Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Advances in applications of data-driven computing / / editors, Jagdish Chand Bansal [et al.]
| Advances in applications of data-driven computing / / editors, Jagdish Chand Bansal [et al.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (xii, 182 pages) : illustrations (some color) |
| Disciplina | 004 |
| Collana | Advances in intelligent systems and computing |
| Soggetto topico |
Artificial intelligence
Electronic data processing Intel·ligència artificial Processament de dades |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 981-336-919-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483110503321 |
| Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Data-Driven Computing and Intelligent Systems [[electronic resource] ] : Selected Papers from ADCIS 2023, Volume 4 / / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Hemant Rathore, Jagdish Chand Bansal
| Advances in Data-Driven Computing and Intelligent Systems [[electronic resource] ] : Selected Papers from ADCIS 2023, Volume 4 / / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Hemant Rathore, Jagdish Chand Bansal |
| Autore | Das Swagatam |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (517 pages) |
| Disciplina | 006.33 |
| Altri autori (Persone) |
SahaSnehanshu
CoelloCarlos A. Coello RathoreHemant BansalJagdish Chand |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Telecommunication
Electronic circuits Cloud Computing Artificial intelligence Signal processing Communications Engineering, Networks Electronic Circuits and Systems Artificial Intelligence Signal, Speech and Image Processing |
| ISBN | 981-9995-31-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910847582703321 |
Das Swagatam
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Data-Driven Computing and Intelligent Systems [[electronic resource] ] : Selected Papers from ADCIS 2022, Volume 1 / / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Jagdish Chand Bansal
| Advances in Data-Driven Computing and Intelligent Systems [[electronic resource] ] : Selected Papers from ADCIS 2022, Volume 1 / / edited by Swagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Jagdish Chand Bansal |
| Autore | Das Swagatam |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (885 pages) |
| Disciplina | 006.33 |
| Altri autori (Persone) |
SahaSnehanshu
Coello CoelloCarlos A BansalJagdish Chand |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Telecommunication
Electronic circuits Cloud Computing Artificial intelligence Signal processing Communications Engineering, Networks Electronic Circuits and Systems Artificial Intelligence Signal, Speech and Image Processing |
| ISBN | 981-9932-50-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contibutors -- Adaptive Volterra Noise Cancellation Using Equilibrium Optimizer Algorithm -- 1 Introduction -- 2 Problem Formulation -- 3 Proposed Equilibrium Optimizer Algorithm-Based Adaptive Volterra Noise Cancellation -- 3.1 Gbest -- 3.2 Exploration Stage (F) -- 3.3 Exploitation Stage (Rate of Generation G) -- 4 Simulation Outcomes -- 4.1 Qualitative Performance Analysis -- 4.2 Quantitative Performance Analysis -- 5 Conclusion and Scope -- References -- SHLPM: Sentiment Analysis on Code-Mixed Data Using Summation of Hidden Layers of Pre-trained Model -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 BERT -- 3.2 RoBERTa -- 3.3 SHLPM -- 4 Implementation Details -- 4.1 Dataset and Pre-processing -- 4.2 SHLPM-BERT -- 4.3 SHLPM-XLM-RoBERTa -- 5 Results and Discussion -- 6 Conclusion -- References -- Comprehensive Analysis of Online Social Network Frauds -- 1 Introduction -- 1.1 Statistics of Online Social Network Frauds -- 2 Interrelationship between OSN Frauds, Social Network Threats, and Cybercrime -- 3 Types of Frauds in OSN -- 3.1 Social Engineering Frauds (SEF) -- 3.2 Human-Targeted Frauds (Child/Adults) -- 3.3 False Identity -- 3.4 Misinformation -- 3.5 E-commerce Fraud (Consumer Frauds) -- 3.6 Case Study for Facebook Security Fraud -- 4 OSN Frauds Detection Using Machine Learning -- 4.1 Pros and Cons -- 5 Conclusion -- References -- Electric Vehicle Control Scheme for V2G and G2V Mode of Operation Using PI/Fuzzy-Based Controller -- 1 Introduction -- 2 Motivation -- 3 System Description -- 4 Mathematical Model Equipments Used -- 4.1 Bidirectional AC-DC Converter -- 4.2 Bidirectional Buck-Boost Converter -- 4.3 Battery Modeling -- 4.4 Control of 1-∅-Based Bidirectional AC-DC Converter Strategy -- 5 Fuzzy Logic Controller -- 6 Control Strategy -- 6.1 Constant Voltage Strategy.
6.2 Constant Current Strategy -- 7 Results and Discussion -- 7.1 PI Controller -- 7.2 Fuzzy Logic Controller -- 7.3 Comparison of Harmonic Profile -- 8 Conclusion -- References -- Experimental Analysis of Skip Connections for SAR Image Denoising -- 1 Introduction -- 2 Related Works -- 2.1 Residual Network -- 2.2 Existing ResNet-Based Denoising Works -- 3 Implementation of the Different Patterns of Skip Connections -- 3.1 Datasets and Pre-processing -- 3.2 Loss Function -- 4 Results and Discussions -- 4.1 Denoising Results on Synthetic Images -- 4.2 Denoising Results on Real SAR Images -- 5 Conclusion -- References -- A Proficient and Economical Approach for IoT-Based Smart Doorbell System -- 1 Introduction -- 2 Literature Review -- 3 System Design and Implementation -- 3.1 System Design -- 3.2 Implementation -- 4 Results and Discussion -- 4.1 Performance Results -- 4.2 Comparison with an Existing System -- 4.3 Cost Analysis -- 5 Limitations -- 6 Conclusion -- References -- Predicting Word Importance Using a Support Vector Regression Model for Multi-document Text Summarization -- 1 Introduction -- 2 Related Work -- 3 Description of Dataset -- 4 Proposed Methodology -- 4.1 Preprocessing -- 4.2 Word Importance Prediction Using Support Vector Regression Model -- 4.3 Sentence Scoring -- 4.4 Summary Generation -- 5 Evaluation, Experiment, and Results -- 5.1 Evaluation -- 5.2 Experiment -- 5.3 Results -- 6 Conclusion and Future Works -- References -- A Comprehensive Survey on Deep Learning-Based Pulmonary Nodule Identification on CT Images -- 1 Introduction -- 2 Datasets and Experimental Setup -- 2.1 LIDC/IDRI Dataset -- 2.2 LUNA16 Dataset -- 2.3 NLST Dataset -- 2.4 KAGGLE DATA SCIENCE BOWL (KDSB) Dataset -- 2.5 VIA/I-ELCAP -- 2.6 NELSON -- 2.7 Others -- 3 CAD System Structure -- 3.1 Data Acquisition -- 3.2 Preprocessing -- 3.3 Lung Segmentation. 3.4 Candidate Nodule Detection -- 3.5 False Positive Reduction -- 3.6 Nodule Categorization -- 4 CNN -- 4.1 Overview -- 4.2 CNN Architectures for Medical Imaging -- 4.3 Unique Characteristics of CNNs -- 4.4 CNN Software and Hardware Equipment -- 4.5 CNNs versus Conventional Models -- 5 Discussion -- 5.1 Research Trends -- 5.2 Challenges and Future Directions -- 6 Conclusion -- References -- Comparative Study on Various CNNs for Classification and Identification of Biotic Stress of Paddy Leaf -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Proposed Methods -- 3 Experimental Results -- 3.1 Hardware Setup -- 3.2 Time Analysis with respect to GPU and CPU -- 3.3 Performance Analysis for Keras and PyTorch -- 3.4 Performance Analysis of CNN Models -- 3.5 Comparison of the Proposed CNN with Other State-of-the-Art Works -- 4 Conclusion -- References -- Studies on Machine Learning Techniques for Multivariate Forecasting of Delhi Air Quality Index -- 1 Introduction -- 2 Materials and Methodology -- 2.1 Delhi AQI Multivariate Data -- 2.2 Methodology -- 3 Experimental Setup and Simulation Results -- 4 Contrast Analysis Considering Dimensionality Reduction -- 5 Conclusions -- References -- Fine-Grained Voice Discrimination for Low-Resource Datasets Using Scalogram Images -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 Collection of Voice Dataset -- 3.2 Preprocessing of Available Dataset to Increase the Trainable Samples -- 3.3 Classification of Phonemes Using Deep Convolutional Neural Network (DCNN)-Based Image Classifiers -- 4 Implementation Result and Analysis -- 5 Conclusion and Future Work -- References -- Sign Language Recognition for Indian Sign Language -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset -- 3.2 Data Preprocessing -- 3.3 Data Splitting -- 3.4 Data Augmentation -- 3.5 Model Compilation. 3.6 Model Training and Testing -- 4 Results -- 5 Novelty and Future Work -- 6 Conclusion -- References -- Buffering Performance of Optical Packet Switch Consisting of Hybrid Buffer -- 1 Introduction -- 2 Literature Survey -- 3 Description of the Optical Packet Switch -- 4 Simulation Results -- 4.1 Bernoulli Process -- 4.2 Results -- 5 Conclusions -- References -- Load Balancing using Probability Distribution in Software Defined Network -- 1 Introduction -- 2 Related Work -- 3 Grouping of Controllers in SDN -- 4 Load Balancing in SDN -- 4.1 Simulation and Evaluation Result -- 5 Conclusion -- References -- COVID Prediction Using Different Modality of Medical Imaging -- 1 Introduction -- 2 Principles of Support Vector Machine (SVM) -- 2.1 Linear Case -- 2.2 Nonlinear Case -- 3 Material and Methods -- 3.1 CT Image Dataset -- 3.2 X-Ray Image Dataset -- 3.3 Ultrasound Image Dataset -- 4 The Proposed Model -- 5 Experimental Result -- 6 Conclusion -- References -- Optimizing Super-Resolution Generative Adversarial Networks -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 3.1 Training Dataset -- 3.2 Test Dataset -- 4 Proposed Methodology -- 5 Performance Metrics -- 5.1 Peak Signal-to-Noise Ratio (PSNR) -- 5.2 Structural Similarity Index (SSIM) -- 6 Results and Discussion -- 7 Conclusion -- References -- Prediction of Hydrodynamic Coefficients of Stratified Porous Structure Using Artificial Neural Network (ANN) -- 1 Introduction -- 2 Stratified Porous Structure -- 3 Experimental Setup -- 4 Artificial Neural Network -- 4.1 Dataset Used for ANN -- 4.2 ANN Model -- 5 Results and Discussions -- 6 Conclusions -- References -- Performance Analysis of Machine Learning Algorithms for Landslide Prediction -- 1 Introduction -- 2 Literature Survey -- 3 Methodology of the Performance Analysis Work -- 3.1 Data Acquisition Layer -- 3.2 Fog Layer -- 3.3 Cloud Layer. 4 Performance Analysis and Results -- 5 Conclusion -- References -- Brain Hemorrhage Classification Using Leaky ReLU-Based Transfer Learning Approach -- 1 Introduction -- 2 Related Works -- 3 Materials and Method -- 3.1 Dataset -- 3.2 Transfer Learning -- 3.3 ResNet50 -- 4 Proposed Methodology -- 4.1 Input Dataset -- 4.2 Pre-processing -- 4.3 Network Training -- 4.4 Transfer Learning-Based Feature Extraction -- 5 Results -- 6 Conclusion -- References -- Factors Affecting Learning the First Programming Language of University Students -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Collection -- 3.2 Experimental Design -- 3.3 Data Analysis -- 4 Result -- 4.1 Findings -- 5 Decision and Conclusion -- References -- Nature-Inspired Hybrid Virtual Machine Placement Approach in Cloud -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 4 Proposed Framework -- 4.1 Intelligent Water Drops (IWD) Algorithm -- 4.2 Water Cycle Algorithm (WCA) -- 4.3 Intelligent Water Drop Cycle Algorithm (IWDCA) -- 5 Result -- 5.1 Experiment Setup -- 5.2 Simulation Analysis of IWDCA -- 6 Conclusion -- References -- Segmented ε-Greedy for Solving a Redesigned Multi-arm Bandit Environment -- 1 Introduction -- 2 Previous Works -- 3 Methodology -- 4 Results -- 5 Conclusion and Future Work -- References -- Data-Based Time Series Modelling of Industrial Grinding Circuits -- 1 Introduction -- 2 Formulation -- 2.1 Grinding Circuit -- 2.2 Least Square Support Vector Regression -- 2.3 Proposed Algorithm -- 3 Results and Discussions -- 3.1 Results of Proposed Algorithm -- 3.2 LS-SVR Model Performance -- 3.3 Comparison with Arbitrarily Selected Model -- 4 Conclusions -- References -- Computational Models for Prognosis of Medication for Cardiovascular Diseases -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References. Develop a Marathi Lemmatizer for Common Nouns and Simple Tenses of Verbs. |
| Record Nr. | UNINA-9910736981503321 |
|
Das Swagatam
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Communication and Intelligent Systems [[electronic resource] ] : Proceedings of ICCIS 2019 / / edited by Jagdish Chand Bansal, Mukesh Kumar Gupta, Harish Sharma, Basant Agarwal
| Communication and Intelligent Systems [[electronic resource] ] : Proceedings of ICCIS 2019 / / edited by Jagdish Chand Bansal, Mukesh Kumar Gupta, Harish Sharma, Basant Agarwal |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (517 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Artificial intelligence Electrical engineering Wireless communication systems Mobile communication systems Computational Intelligence Artificial Intelligence Communications Engineering, Networks Wireless and Mobile Communication |
| ISBN | 981-15-3325-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Extremely High Capacity, Secure, Image Steganography based on composite Edge Detection, with message Integrity -- A Distributed Fault Analysis (DFA) Method for Fault Tolerance in High-Performance Computing Systems -- Software Cost Estimation For Python Projects Using Genetic Algorithm -- Performance Evaluation of Queue with Negative Arrivals, Second Optional Service and Unreliable Server in Communication Networks -- An Empirical Analysis on Retrieval of Math Information from the Scientific Documents -- One shot Digit classification based on Human concept learning -- Appropriateness of Machine Learning Techniques for TCP with MANETs. |
| Record Nr. | UNINA-9910484226803321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computationally intelligent systems and their applications / / Editor, Jagdish Chand Bansal [and three others]
| Computationally intelligent systems and their applications / / Editor, Jagdish Chand Bansal [and three others] |
| Pubbl/distr/stampa | Gateway East, Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (171 pages) |
| Disciplina | 006.3 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Artificial intelligence
Computational intelligence Intel·ligència computacional |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 981-16-0407-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910484345703321 |
| Gateway East, Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computer vision and machine learning in agriculture . Volume 2 / / Mohammad Shorif Uddin and Jagdish Chand Bansal
| Computer vision and machine learning in agriculture . Volume 2 / / Mohammad Shorif Uddin and Jagdish Chand Bansal |
| Autore | Uddin Mohammad Shorif |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (269 pages) |
| Disciplina | 338.10285 |
| Collana | Algorithms for Intelligent Systems |
| Soggetto topico |
Artificial intelligence - Agricultural applications
Machine learning - Development |
| ISBN |
981-16-9991-7
981-16-9990-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910743346603321 |
|
Uddin Mohammad Shorif
|
||
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computer vision and machine learning in agriculture / / Mohammad Shorif Uddin and Jagdish Chand Bansal, Editors
| Computer vision and machine learning in agriculture / / Mohammad Shorif Uddin and Jagdish Chand Bansal, Editors |
| Pubbl/distr/stampa | Gateway East, Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (180 pages) : illustrations |
| Disciplina | 630.2085 |
| Collana | Algorithms for Intelligent Systems |
| Soggetto topico |
Computational intelligence
Robotics Machine learning Visió per ordinador Aprenentatge automàtic Programari d'aplicació Agricultura |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 981-336-424-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910484429803321 |
| Gateway East, Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computer vision and robotics : proceedings of CVR 2021 / / edited by Jagdish Chand Bansal, Andries Engelbrecht, Praveen Kumar Shukla
| Computer vision and robotics : proceedings of CVR 2021 / / edited by Jagdish Chand Bansal, Andries Engelbrecht, Praveen Kumar Shukla |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (541 pages) |
| Disciplina | 929.605 |
| Collana | Algorithms for intelligent systems |
| Soggetto topico | Computer vision |
| ISBN |
981-16-8224-0
981-16-8225-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | AI Techniques for Swedish Leaf Classification Designing a Recommender System for Articles using Implicit Feedback Personality Prediction based on Twitter Tweets Music Therapy for Mood Transformation based on Deep Learning Framew orkRice Crop Diseases and Pest Detection using Edge Detec-tion Techniques and Convolution Neural Netw orkSpatial Analyses of Cyclone Amphan Induced Flood Inundation Mapping Using Sentinel-1A SAR Images Through GEE CloudClassification through Data Mining AlgorithmEarly Detection of Diabetic Retinopathy using Multimodal ApproachIntelligent Techniques for Crowd Detection And People Counting- A Systematic_StudyTwitter Sentiment Analysis of Public Opinion on COVID-19 Vaccines |
| Record Nr. | UNINA-9910743214103321 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Evolutionary and Swarm Intelligence Algorithms / / edited by Jagdish Chand Bansal, Pramod Kumar Singh, Nikhil R. Pal
| Evolutionary and Swarm Intelligence Algorithms / / edited by Jagdish Chand Bansal, Pramod Kumar Singh, Nikhil R. Pal |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (X, 190 p. 57 illus., 21 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Computational intelligence
Artificial intelligence Computational Intelligence Artificial Intelligence |
| ISBN | 3-319-91341-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Swarm and Evolutionary Computation -- Particle Swarm Optimization -- Artificial Bee Colony Algorithm Variants and Its Application to Colormap Quantization -- Spider Monkey Optimization Algorithm -- Genetic Algorithm and Its Advances in Embracing Memetics -- Constrained Multi-Objective Evolutionary Algorithm -- Genetic Programming for Classification and Feature Selection -- Genetic Programming for Job Shop Scheduling -- Evolutionary Fuzzy Systems: A Case Study for Intrusion Detection Systems. |
| Record Nr. | UNINA-9910483134003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Fourth Congress on Intelligent Systems : CIS 2023, Volume 3
| Fourth Congress on Intelligent Systems : CIS 2023, Volume 3 |
| Autore | Kumar Sandeep |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2024 |
| Descrizione fisica | 1 online resource (426 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
KBalachandran
KimJoong Hoon BansalJagdish Chand |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 981-9990-43-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- Insights into Age-Related Macular Degeneration Detection: A Comprehensive Review of OCT Image Analysis -- 1 Introduction -- 1.1 Drusen -- 1.2 Choroidal Neovascularization (CNV) -- 2 Related Work -- 3 Review Analysis -- 3.1 Convolutional Neural Networks (CNNs) -- 3.2 Generative Adversarial Networks (GANs) -- 4 Conclusion -- References -- An Adaptive Detection Mechanism for IoT Devices Anomalies Using AI/ML Based on User Pattern -- 1 Introduction -- 1.1 Background -- 2 Related Work -- 3 Proposed Framework -- 3.1 AI Model -- 3.2 Data Preparation and Preprocessing -- 3.3 Model Flow -- 4 Conclusion and Future Scope -- References -- Automated Verification of the Correctness of Transitions Between Elements of a Mobile Application Using Source Code Generation Tools -- 1 Introduction -- 2 Description of the Study -- 3 Universal Automation Tool for Testing Android and iOS Applications -- 3.1 Page Object Generation Module -- 3.2 Module for Generating Test Scenarios -- 3.3 Module for Receiving Application Assemblies -- 3.4 Mobile Device Farm Integration Module -- 4 Discussion -- 5 Conclusions -- References -- Mute Mate: An Advanced Lip-Reading Solution for Mute Participants in Virtual Conferences -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Dataset Description -- 3.2 Data Preprocessing -- 3.3 Model -- 4 Results -- 5 Conclusion -- References -- An Insightful Analysis of Preprocessing Methods Used in EEG Signals for Computer-Assisted Cognitive Domain -- 1 Introduction -- 2 Material and Methods -- 3 Preprocessing Taxonomy for EEG Signals -- 3.1 Importing Raw Data -- 3.2 Downsampling -- 3.3 Filtering -- 3.4 Re-referencing the Data -- 3.5 Removing Bad Segments -- 3.6 Removing Bad Channels -- 3.7 Artifact Removal -- 3.8 Epoching -- 4 Conclusions and Future Scope -- References.
Understanding Individual Emotional Responses: Analyzing Variations and Introducing Personal Emotional Bias in Kannada Opinion Data Set -- 1 Introduction -- 2 Related Work -- 3 Data Set Collection and Annotation Procedure -- 3.1 Data Collection -- 3.2 Annotation Procedure -- 4 Personal Emotional Bias-PEB -- 5 Experimentation and Results -- 5.1 Multivariate Regression -- 6 Conclusions -- References -- A Survey on Feature Selection, Classification, and Optimization Techniques for EEG-Based Brain-Computer Interface -- 1 Introduction -- 2 Literature Review -- 2.1 EEG-Based BCI -- 2.2 Feature Selection for BCI -- 2.3 Classification Method-Based BCI -- 2.4 Optimization Methods in BCI -- 3 Research Challenges, Gaps and Limitations -- 4 Conclusion -- References -- Mean Teacher Model with Consistency Regularization for Semi-supervised Detection of COVID-19 Using Cough Recordings -- 1 Introduction -- 2 Related Works -- 3 Materials and Methodology -- 3.1 Dataset -- 3.2 Data Preprocessing -- 3.3 Data Augmentation -- 3.4 Feature Extraction and Feature Selection -- 3.5 Proposed Framework for COVID-19 Classification -- 3.6 Performance Metrics -- 4 Result and Discussion -- 4.1 Cross-Validation Results -- 4.2 Test Set Performance -- 5 Conclusion -- References -- Multimodal Early Fusion Strategy Based on Deep Learning Methods for Cervical Cancer Identification -- 1 Introduction -- 2 Methodology -- 2.1 Transfer Learning -- 2.2 Novel Fusion Strategy -- 3 Experimental Results -- 3.1 Dataset -- 3.2 Implementation Environment -- 3.3 Evaluation Metrics -- 4 Conclusion -- References -- Comparing Online and Face-to-Face Training with Employees Perspective -- 1 Introduction -- 2 Literature Review -- 3 Objective -- 4 Methodology -- 5 Points Received from Interview -- 6 Questionnaire Analysis -- 7 Discussion and Implications -- 8 Suggestions -- References. Enhancing Chatbot Interaction with Emotion Detection for Improved Understanding: EmoBot -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Data Preparation -- 3.2 Model Architecture -- 3.3 Training the Model -- 3.4 Emotion Prediction -- 3.5 Streamlit and LangChain Integration -- 4 Results -- 5 Conclusion and Future Works -- References -- Bridging Language Barriers: Exploring Hindi-to-English Speech-to-Speech Translation for Multilingual Communication -- 1 Introduction -- 2 Related Works -- 3 Dataset Description -- 4 Methodology -- 4.1 Speech-To-Text -- 4.2 Text Translation -- 4.3 Text-To-Speech -- 5 Results and Discussion -- 5.1 Speech-to-Text -- 5.2 Text Translation -- 5.3 Text-To-Speech -- 6 Conclusion and Future Works -- References -- CNN-Based Assistive Technology Platform for Hearing Impairments Individuals -- 1 Introduction -- 2 Literature Survey -- 3 Proposed System -- 3.1 Dataset Collection -- 3.2 Data Augmentation -- 3.3 Feature Extraction and Model Training -- 3.4 Mobile Application Development -- 4 Implementation and Results -- 4.1 Performance Evaluation -- 4.2 Results -- 5 Conclusion -- References -- Underwater Image Denoising and Semantic Segmentation -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Two-Dimensional-Variational Mode Decomposition -- 4 Findings and Analysis of the Experiment -- 4.1 Description of the Dataset -- 5 Conclusion -- References -- Ensuring Audit-Free Cloud Using CFF with AES-SHA in Cloud Computing -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Approach -- 4 Segments Description -- 5 Performance Evaluation -- 6 Conclusion -- References -- DC-CNNPAD to Enhance the Detection Rate for Iris Presentation Attack -- 1 Introduction -- 2 Problem Statement -- 3 Related Work -- 4 Proposed Methodology -- 4.1 Data Pre-processing -- 4.2 Dual-Channel CNN PAD Design -- 4.3 Fusion Techniques. 5 Results and Analysis -- 6 Conclusion -- References -- Augmented Reality based Navigation for Indoor Environment using Unity Platform -- 1 Introduction -- 2 Literature Review -- 3 Proposed Work -- 3.1 Prototype and Testing -- 4 Results -- 5 Conclusion -- References -- Identification of Phishing URLs Using Machine Learning Models -- 1 Introduction -- 2 Literature Survey -- 3 Models Comparison -- 3.1 Standalone Models -- 3.2 Ensemble Models -- 3.3 Deep Learning Models -- 3.4 Model Selection -- 4 Dataset -- 5 Features -- 6 Conclusion -- References -- Segmentation of Brain Tumours Using Optimised U-Net Architecture -- 1 Introduction -- 2 Literature Review -- 3 Existing System and Proposed System -- 4 Module Description -- 5 Design Phase -- 5.1 U-Net Architecture -- 5.2 OpenCV -- 5.3 Scikit-Image -- 6 Dataset Models -- 6.1 Flair -- 6.2 T1 -- 6.3 T1ce -- 6.4 T2 -- 6.5 Dataset Models Design -- 7 Implementation and Testing -- 7.1 Input and Output -- 8 Experimental Results -- 8.1 Efficiency of the Proposed System -- 8.2 Training and Prediction -- 9 Conclusion and Future Improvements -- References -- On script upper CmathcalC-Perfection of Tensor Product of Graphs -- 1 Introduction -- 2 Preliminaries -- 3 Results on script upper CmathcalC-Perfection on Tensor Product of Graphs -- 4 Summary and Conclusion -- References -- War Strategy Optimization for Optimal Integration of Public Fast Charging Stations in Radial Feeders -- 1 Introduction -- 2 Modeling of Concepts -- 3 Problem Formulation -- 4 War Strategy Optimization -- 4.1 Attack Strategy -- 4.2 Rank and Weight Updation -- 4.3 Defense Strategy -- 4.4 Replacement/Relocation of Weak Soldiers -- 5 Simulation Results -- 5.1 Base Case -- 5.2 Network Performance with Distributed EV Load Penetration -- 5.3 Network Performance with Optimal Allocation of PFCSs -- 6 Conclusion -- References. Comparative Analysis of Blockchain Technology in Healthcare Data Management -- 1 Introduction -- 2 Literature Survey -- 2.1 Research on Blockchain Technology in Healthcare -- 2.2 Blockchain Technology and Its Applications -- 2.3 Traditional Security Frameworks in Healthcare -- 3 Blockchain Technology -- 3.1 Blockchain Technology in Healthcare Management -- 4 Advantages of Blockchain Technology Over Traditional Security Frameworks -- 5 Case Studies and Real-World Implementations -- 6 Challenges and Limitations of Blockchain Technology -- 7 Conclusion -- References -- Certificate Generation and Validation Using Blockchain -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Architecture Diagram -- 4 Implementation -- 5 Results and Discussion -- 6 Conclusion -- References -- A Review on Deep Learning Algorithms in the Detection of Autism Spectrum Disorder -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Convolutional Neural Network -- 3.2 Recurrent Neural Network -- 3.3 Long Short-Term Memory Network -- 3.4 Convolution Recurrent Neural Network (CRNN) -- 4 Discussions -- 5 Conclusion -- References -- Key Elements for Managing Autonomous Organizational Systems -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Autonomous Organizational Systems -- 5 Decision Making -- 6 Applicable Theories -- 7 Key Elements -- 7.1 Technical Elements -- 7.2 Social (Human) Elements -- 7.3 Conceptual Framework of the Key Elements -- 8 Conclusion -- References -- Summarization of Daily News Using TextRank and TF-IDF Algorithm -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 TextRank Algorithm -- 3.2 TF-IDF Algorithm -- 4 Performance Evaluation Measures -- 5 Experimental Results -- 5.1 Original Text -- 5.2 Summary Produced by TextRank Algorithm -- 5.3 Summary Produced by TF-IDF Algorithm -- 6 Observations and Findings. References:. |
| Record Nr. | UNINA-9910845500303321 |
|
Kumar Sandeep
|
||
| Singapore : , : Springer Singapore Pte. Limited, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
