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Advances and Applications of Artificial Intelligence and Machine Learning : Proceedings of ICAAAIML 2022
| Advances and Applications of Artificial Intelligence and Machine Learning : Proceedings of ICAAAIML 2022 |
| Autore | Unhelkar Bhuvan |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2023 |
| Descrizione fisica | 1 online resource (782 pages) |
| Altri autori (Persone) |
PandeyHari Mohan
AgrawalArun Prakash ChoudharyAnkur |
| Collana | Lecture Notes in Electrical Engineering Series |
| ISBN | 981-9959-74-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Contents -- About the Editors -- Development of Big Data Dimensionality Reduction Methods for Effective Data Transmission and Feature Enhancement Algorithms -- 1 Introduction -- 2 Works -- 3 Objectives -- 4 Proposed Dimensionality Reduction Method -- 5 Analysis of the Obtained Results -- 6 Conclusion -- References -- IndianFood-7: Detecting Indian Food Items Using Deep Learning-Based Computer Vision -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Preparation -- 3.2 Our Experimentation on Object Detection Models -- 4 Results -- 5 Conclusion -- References -- Prediction of Protein-Protein Interaction Using Support Vector Machine Based on Spatial Distribution of Amino Acids -- 1 Introduction -- 2 Experimental Setup -- 3 Methodology -- 3.1 Data Set -- 3.2 Feature Representation -- 3.3 Support Vector Machines (SVM) -- 4 Results and Discussion -- 4.1 Evaluation Metrics -- 4.2 Performance of Proposed Model -- 4.3 Proposed Model Comparison Against Various Predictors -- 5 Conclusion -- References -- A Computational Comparison of VGG16 and XceptionNet for Mango Plant Disease Recognition -- 1 Introduction -- 2 Methodology and Dataset -- 2.1 Architecture of the Proposed System -- 2.2 Dataset Description -- 2.3 Data Pre-processing -- 2.4 Models Used -- 2.5 Training and Compiling the Model -- 3 Result and Analysis -- 4 Conclusion -- References -- Generate Artificial Human Faces with Deep Convolutional Generative Adversarial Network (DCGAN) Machine Learning Model -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Experimental Setup -- 3.2 Dataset Description -- 3.3 Model Description -- 4 Results -- 5 Future Scope and Conclusion -- References -- Robust Approach for Person Identification Using Three-Triangle Concept -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Block Diagram of Recommended System.
3.2 Algorithm Used -- 4 Circuit Layout -- 5 Interfacing of Components -- 6 Experimental Results -- 7 Conclusions -- 8 Future Scope -- References -- COVID-19 Disease Detection Using Explainable AI -- 1 Introduction -- 2 Explainable Artificial Intelligence -- 3 Dataset Description -- 4 Approach to the Proposed System -- 4.1 Support Vector Machine -- 4.2 Convolutional Neural Networks -- 4.3 ResNet50 -- 4.4 Implementation of Explainable AI -- 5 Proposed Methodology -- 6 Results -- 7 Conclusion and Future Scope -- References -- Towards Helping Visually Impaired People to Navigate Outdoor -- 1 Introduction -- 1.1 Convolutional Neural Network -- 1.2 Visual Geometry Group -- 2 Literature -- 3 Methodology -- 3.1 Create the Dataset -- 3.2 Applying Existing Approach -- 3.3 Analyzing the Existing Approach -- 3.4 Detect Objects in Image -- 3.5 Train and Test the Model -- 3.6 Analyzing the Results -- 4 Experimentation -- 5 Conclusion and Future Work -- References -- An Analysis of Deployment Challenges for Kubernetes: A NextGen Virtualization -- 1 Introduction -- 2 Origin, History of Kubernetes, and the Community Behind -- 3 Related Works -- 3.1 Literature Review -- 3.2 Objective -- 4 Deployment of Application in Kubernetes Cluster in Public Cloud -- 4.1 Survey to Examine Kubernetes Impact -- 5 Analysis of Deployment Failure Strategies and Measures -- 6 Result Analysis -- 7 Result Analysis -- 8 Conclusion -- References -- A New Task Offloading Scheme for Geospatial Fog Computing Environment Using M/M/C Queueing Approach -- 1 Introduction -- 2 Related Work -- 3 Establishing the Model -- 4 Numerical and Simulation Examples -- 5 Conclusions and Future Work -- References -- Face Recognition Using Deep Neural Network with MobileNetV3-Large -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset -- 3.2 Pre-processing -- 3.3 MobileNetV3Large Model. 3.4 Hyperparameter Tuning -- 4 Result -- 5 Conclusion -- References -- Detection of BotNet Using Extreme Learning Machine Tuned by Enhanced Sine Cosine Algorithm -- 1 Introduction -- 2 Background and Related Work -- 2.1 BotNet and DDOS -- 2.2 Extreme Learning Machine -- 2.3 Population-Based Metaheuristics -- 3 Proposed Method -- 3.1 Suggested Improved SCA -- 4 Experiments and Discussion -- 4.1 Dataset Description, Pre-processing and Evaluation Metrics -- 4.2 Research Findings and Comparative Analysis -- 5 Conclusion -- References -- Cloud Services Management Using LSTM-RNN -- 1 Introduction -- 2 Related Work -- 3 Proposed Model -- 3.1 Forecast Utilizing LSTM-RNN -- 3.2 Workload Prediction Using LSTM Pseudocode -- 4 Result -- 5 Conclusion and Future Scope -- References -- Detection of Various Types of Thyroid-Related Disease Using Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Proposed System -- 3.1 Dataset -- 3.2 Exploratory Data Analysis -- 3.3 Data Preprocessing -- 3.4 Training Phase -- 3.5 Testing the Model -- 4 Results and Discussion -- 5 Conclusion -- References -- Implementation of WSN in the Smart Hanger to Facilitate MRO Operations on Aircraft Fuselage Using Machine Learning -- 1 Introduction -- 2 Acquisition and Dataset -- 2.1 Complexity of Model and Training Dataset -- 2.2 Learning from Imbalanced Data -- 3 Existing Machine Learning Approaches -- 3.1 DNN (Deep Neural Networks) -- 3.2 Support Vector Machine (SVM) -- 3.3 Algorithmic Approach Using Minimal Data: Few-Shot Learning -- 4 State of the Art Method Evaluation -- 4.1 Experiment -- 4.2 Result -- 5 Proposed Approach -- 6 Conclusion and Prospects -- References -- Wi-Fi Controlled Smart Robot for Objects Tracking and Counting -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Wi-Fi Controlled Smart Robot Through Web Server. 3.2 Proposed Methodology for Color Detection -- 3.3 Object Tracking for Counting Objects -- 4 Results and Discussion -- 5 Conclusion -- References -- Speech Recognition for Kannada Using LSTM -- 1 Introduction -- 2 Literature Review -- 3 Overview of LSTM and Kaldi -- 3.1 Markov Models -- 3.2 RNN -- 3.3 LSTM -- 3.4 Kaldi -- 4 Methodology -- 4.1 Audio Data Collection -- 4.2 Text Data Pre-processing -- 4.3 Feature Extraction and Preparing Language Models -- 4.4 Experiments with Monophone, Triphone Models -- 4.5 Experiments with DNN and LSTM -- 5 Results -- 6 Conclusion -- References -- Computer Vision-Based Smart Helmet with Voice Assistant for Increasing Driver Safety -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Deep Learning Model Development -- 3.2 Rear-End Collision Warning System -- 3.3 Deployment of Deep Learning Model via Server -- 3.4 Architecture of Helmet Software -- 3.5 Building Helmet (Hardware) Prototype -- 3.6 Comparison and Analysis of Models -- 4 Result -- 5 Conclusion and Future Scope -- References -- Predicting Aging Related Bugs with Automated Feature Selection Techniques in Cloud Oriented Softwares -- 1 Research Motivation and Aim -- 1.1 Imbalanced Data -- 1.2 High Dimensional Data -- 2 Related Work -- 3 Research Contributions -- 4 Research Framework -- 4.1 Automated Bug Report Extraction -- 4.2 Feature Selection Techniques -- 4.3 Datasets -- 4.4 Software Metrics -- 4.5 Imbalance Mitigation Procedure-SMOTE -- 4.6 Machine Learning Classifiers -- 4.7 Performance Measures -- 5 Experimental Setup -- 6 Results and Discussions -- 6.1 Detailed Analysis of Feature Ranking -- 6.2 Relative Comparison of Techniques -- 7 Conclusion -- 8 Threats to Validity and Future Work -- References -- Time Series Analysis of Crypto Currency Using ARIMAX -- 1 Introduction -- 2 Literature Review -- 3 Methodology. 4 Components Taken into Consideration -- 4.1 Factors that Affect Crypto Currency -- 4.2 Dataset Used -- 4.3 ARIMAX Algorithm -- 5 Experimental Setup -- 5.1 Cointegrated Pair -- 5.2 Selection of Features -- 5.3 Building the Model -- 6 Result Analysis -- 7 Conclusion -- References -- A Machine Learning Approach Towards Prediction of User's Responsiveness to Notifications with Best Device Identification for Notification Delivery -- 1 Introduction -- 2 Related Work -- 3 Proposed System Architecture -- 3.1 Notification Module -- 3.2 User Identification Module -- 3.3 Active Device and Proximity Detection Module -- 3.4 Privacy and Access Control Module -- 3.5 Intelligent Delivery System Module -- 3.6 Notification Storage Bucket -- 4 Predicting User's Responsiveness to Notifications -- 4.1 Dataset -- 4.2 Predicting User's Responsiveness Using Machine Learning -- 5 Results and Discussions -- 6 Conclusion and Future Work -- References -- Real-Time Full Body Tracking for Life-Size Telepresence -- 1 Introduction -- 2 Related Work -- 3 Material and Method -- 3.1 Full-Body Tracking -- 3.2 Background Removal -- 3.3 Remote User Setting -- 4 Results and Discussion -- 5 Conclusion -- References -- Solar Power Generation Forecasting Using Deep Learning -- 1 Introduction -- 2 Use of Artificial Intelligence in Predicting Data -- 3 Methodology -- 3.1 Data Collection -- 3.2 Pre-processing -- 3.3 Split Data into Train and Testing Sets -- 3.4 Data Standardization -- 3.5 Building Model -- 3.6 Training Model -- 4 Model Building and Implementation -- 5 Model Evaluation -- 6 Results -- 7 Conclusion -- References -- Applications of Big Five Personality Test in Job Performance -- 1 Introduction -- 1.1 Dimensions of Job Performance -- 1.2 Personality Model with Five Traits -- 2 Literature Review -- 3 Objectives of the Study -- 4 Research Design -- 4.1 Measuring Instruments. 5 Data Analysis Technique Employed. |
| Record Nr. | UNINA-9910763599703321 |
Unhelkar Bhuvan
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| Singapore : , : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Artificial-Business Analytics and Quantum Machine Learning : Select Proceedings of the 3rd International Conference, Com-IT-Con 2023, Volume 1 / / edited by K. C. Santosh, Sandeep Kumar Sood, Hari Mohan Pandey, Charu Virmani
| Advances in Artificial-Business Analytics and Quantum Machine Learning : Select Proceedings of the 3rd International Conference, Com-IT-Con 2023, Volume 1 / / edited by K. C. Santosh, Sandeep Kumar Sood, Hari Mohan Pandey, Charu Virmani |
| Autore | Santosh K. C |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (810 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
SoodSandeep Kumar
PandeyHari Mohan VirmaniCharu |
| Collana | Lecture Notes in Electrical Engineering |
| Soggetto topico |
Data protection
Artificial intelligence Application software Data and Information Security Artificial Intelligence Computer and Information Systems Applications |
| ISBN | 981-9725-08-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Track 1 AI & Business Analytics -- Track 2 Virtual Reality & Augmented Reality -- Track 3 Computational Biology & Bioinformatics -- Track 4 Quantum Information System -- Track 5 Block Chain & Cyber Security -- Track 6 Data Science & Machine Learning -- Track 7 Cloud Computing & Virtualisation. |
| Record Nr. | UNINA-9910887804603321 |
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Santosh K. C
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Artificial-Business Analytics and Quantum Machine Learning : Select Proceedings of the 3rd International Conference, Com-IT-Con 2023, Volume 2 / / edited by KC Santosh, Poonam Nandal, Sandeep Kumar Sood, Hari Mohan Pandey
| Advances in Artificial-Business Analytics and Quantum Machine Learning : Select Proceedings of the 3rd International Conference, Com-IT-Con 2023, Volume 2 / / edited by KC Santosh, Poonam Nandal, Sandeep Kumar Sood, Hari Mohan Pandey |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (XVI, 330 p. 115 illus., 74 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Artificial intelligence
Business - Data processing Data protection Artificial Intelligence Business Informatics Data and Information Security |
| ISBN | 981-9748-60-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910897988103321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Applications of artificial intelligence and machine learning : select proceedings of ICAAAIML 2021 / / Bhuvan Unhelker, Hari Mohan Pandey and Gaurav Raj, editors
| Applications of artificial intelligence and machine learning : select proceedings of ICAAAIML 2021 / / Bhuvan Unhelker, Hari Mohan Pandey and Gaurav Raj, editors |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore Pte Ltd., , [2022] |
| Descrizione fisica | 1 online resource (792 pages) |
| Disciplina | 006.3 |
| Collana | Lecture notes in electrical engineering |
| Soggetto topico |
Machine learning
Artificial intelligence |
| ISBN | 981-19-4831-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Contents -- About the Editors -- Firefly Algorithm and Deep Neural Network Approach for Intrusion Detection -- 1 Introduction -- 1.1 Research Goals and Contributions -- 1.2 Structure of the Paper -- 2 Theoretical Background and Literature Review -- 3 Proposed Method -- 3.1 Enhanced FA Metaheuristics -- 4 The eFA and DNN Framework for IDS Classification Experiments -- 5 Conclusion -- References -- Dimensionality Reduction Method for Early Detection of Dementia -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Materials and Subjects -- 3.2 Pre-processing -- 3.3 Feature Reduction -- 4 Result and Discussion -- 5 Conclusion -- References -- Prognostication in Retail World: Analysing Using Opinion Mining -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Model -- 3.1 Sentimental Analysis -- 3.2 Classification Model -- 3.3 Techniques and Tools -- 4 Data -- 5 Evaluation Outcome -- 6 Conclusion -- References -- Impact of Resolution Techniques on Chlorophyll Fluorescence Wheat Images Using Classifier Models to Detect Nitrogen Deficiency -- 1 Introduction -- 2 Related Work -- 3 Experimental Setup -- 4 Results and Discussions -- 5 Conclusions -- References -- Exploring Practical Deep Learning Approaches for English-to-Hindi Image Caption Translation Using Transformers and Object Detectors -- 1 Background -- 2 Dataset, Methodology and Experimental Setup -- 2.1 Dataset -- 2.2 Experimental Setup -- 2.3 Pre-processing Dataset -- 2.4 Run-Time Data Handling -- 2.5 Training and Evaluation -- 3 Model Architectures and Configurations Tested -- 3.1 Class A (Seq2Seq Caption Translation) -- 3.2 Class B (Transformer Caption Translation) -- 3.3 Class C (Pre-trained Transformer Caption Translation) -- 4 Results -- 5 Comparison with Existing Work -- 6 Conclusion -- References.
Saving Patterns and Investment Preferences: Prediction Through Machine Learning Approaches -- 1 Introduction -- 2 Review of Literature and Hypothesis Development -- 3 Data Analysis -- 3.1 Regression Equation and Data -- 4 Result Analysis and Discussion -- 4.1 Effect of Eight Independent Variables on the Saving Patterns -- 4.2 Effect of Eight Independent Variables on the Investment Preferences -- 4.3 Discussion -- 5 Conclusion -- References -- A Machine Learning Based Approach for Detection of Distributed Denial of Service Attacks -- 1 Introduction -- 2 Related Work -- 3 Proposed Framework for DDoS Attack Detection -- 3.1 Problem Definition -- 3.2 The Framework -- 3.3 Proposed Algorithm -- 3.4 Metrics for Performance Evaluation -- 4 Experimental Results -- 5 Conclusion and Future Work -- References -- Convolutional Neural Network Based Automatic Speech Recognition for Tamil Language -- 1 Introduction -- 2 Literature Review -- 3 Convolution Neural Network -- 4 Experimental Setup -- 4.1 Feature Extraction -- 4.2 Convolutional Neural Network Model -- 5 Result and Discussion -- 6 Conclusion -- References -- Identification of Wheat and Foreign Matter Using Artificial Neural Network and Genetic Algorithm -- 1 Introduction -- 2 Proposed Methodology -- 2.1 Preparation of Samples -- 2.2 Image Segmentation -- 2.3 Feature Extraction -- 2.4 Detection using ANN -- 2.5 Selection of Optimal Features Using GA -- 3 Experimental Results and Discussions -- 4 Conclusion -- References -- Efficient Classification of Heart Disease Forecasting by Using Hyperparameter Tuning -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Classification of Heart Disease Prediction Using Neural Network Model with Hyper Parameter Tuning -- 3.2 Automatic Hyper Parameter Tuning -- 3.3 Evaluation Metrics -- 4 Results and Discussion -- 4.1 Outcome of Data Pre-processing. 4.2 Performance Evaluation -- 4.3 Comparison of Model Performance with and without Hyper Parameter Tuning -- 5 Conclusion -- References -- LS-Net: An Improved Deep Generative Adversarial Network for Retinal Lesion Segmentation in Fundus Image -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Conditional GANs -- 3.2 Image-To-Image Translation Network -- 3.3 Spectral Normalization -- 3.4 Loss Function -- 4 Experimental Setup -- 4.1 Dataset -- 4.2 Evaluation Metrics -- 4.3 Network Training -- 4.4 Implementation Details -- 5 Results and Discussion -- 5.1 Results -- 5.2 Discussion -- 6 Conclusion -- References -- A Novel Approach for Analysis of Air Quality Index Before and After Covid-19 Using Machine Learning -- 1 Introduction -- 2 Background and Motivation -- 3 Proposed Work -- 4 Multiple Linear Regression -- 5 Polynomial Regression -- 6 Experimental Result -- 6.1 Dataset -- 6.2 Evaluation Matrix -- 6.3 Result and Discussion -- 7 Conclusion -- References -- Embedding of Q-Learning in Sine Co-Sine Algorithm for Optimal Multi Robot Path Planning -- 1 Introduction -- 2 Formulation of the Problem -- 2.1 Objective Function Creation for Optimized Navigation -- 2.2 Movement of Mobile Robot -- 3 Projected Optimization Methods -- 3.1 Q-Learning Algorithm -- 3.2 Sine-Cosine Algorithm (SCA) -- 4 Necessity of Hybridization and Proposed Algorithm for Multi-robot Path Planning -- 5 Computer Simulation -- 6 Experiment on E-puck Robot -- 7 Performance Analysis -- 8 Conclusion and Future Works -- References -- Image-Based Number Sign Recognition for Ethiopian Sign Language Using Support Vector Machine -- 1 Introduction -- 2 Related Works -- 3 Ethiopian Sign Language Number System -- 3.1 Amharic Sign Language System -- 3.2 Proposed System -- 3.3 Support Vector Machine Modeling -- 4 Results and Discussion -- 4.1 Dataset -- 4.2 Performance Evaluation. 4.3 Test Result -- 5 Conclusion -- References -- BIC Algorithm for Exercise Behavior at Customers' Fitness Center in Ho Chi Minh City, Vietnam -- 1 Introduction -- 2 Literature Review -- 2.1 Exercise Behavior (EB) -- 2.2 Usefulness (US) -- 2.3 Ease of Use (EU) -- 2.4 Barrier (BR) -- 2.5 Facilities (FAC) -- 2.6 Price and Promotion (PP) -- 2.7 Service Quality (SQ) -- 3 Methodology -- 3.1 Sample -- 3.2 Reliability Test and BIC Algorithm -- 4 Results -- 4.1 Reliability Test -- 4.2 BIC Algorithm -- 4.3 Model Evaluation -- 5 Conclusions -- 6 Limitations and Future Scope -- References -- Medicine Supply Chain Using Ethereum Blockchain -- 1 Introduction -- 2 Related Previous Work -- 3 Proposed Method -- 3.1 Overview of Drug SCM Procedure -- 3.2 Three-Layer Architecture -- 3.3 Detail Architecture of Proposed DSCM System -- 3.4 Smart Contract of DSCM -- 3.5 Transactions Execution Procedure in DSCM -- 4 Stakeholders -- 4.1 Supplier -- 4.2 Manufacturer -- 4.3 Distributor -- 4.4 Hospitals -- 4.5 Pharmacies -- 5 Scope -- 6 Result and Evaluation -- 6.1 Deployment Costs -- 6.2 Price of the Gas Used in deploy the Smart Contract -- 7 Conclusion and Future Work -- References -- Human Activity Recognition Using Single Frame CNN -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methods and Results -- 3.1 CNN Classification Model -- 3.2 Compile and Train the Model -- 3.3 Plot Accuracy Curves and Model's Loss -- 4 Conclusion -- 5 Future Scope -- References -- Monitoring Pedestrian Social Distance System for COVID-19 -- 1 Introduction -- 2 Literature Survey -- 3 Technologies Used -- 3.1 Python -- 3.2 OpenCV -- 3.3 YOLOv3 -- 4 Propounded Monitoring Pedestrian Scheme -- 4.1 Camera Perspective Transformation -- 4.2 Pedestrian Detection and Tracking -- 4.3 Distance Calculation -- 4.4 Distance Violation with Count -- 5 Testing and Analysis -- 6 Conclusion -- References. A Study and Comparative Analysis on Different Techniques Used for Predicting Type 2 Diabetes Mellitus -- 1 Introduction -- 1.1 Classification of Diabetes Mellitus: There Are Primarily Three Types of Known Diabetes Mellitus -- 1.2 Possible Reasons for Diabetes -- 1.3 Possible Problems Due to Diabetes: -- 2 Existing Predictive Analysis Techniques -- 2.1 Machine Learning (ML) Algorithms can be broadly classified as -- 2.2 Deep Learning (DL) Algorithm -- 2.3 Nature-Inspired Algorithm -- 3 Performance Analysis of Various Predictive Analysis Techniques -- 4 Comparison of Techniques Employed for Diabetes Prediction -- 5 Conclusion and Future Scope -- References -- RGB Based Secure Share Creation in Steganography with ECC and DNN -- 1 Introduction -- 2 Steganographic Techniques -- 3 Elliptic Curve Cryptography [ECC] -- 3.1 Proposed Model -- 3.2 Implementation Specifications -- 3.3 Modelling of Architecture -- 3.4 Secure Share Creation Using RGB -- 3.5 Reconstruction of the Shadow Images -- 4 Results and Discussion -- 4.1 Results for Multiple Hidden Secrets -- 4.2 Splitting of Channels -- 4.3 Creating Shares or Shadows of the Corresponding Channels -- 4.4 Encrypting the Generated Shares -- 4.5 Comparison of Histogram Between the Original Shares and the Encrypted Shares -- 4.6 Decryption and Stacking of Shares -- 4.7 Revealed Network -- 4.8 SSIM of Cover, Container, Secret and Decoded Secret Images -- 4.9 Complexity of Computation -- 5 Conclusion -- References -- Model to Detect and Correct the Grammatical Error in a Sentence Using Pre-trained BERT -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- Crop Recommendation System for Precision Agriculture Using Fuzzy Clustering Based Ant Colony Optimization -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Collaborative Filtering. 3.2 Ant Colony Optimization (ACO). |
| Record Nr. | UNINA-9910595034803321 |
| Singapore : , : Springer Nature Singapore Pte Ltd., , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Applications of artificial intelligence and machine learning : select proceedings of ICAAAIML 2021 / / Bhuvan Unhelker, Hari Mohan Pandey and Gaurav Raj, editors
| Applications of artificial intelligence and machine learning : select proceedings of ICAAAIML 2021 / / Bhuvan Unhelker, Hari Mohan Pandey and Gaurav Raj, editors |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore Pte Ltd., , [2022] |
| Descrizione fisica | 1 online resource (792 pages) |
| Disciplina | 006.3 |
| Collana | Lecture notes in electrical engineering |
| Soggetto topico |
Machine learning
Artificial intelligence |
| ISBN | 981-19-4831-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Contents -- About the Editors -- Firefly Algorithm and Deep Neural Network Approach for Intrusion Detection -- 1 Introduction -- 1.1 Research Goals and Contributions -- 1.2 Structure of the Paper -- 2 Theoretical Background and Literature Review -- 3 Proposed Method -- 3.1 Enhanced FA Metaheuristics -- 4 The eFA and DNN Framework for IDS Classification Experiments -- 5 Conclusion -- References -- Dimensionality Reduction Method for Early Detection of Dementia -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Materials and Subjects -- 3.2 Pre-processing -- 3.3 Feature Reduction -- 4 Result and Discussion -- 5 Conclusion -- References -- Prognostication in Retail World: Analysing Using Opinion Mining -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Model -- 3.1 Sentimental Analysis -- 3.2 Classification Model -- 3.3 Techniques and Tools -- 4 Data -- 5 Evaluation Outcome -- 6 Conclusion -- References -- Impact of Resolution Techniques on Chlorophyll Fluorescence Wheat Images Using Classifier Models to Detect Nitrogen Deficiency -- 1 Introduction -- 2 Related Work -- 3 Experimental Setup -- 4 Results and Discussions -- 5 Conclusions -- References -- Exploring Practical Deep Learning Approaches for English-to-Hindi Image Caption Translation Using Transformers and Object Detectors -- 1 Background -- 2 Dataset, Methodology and Experimental Setup -- 2.1 Dataset -- 2.2 Experimental Setup -- 2.3 Pre-processing Dataset -- 2.4 Run-Time Data Handling -- 2.5 Training and Evaluation -- 3 Model Architectures and Configurations Tested -- 3.1 Class A (Seq2Seq Caption Translation) -- 3.2 Class B (Transformer Caption Translation) -- 3.3 Class C (Pre-trained Transformer Caption Translation) -- 4 Results -- 5 Comparison with Existing Work -- 6 Conclusion -- References.
Saving Patterns and Investment Preferences: Prediction Through Machine Learning Approaches -- 1 Introduction -- 2 Review of Literature and Hypothesis Development -- 3 Data Analysis -- 3.1 Regression Equation and Data -- 4 Result Analysis and Discussion -- 4.1 Effect of Eight Independent Variables on the Saving Patterns -- 4.2 Effect of Eight Independent Variables on the Investment Preferences -- 4.3 Discussion -- 5 Conclusion -- References -- A Machine Learning Based Approach for Detection of Distributed Denial of Service Attacks -- 1 Introduction -- 2 Related Work -- 3 Proposed Framework for DDoS Attack Detection -- 3.1 Problem Definition -- 3.2 The Framework -- 3.3 Proposed Algorithm -- 3.4 Metrics for Performance Evaluation -- 4 Experimental Results -- 5 Conclusion and Future Work -- References -- Convolutional Neural Network Based Automatic Speech Recognition for Tamil Language -- 1 Introduction -- 2 Literature Review -- 3 Convolution Neural Network -- 4 Experimental Setup -- 4.1 Feature Extraction -- 4.2 Convolutional Neural Network Model -- 5 Result and Discussion -- 6 Conclusion -- References -- Identification of Wheat and Foreign Matter Using Artificial Neural Network and Genetic Algorithm -- 1 Introduction -- 2 Proposed Methodology -- 2.1 Preparation of Samples -- 2.2 Image Segmentation -- 2.3 Feature Extraction -- 2.4 Detection using ANN -- 2.5 Selection of Optimal Features Using GA -- 3 Experimental Results and Discussions -- 4 Conclusion -- References -- Efficient Classification of Heart Disease Forecasting by Using Hyperparameter Tuning -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Classification of Heart Disease Prediction Using Neural Network Model with Hyper Parameter Tuning -- 3.2 Automatic Hyper Parameter Tuning -- 3.3 Evaluation Metrics -- 4 Results and Discussion -- 4.1 Outcome of Data Pre-processing. 4.2 Performance Evaluation -- 4.3 Comparison of Model Performance with and without Hyper Parameter Tuning -- 5 Conclusion -- References -- LS-Net: An Improved Deep Generative Adversarial Network for Retinal Lesion Segmentation in Fundus Image -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Conditional GANs -- 3.2 Image-To-Image Translation Network -- 3.3 Spectral Normalization -- 3.4 Loss Function -- 4 Experimental Setup -- 4.1 Dataset -- 4.2 Evaluation Metrics -- 4.3 Network Training -- 4.4 Implementation Details -- 5 Results and Discussion -- 5.1 Results -- 5.2 Discussion -- 6 Conclusion -- References -- A Novel Approach for Analysis of Air Quality Index Before and After Covid-19 Using Machine Learning -- 1 Introduction -- 2 Background and Motivation -- 3 Proposed Work -- 4 Multiple Linear Regression -- 5 Polynomial Regression -- 6 Experimental Result -- 6.1 Dataset -- 6.2 Evaluation Matrix -- 6.3 Result and Discussion -- 7 Conclusion -- References -- Embedding of Q-Learning in Sine Co-Sine Algorithm for Optimal Multi Robot Path Planning -- 1 Introduction -- 2 Formulation of the Problem -- 2.1 Objective Function Creation for Optimized Navigation -- 2.2 Movement of Mobile Robot -- 3 Projected Optimization Methods -- 3.1 Q-Learning Algorithm -- 3.2 Sine-Cosine Algorithm (SCA) -- 4 Necessity of Hybridization and Proposed Algorithm for Multi-robot Path Planning -- 5 Computer Simulation -- 6 Experiment on E-puck Robot -- 7 Performance Analysis -- 8 Conclusion and Future Works -- References -- Image-Based Number Sign Recognition for Ethiopian Sign Language Using Support Vector Machine -- 1 Introduction -- 2 Related Works -- 3 Ethiopian Sign Language Number System -- 3.1 Amharic Sign Language System -- 3.2 Proposed System -- 3.3 Support Vector Machine Modeling -- 4 Results and Discussion -- 4.1 Dataset -- 4.2 Performance Evaluation. 4.3 Test Result -- 5 Conclusion -- References -- BIC Algorithm for Exercise Behavior at Customers' Fitness Center in Ho Chi Minh City, Vietnam -- 1 Introduction -- 2 Literature Review -- 2.1 Exercise Behavior (EB) -- 2.2 Usefulness (US) -- 2.3 Ease of Use (EU) -- 2.4 Barrier (BR) -- 2.5 Facilities (FAC) -- 2.6 Price and Promotion (PP) -- 2.7 Service Quality (SQ) -- 3 Methodology -- 3.1 Sample -- 3.2 Reliability Test and BIC Algorithm -- 4 Results -- 4.1 Reliability Test -- 4.2 BIC Algorithm -- 4.3 Model Evaluation -- 5 Conclusions -- 6 Limitations and Future Scope -- References -- Medicine Supply Chain Using Ethereum Blockchain -- 1 Introduction -- 2 Related Previous Work -- 3 Proposed Method -- 3.1 Overview of Drug SCM Procedure -- 3.2 Three-Layer Architecture -- 3.3 Detail Architecture of Proposed DSCM System -- 3.4 Smart Contract of DSCM -- 3.5 Transactions Execution Procedure in DSCM -- 4 Stakeholders -- 4.1 Supplier -- 4.2 Manufacturer -- 4.3 Distributor -- 4.4 Hospitals -- 4.5 Pharmacies -- 5 Scope -- 6 Result and Evaluation -- 6.1 Deployment Costs -- 6.2 Price of the Gas Used in deploy the Smart Contract -- 7 Conclusion and Future Work -- References -- Human Activity Recognition Using Single Frame CNN -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methods and Results -- 3.1 CNN Classification Model -- 3.2 Compile and Train the Model -- 3.3 Plot Accuracy Curves and Model's Loss -- 4 Conclusion -- 5 Future Scope -- References -- Monitoring Pedestrian Social Distance System for COVID-19 -- 1 Introduction -- 2 Literature Survey -- 3 Technologies Used -- 3.1 Python -- 3.2 OpenCV -- 3.3 YOLOv3 -- 4 Propounded Monitoring Pedestrian Scheme -- 4.1 Camera Perspective Transformation -- 4.2 Pedestrian Detection and Tracking -- 4.3 Distance Calculation -- 4.4 Distance Violation with Count -- 5 Testing and Analysis -- 6 Conclusion -- References. A Study and Comparative Analysis on Different Techniques Used for Predicting Type 2 Diabetes Mellitus -- 1 Introduction -- 1.1 Classification of Diabetes Mellitus: There Are Primarily Three Types of Known Diabetes Mellitus -- 1.2 Possible Reasons for Diabetes -- 1.3 Possible Problems Due to Diabetes: -- 2 Existing Predictive Analysis Techniques -- 2.1 Machine Learning (ML) Algorithms can be broadly classified as -- 2.2 Deep Learning (DL) Algorithm -- 2.3 Nature-Inspired Algorithm -- 3 Performance Analysis of Various Predictive Analysis Techniques -- 4 Comparison of Techniques Employed for Diabetes Prediction -- 5 Conclusion and Future Scope -- References -- RGB Based Secure Share Creation in Steganography with ECC and DNN -- 1 Introduction -- 2 Steganographic Techniques -- 3 Elliptic Curve Cryptography [ECC] -- 3.1 Proposed Model -- 3.2 Implementation Specifications -- 3.3 Modelling of Architecture -- 3.4 Secure Share Creation Using RGB -- 3.5 Reconstruction of the Shadow Images -- 4 Results and Discussion -- 4.1 Results for Multiple Hidden Secrets -- 4.2 Splitting of Channels -- 4.3 Creating Shares or Shadows of the Corresponding Channels -- 4.4 Encrypting the Generated Shares -- 4.5 Comparison of Histogram Between the Original Shares and the Encrypted Shares -- 4.6 Decryption and Stacking of Shares -- 4.7 Revealed Network -- 4.8 SSIM of Cover, Container, Secret and Decoded Secret Images -- 4.9 Complexity of Computation -- 5 Conclusion -- References -- Model to Detect and Correct the Grammatical Error in a Sentence Using Pre-trained BERT -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- Crop Recommendation System for Precision Agriculture Using Fuzzy Clustering Based Ant Colony Optimization -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Collaborative Filtering. 3.2 Ant Colony Optimization (ACO). |
| Record Nr. | UNISA-996490364103316 |
| Singapore : , : Springer Nature Singapore Pte Ltd., , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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