion -- References -- Empirical Analysis of Classification Approaches for Indian Language Processing -- 1 Introduction -- 1.1 Background: Linguistic Diversity in India -- 1.2 Objectives -- 2 Optical Character Recognition Workflow -- 2.1 Classification -- 2.2 Post Processing -- 3 Related Work on Indian Language -- 3.1 Devnagari Hindi, Marathi, Gurmukhi, and Gujarati -- 3.2 Telugu -- 3.3 Bangla -- 3.4 Kannada -- 4 Performance Evaluation of Classifiers with K-fold Validation for Indic Language -- 5 Limitations -- 6 Conclusion -- References -- An Overview of Generative Models for EEG Signal Processing -- 1 Introduction -- 2 Previous Works -- 2.1 Machine Learning -- 2.2 Deep Learning -- 2.3 Generative Models -- 3 Normalizing Flows -- 3.1 Change of Variable Formula -- 3.2 Jacobian Matrix -- 3.3 Types of Flows -- 3.4 Popular Normalizing Flow Architectures -- 3.5 Applications of Normalizing Flows -- 4 Scope of Flow-Based Models for EEG Signal Processing -- 5 Key Findings and Conclusion -- References -- Anomalous EEG Signal Time Series Classification Using Modified Metaheuristic Optimized RNN -- 1 Introduction -- 2 Related Works -- 2.1 Recurrent Neural Networks -- 2.2 Metaheuristic Optimization. 3 Methods. |
| Record Nr. | UNINA-9910865235703321 |
|
Sharma Harish
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| Singapore : , : Springer Singapore Pte. Limited, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Communication and Intelligent Systems : Proceedings of ICCIS 2023, Volume 1
| Communication and Intelligent Systems : Proceedings of ICCIS 2023, Volume 1 |
| Autore | Sharma Harish |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (459 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
ShrivastavaVivek
TripathiAshish Kumar WangLipo |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 981-9720-53-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910866572303321 |
|
Sharma Harish
|
||
| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Communication and Intelligent Systems : Proceedings of ICCIS 2022, Volume 2 / / edited by Harish Sharma, Vivek Shrivastava, Kusum Kumari Bharti, Lipo Wang
| Communication and Intelligent Systems : Proceedings of ICCIS 2022, Volume 2 / / edited by Harish Sharma, Vivek Shrivastava, Kusum Kumari Bharti, Lipo Wang |
| Autore | Sharma Harish |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (692 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
ShrivastavaVivek
BhartiKusum Kumari WangLipo |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Artificial intelligence Image processing—Digital techniques Computer vision Machine learning Computational Intelligence Artificial Intelligence Computer Imaging, Vision, Pattern Recognition and Graphics Machine Learning |
| ISBN | 981-9923-22-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Development an PMSM Servo Driver for CNC Machines using TMS28379D Microcontroller -- A Probabilistic Method to Identify HTTP/1.1 Slow Rate DoS Attacks -- Transmission Pricing using MW Mile Method in Deregulated Environment -- Performance Analysis of Non-Linear Companding Techniques for PAPR Mitigation in 5G GFDM Systems -- Tensor Completion based Data Imputation Framework for IoT-based Underwater Sensor Network -- Pre-training Classification and Clustering Models for Vietnamese Automatic Text Summarization -- Identifying Critical Transition in Bitcoin Market using Topological Data Analysis and Clustering -- Healthcare Information Exchange using Blockchain Technology -- Multilevel Credit Card Fraud Detection Using Face Recognition and Machine Learning -- Transfer Learning based End-to-End Indian-English Recognition System -- Impact of COVID-19 on the Sectors of the Indian Economy and the World -- Wind Farm Layout Optimization Problem using Teaching Learning Based Optimization Algorithm -- An Ensemble Multimodal Fusion using Naive Bayes Approach for Haptic Identification of Objects -- Chaotic Maps and DCT based Image Steganography-cum-Encryption Hybrid Approach -- An Empirical Analysis and Challenging Era of Blockchain in Green Society. |
| Record Nr. | UNINA-9910734878603321 |
|
Sharma Harish
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Communication and Intelligent Systems : Proceedings of ICCIS 2022, Volume 1 / / edited by Harish Sharma, Vivek Shrivastava, Kusum Kumari Bharti, Lipo Wang
| Communication and Intelligent Systems : Proceedings of ICCIS 2022, Volume 1 / / edited by Harish Sharma, Vivek Shrivastava, Kusum Kumari Bharti, Lipo Wang |
| Autore | Sharma Harish |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (722 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
ShrivastavaVivek
BhartiKusum Kumari WangLipo |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Artificial intelligence Image processing—Digital techniques Computer vision Machine learning Computational Intelligence Artificial Intelligence Computer Imaging, Vision, Pattern Recognition and Graphics Machine Learning |
| ISBN | 981-9921-00-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Network Coverage and Event Detection in Mobile Sensor Networks -- Attention Guided Human Fall Detection for Elderly Patient Monitoring -- SDN Enabled IoT to Combat the DDoS Attacks -- Analysis of Existing Datasets of Household Objects for AI-enabled Techniques -- In silico Molecular Docking Study by using Bio-Informatics Database to Fabricate M Cell Targeting Nanocarrier System for Oral Delivery of Macromolecules -- Open Source Datasets for Colonoscopy Polyps and its AI-enabled Techniques -- Cloud based House Price Predictor App using Machine Learning -- Compendium of Qubit Technologies in Quantum Computing -- A Novel Post Quantum Piekert's Reconciliation Based Forward Secure Authentication Key Agreement for Mobile Devices -- An Overview of IoT and Smart Application Environments: Research and Challenges -- Human Detection and Tracking Based on YOLOv3 and DeepSORT -- Smart City: Road Traffic Monitoring System Based on the Integration of IoT and ML -- Weed Detection in Crops using Lightweight EfficientNets -- Meta-Heuristics for the Single Channel PMU Placement Problem Considering Zero-Injection-Buses -- Comparative Analysis of Different Machine Learning Approaches for Sentiment Analysis -- A Comprehensive Investigation of Machine Learning Algorithms with SMOTE Integration to maximize F1 Score -- Detection of Pathological Myopia from Fundus Images. |
| Record Nr. | UNINA-9910735783503321 |
|
Sharma Harish
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||