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.
Computational Intelligence in Machine Learning : Proceedings of the 2nd International Conference ICCIML 2022
| Computational Intelligence in Machine Learning : Proceedings of the 2nd International Conference ICCIML 2022 |
| Autore | Gunjan Vinit Kumar |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (686 pages) |
| Altri autori (Persone) |
KumarAmit
ZuradaJacek M SinghSri Niwas |
| Collana | Lecture Notes in Electrical Engineering Series |
| ISBN | 981-9979-54-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Contents -- About the Editors -- A Deep Learning Method for Autism Spectrum Disorder -- 1 Introduction -- 2 Transfer Learning -- 3 Experiments -- 3.1 Data Set -- 3.2 VGG-16 -- 4 Results and Discussion -- 5 Conclusion -- References -- Cyber-Attacks and Anomaly Detection in Networking Based on Deep Learning-A Survey -- 1 Introduction -- 2 Taxonomy on Anomaly Detection of Cyberattacks in Networking -- 2.1 Machine Learning -- 2.2 Supervised Learning -- 2.3 Unsupervised Learning -- 2.4 Semi-supervised Learning -- 3 Literature -- 4 Comparative Analysis -- 5 Problem Statement -- 6 Conclusion -- References -- AI-Enabled Analysis of Climate Change on Agriculture and Yield Prediction for Coastal Area -- 1 Introduction -- 2 Literature Survey -- 3 Implementation -- 3.1 LSTM Model -- 3.2 Random Forest Model -- 3.3 Predicted Temperature and Actual Temperature -- 3.4 Shows the Baseline Predicted Example -- 3.5 Shows the Prediction Weather -- 3.6 Shows the Alternate Crop -- 4 Result Analysis -- 5 Conclusion and Future Scope -- References -- Deep Learning Methods for Predicting Severity for Diabetic Retinopathy on Retinal Fundus Images -- 1 Introduction -- 2 DR Features -- 3 Literature Review -- 4 Proposed Methodology -- 5 Conclusion -- References -- Hate Text Finder Using Logistic Regression -- 1 Introduction -- 2 Related Work -- 3 Proposed System -- 4 Working of Proposed System -- 5 Results -- 6 Conclusion -- 7 Future Scope -- References -- Automated Revealing and Warning System for Pits and Blockades on Roads to Assist Carters -- 1 Introduction -- 2 Pothole and Obstacle Detection Working Model -- 3 Implementation of Pothole and Obstacle Detection -- 3.1 Stage 1: When an Obstacle is Detected -- 3.2 Stage 2: When the Working Model Detects Potholes -- 4 Conclusion -- References.
Green Data Center Power Flow Management with Renewable Energy Sources and Interlinking Converter -- 1 Introduction -- 2 Uninterruptible Power Supply -- 3 Proposed Framework for Green Data Center -- 4 Simulation Result -- 5 Conclusion -- References -- Design of Grid-Connected Battery Storage Wave Energy and PV Hybrid Renewable Power Generation -- 1 Introduction -- 2 Problem Formulation -- 2.1 Scenario 1: Rising Voltage Profile -- 2.2 Scenario 2: Backward Power Flow -- 2.3 Scenario 3: An Increase in the Fault Current's Size -- 2.4 Scenario 4: The Traditional Method is to Estimate the EG's Penetration Limitations -- 3 Proposed Solutions -- References -- Power Quality Enhancement with PSO-Based Optimisation of PI-Based Controller for Active Power Filter -- 1 Introduction -- 2 Power Quality -- 2.1 Power Quality Problems -- 2.2 The Benefits of Power Quality -- 3 PSO -- 4 Optimisation of PI Controller By Using PSO -- 5 Conclusion -- References -- Monitoring and Control of Motor Drive Parameters Using Internet of Things Protocol for Industrial Automation -- 1 Introduction -- 1.1 Automation -- 1.2 Material and Method -- 1.3 Relay and Contactor -- 2 Architecture of SCADA -- 2.1 Human-Machine Interface (HMI) -- 2.2 Internet of Things SCADA System -- 2.3 Data Communication -- 2.4 Data Presentation -- 2.5 Data Acquisition -- 3 Conclusion -- References -- Switching Loss Comparison of a Cascaded Diode-Clamped Inverter with Conventional Multilevel Inverters -- 1 Introduction -- 2 Inverter Topologies -- 2.1 Cascaded H-Bridge Inverter (CHBI)-(9-Level) -- 2.2 Diode-Clamped Multilevel Inverter (DCMLI)-(Five-Level) -- 2.3 Hybrid Inverter-Cascaded Diode-Clamped Inverter (CDCI)-(Nine-Level) -- 3 Switching Loss Calculation -- 4 Simulation and Results -- 4.1 Cascaded H-Bridge Inverter (Nine-Level)-Results -- 4.2 Diode-Clamped Multilevel Inverter (FiveLevel)-Results. 4.3 Cascaded Diode-Clamped Inverter (Nine-Level)-Results -- 4.4 Comparision of CHBI, DCMLI and CDCI -- 5 Conclusion -- References -- An Energy-Efficient Mechanism Using Blockchain Technology for Machine-Type Communication in LTE Network -- 1 Introduction -- 2 Related Work -- 3 Proposed Cluster-Based Energy-Efficient Cluster Head Using Blockchain -- 3.1 Distance (fdistance) -- 3.2 Delay (fdelay) -- 3.3 Energy (fenergy) -- 3.4 Objective Function -- 3.5 WTL Algorithm for Optimal Cluster Head Selection -- 3.6 Blockchain Technology -- 4 Results and Discussions -- 4.1 Simulation Procedure -- 5 Conclusion -- References -- Comparison of Echo State Network with ANN-Based Forecasting Model for Solar Power Generation Forecasting -- 1 Introduction -- 2 Methodology -- 2.1 Artificial Neural Network -- 2.2 Echo State Network -- 3 Statistical Methods -- 4 Result and Discussion -- 5 Conclusion -- References -- A Grey Wolf Integrated with Jaya Optimization Based Route Selection in IoT Network -- 1 Introduction -- 2 Literature Review -- 3 Proposed Routing Strategy in IoT -- 3.1 Computation of Fitness Value -- 3.2 Optimal Node Selection Using GWJO Model -- 3.3 Route Establishment -- 4 Results -- 4.1 Simulation Set-Up -- 5 Conclusion -- References -- Secure Software Development Life Cycle: An Approach to Reduce the Risks of Cyber Attacks in Cyber Physical Systems and Digital Twins -- 1 Introduction -- 2 Literature Survey -- 2.1 Cyber Physical Systems and Their Attacks? -- 2.2 Advantages of Digital Twin Over Cyber Physical System -- 2.3 Disadvantages of DT -- 2.4 Cyber Digital Twin -- 2.5 How Secure Are CDTs? -- 3 Methodology -- 3.1 Secure Software Development Life Cycle (Proposed Solution) -- 3.2 Why SSDLC and not SDLC? -- 3.3 Detailed Look at the SSDLC -- 4 Conclusion -- References. Social Networks and Time Taken for Adoption of Organic Food Product in Virudhunagar District-An Empirical Study -- 1 Introduction -- 2 Related Works -- 3 Conceptual Framework -- 4 Objectives of the Study -- 5 Area of the Study, Sample Framework and Procedure -- 6 Days to Purchase -- 7 Members of the Social Group -- 8 Reason to Join in the Group -- 9 The Frequency of Participation in the Group -- 10 Information Trust by the Respondents -- 11 Convey Information About New Product -- 12 Cost Spend by the Respondents for Passing the Information -- 13 Like to Spread the Information -- 14 Quantity of Passing of Information -- 15 Hypothesis -- 16 Kruskal-Wallis Test -- 17 Living Place and Adoption of New Product in the Market -- 18 Chi-Square Tests -- 19 Age Group and Information Passing -- 20 Chi-Square Test -- 21 Exponential Smoothing for Applying Roger's Model in Identifying the Adoption of Organic Food Product -- 22 Exponential Growth -- 23 Findings and Discussion -- References -- Usage of Generative Adversarial Network to Improve Text to Image Synthesis -- 1 Introduction -- 2 Literature Survey -- 2.1 Generative Adversarial Networks -- 2.2 Text to Photo-Realistic Image Synthesis with Stacked GAN -- 2.3 Image Generation from Scene Graphs -- 2.4 Fine Grained Text to Image Generation with Attentional Generative Adversarial Networks (Attn GAN) -- 2.5 Realistic Image Synthesis with Stacked Generative Adversarial Networks (Stack GAN++) -- 3 Methodology -- 3.1 Defining Goal -- 3.2 Researching Previous Attempts -- 3.3 Defining Approach -- 3.4 Algorithm -- 4 Experiments and Results -- 4.1 Experiment Setting -- 4.2 Effectiveness of New Modules -- 4.3 Component Analysis of AATM -- 4.4 Component Analysis of SDM -- 4.5 Comparison of KT GAN with Other GAN Models -- 4.6 Visualization -- 5 Conclusion -- References. Recurrent Neural Network-Based Solar Power Generation Forecasting Model in Comparison with ANN -- 1 Introduction -- 2 Methodology -- 2.1 Artificial Neural Network (ANN) -- 2.2 Recurrent Neural Network (RNN) -- 3 Statistical Measures -- 4 Result and Discussion -- 5 Conclusion -- References -- Android Malware Detection Using Genetic Algorithm Based Optimized Feature Selection and Machine Learning -- 1 Introduction -- 1.1 A Subsection Sample -- 2 Proposed Method -- 2.1 Supervised Classification (Training Dataset) -- 2.2 Supervised Classification (Test Dataset) -- 2.3 System Design -- 2.4 Use Case Diagram -- 3 Testing and Implementation -- 4 Results and Discussion -- 5 Conclusion -- References -- Mental Health Disorder Predication Using Machine Learning for Online Social Media -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Collection -- 3.3 Check Category -- 3.4 Check Wordlist -- 4 Machine Learning Models -- 5 Result and Discussion -- 6 Conclusion -- References -- An Application on Sweeping Machines Detection Using YOLOv5 Custom Object Detection -- 1 Introduction -- 2 Related Work -- 2.1 YOLOv5 -- 2.2 Model Description -- 3 Proposed System -- 3.1 Dataset -- 3.2 Manual Labeling -- 3.3 Augmentation -- 4 Training -- 5 Results -- 6 Command -- 7 Conclusion and Future Work -- References -- Analyze and Detect Lung Disorders Using Machine Learning Approaches-A Systematic Review -- 1 Introduction -- 2 State-of-Art: Overview -- 3 Dataset Availability -- 4 Methodology -- 5 Conclusions and Future Work -- References -- A Study on Predicting Skilled Employees' Using Machine Learning Techniques -- 1 Introduction -- 2 Related Work -- 3 Classifier Construction -- 3.1 Objectives and Problem Definition -- 3.2 Data Collection and Understanding Process -- 3.3 Data Preparation and Pre-processing -- 4 Modeling and Experiments. 5 Comparative Analysis and Discussion:. |
| Record Nr. | UNINA-9910838282603321 |
Gunjan Vinit Kumar
|
||
| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computational Methods in Molecular Imaging Technologies / / by Vinit Kumar Gunjan, Fahimuddin Shaik, C Venkatesh, M. Amarnath
| Computational Methods in Molecular Imaging Technologies / / by Vinit Kumar Gunjan, Fahimuddin Shaik, C Venkatesh, M. Amarnath |
| Autore | Gunjan Vinit Kumar |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (74 pages) : illustrations |
| Disciplina | 616.0754 |
| Collana | SpringerBriefs in Forensic and Medical Bioinformatics |
| Soggetto topico |
Biomedical engineering
Signal processing Image processing Speech processing systems Radiology Optical data processing Health informatics Bioinformatics Biomedical Engineering and Bioengineering Signal, Image and Speech Processing Imaging / Radiology Computer Imaging, Vision, Pattern Recognition and Graphics Health Informatics Computational Biology/Bioinformatics |
| ISBN | 981-10-4636-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1.Introduction -- 2.Artifacts Correction in MRI Images -- 3.Spiral Cone-beam CT Reconstruction -- 4.Visual Quality Improvement of CT Image Reconstruction with Quantitative Measures -- 5.References. |
| Record Nr. | UNINA-9910254313603321 |
|
Gunjan Vinit Kumar
|
||
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Modern Approaches in IoT and Machine Learning for Cyber Security [[electronic resource] ] : Latest Trends in AI / / edited by Vinit Kumar Gunjan, Mohd Dilshad Ansari, Mohammed Usman, ThiDieuLinh Nguyen
| Modern Approaches in IoT and Machine Learning for Cyber Security [[electronic resource] ] : Latest Trends in AI / / edited by Vinit Kumar Gunjan, Mohd Dilshad Ansari, Mohammed Usman, ThiDieuLinh Nguyen |
| Autore | Gunjan Vinit Kumar |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (415 pages) |
| Disciplina | 005.8 |
| Altri autori (Persone) |
AnsariMohd Dilshad
UsmanMohammed (Electrical engineering professor) NguyenThiDieuLinh |
| Collana | Internet of Things, Technology, Communications and Computing |
| Soggetto topico |
Cooperating objects (Computer systems)
Telecommunication Data protection Quantitative research Cyber-Physical Systems Communications Engineering, Networks Data and Information Security Data Analysis and Big Data |
| ISBN | 3-031-09955-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Being secure, vigilant and resilient in the age of Industry 4.0 -- Facing new cyber risks in the age of smart production -- Leveraging AI for threat detection -- Being resilient when attacks inevitably hit home -- Security for the Industrial Internet of Things -- Reinventing the Internet to Secure the Digital Economy -- The future of cybersecurity -- Adapting data science for security challenges -- Big data analytics for cybersecurity -- Data Analytics and Decision Support for Cybersecurity -- Data Science in Cybersecurity and Cyberthreat Intelligence -- Integrating cyber security and data science for social media -- Data warehousing and data mining techniques for cyber security -- Machine learning and deep learning methods for cybersecurity -- Machine Learning and Big Data Processing for Cybersecurity Data Analysis -- Blockchain's roles in strengthening cybersecurity and protecting privacy -- Using virtual environments for the assessment of cybersecurity issues in IoT scenarios -- Security considerations for secure and trustworthy smart home system in the IoT environment -- Cyber security challenges for IoT-based smart grid networks -- Evaluating critical security issues of the IoT world -- Internet of Things security and forensics -- Applying Artificial Intelligence Techniques to Prevent Cyber Assaults -- Cyber security and the role of intelligent systems in addressing its challenges -- Cyber security of water SCADA systems -- Bio-inspiring cyber security and cloud services -- AI enabled blockchain smart contracts -- Cyber security and the evolution in intrusion detection systems -- A cyber security study of a SCADA energy management system -- Security analysis and recommendations for AI/ML enabled automated cyber medical systems -- Making knowledge tradable in edge-AI enabled IoT -- Artificial intelligence and national security -- Conclusion. |
| Record Nr. | UNINA-9910770257603321 |
|
Gunjan Vinit Kumar
|
||
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Proceedings of 4th International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications : Icmisc 2023
| Proceedings of 4th International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications : Icmisc 2023 |
| Autore | Gunjan Vinit Kumar |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (792 pages) |
| Disciplina | 307.760285 |
| Altri autori (Persone) | ZuradaJacek M |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 981-9994-42-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- About the Editors -- Smart Glasses for Visually Impaired -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Results and Discussion -- 5 Conclusion -- References -- Stock Market Prediction Using Machine Learning: A Review -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Conclusion -- References -- Implementation of Dual-Band Dielectric Resonator Antenna for 5G Applications -- 1 Introduction -- 2 Literature Survey -- 3 Antenna Configuration -- 3.1 Antenna Feed -- 4 Simulation Results -- 5 Conclusion -- References -- Defect Detection in Metal Surfaces Using Computer Vision -- 1 Introduction -- 2 Literature Review -- 3 Research Mythology -- 4 Methodology and Implementation -- 5 Data Analysis -- 6 Results -- 7 Conclusion -- References -- Liver Cirrhosis Prediction Using Machine Learning Classification Techniques -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Data Preprocessing -- 3.4 Feature Selection -- 3.5 Classification Using ML Algorithms -- 3.6 Evaluation Metrics -- 4 Experimental Results -- 4.1 Precision Recall Curves -- 4.2 Evaluation Metrics -- 5 Conclusions -- References -- A Recent Survey on Risk Factors Affecting the Blood Pressure in India -- 1 Introduction -- 2 Motivation -- 3 Factors Affecting the BP -- 3.1 Age's Effect on BP -- 3.2 Obesity Effect on BP -- 3.3 Cholesterol Effect on BP -- 3.4 Anger Effect on BP -- 3.5 Anxiety Effect on BP -- 3.6 Impact of Salt on BP -- 3.7 Impact of Alcohol on BP -- 3.8 Impact of Smoking on BP -- 3.9 Impact of Socioeconomic Status on BP -- 4 Hypertension Effects on the Body -- 5 Conclusion -- References -- Real-Time Monitoring System for Breakdown Analysis and OEE in the Wire Drawing Industry -- 1 Introduction -- 2 Methodology -- 3 Current Scenario in the Wire Drawing Industry.
4 Proposed Solutions -- 5 Requirements for Successful Implementation -- 6 Results Achieved Through the Use of the System -- 7 Results -- 8 Conclusion -- References -- Tooth Sensitivity Device-Detection and Diagnosing of Sensitivity in the Dental Pulp -- 1 Introduction -- 2 Literature Review -- 3 Proposed Method -- 3.1 Hot Stimulus and Cold Stimulus -- 4 Result and Discussion -- 5 Conclusion -- References -- Recognition of Skin Cancer -- 1 Introduction -- 2 Proposed System -- 3 Literature Review -- 4 Module Description Image Acquisition -- 5 Architecture -- 6 System Perpetration -- 7 The MATLAB Language -- 8 Software Description MATLAB -- 9 Result and Discussion -- 10 Conclusion and Future Scope -- References -- IoT-Based Smart Street Lighting Surveillance System -- 1 Introduction -- 2 Literature Survey -- 3 Proposed System -- 3.1 Description -- 4 Design Methodology -- 5 Flow Chart of Smart Lighting System -- 6 Advantages -- 7 Limitations -- 8 Result -- 9 Conclusion -- References -- Rock Segmentation of Real Martian Scenes Using Dual Attention Mechanism-Based U-Net -- 1 Introduction -- 2 Materials and Methodology -- 2.1 About Dataset -- 2.2 Methodology -- 3 Result and Discussion -- 4 Conclusion -- References -- IAAS: IoT-Based Automatic Attendance System with Photo Face Recognition in Smart Campus -- 1 Introduction -- 2 Literature Review -- 3 Algorithms -- 4 Problem Statement -- 5 Objective -- 6 System Design and Architecture -- 7 System Requirements -- 7.1 Hardware Requirements -- 7.2 Software Requirements -- 8 System Implementation and Methodology -- 9 Results -- 10 Conclusion -- References -- Hardware Implementation of Moving Object Detection Using Background Subtraction Algorithm -- 1 Introduction -- 2 Literature Survey -- 3 Theoretical Aspects of Motion Detection. 4 Proposed Hardware Architecture for Motion Detection Using Background Subtraction -- 5 Results -- 5.1 Hardware Utilization -- 5.2 Object Detection Output -- 5.3 Comparison with Existing Work -- 6 Conclusion -- References -- Crime Pattern Identification and Prediction Using Machine Learning -- 1 Introduction -- 2 Methodology -- 2.1 Logistic Regression -- 2.2 Random Forest -- 2.3 Linear Regression -- 2.4 AdaBoost Classifier -- 2.5 K-Nearest-Neighbor -- 2.6 Support Vector Machine -- 2.7 Decision Tree -- 2.8 Data Pre-processing -- 3 Results -- 4 Conclusion -- References -- IMICE: An Improved Missing Data Imputation Using Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Principal Component Analysis -- 3.2 IMICE -- 3.3 Flowchart -- 4 Experimental Setup -- 4.1 Diabetes Dataset -- 4.2 Results -- 5 Conclusion and Future Work -- References -- Analyzing Students' Opinion on E-Learning-Indian Students' Perspective -- 1 Introduction -- 2 Literature Survey -- 2.1 Research Gap -- 3 Methodology -- 3.1 Data Collection -- 4 Result and Discussion -- 5 Conclusion -- References -- Rash Driving Detection and Alerting System -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Design and Implementation -- 5 Result -- 6 Conclusion -- References -- Logistic-Based OVA-CNN Model for Alzheimer's Disease Detection and Prediction Using MR Images -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Pre-processing -- 3.2 OVA-CNN: Theoretical Concept -- 3.3 OVA-CNN: Architectural Design -- 4 Results and Discussion -- 4.1 Dataset and Experimental Setup -- 5 Discussion -- 6 Conclusion -- References -- Comparative Study of CNNs for Camouflaged Object Detection -- 1 Introduction -- 2 Related Work -- 2.1 Camouflaged Object Detection Using SINet -- 2.2 Camouflaged Object Detection Using ERRNet -- 2.3 Camouflaged Object Detection Using DGNet. 2.4 Camouflaged Object Detection Using SINet-V2 -- 2.5 Camouflaged Object Detection Using HITNet -- 3 Proposed Work -- 4 Results and Discussion -- 4.1 Comparison of Different Models -- 4.2 Analysis of Datasets Used -- 4.3 Evaluation Metrics -- 4.4 Quantization -- 4.5 Deploying the Model on Edge Device -- 5 Future Scope -- 6 Conclusion -- References -- 3D Avatar Reconstruction Using Multi-level Pixel-Aligned Implicit Function -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 FSRCNN -- 3.2 The Coarse-Level Module -- 3.3 The Fine-Level Modules Fine-Level Module -- 3.4 Multi-layer Perceptron (MLP) -- 4 Experimental Results -- 4.1 Dataset Description -- 5 Conclusion -- References -- Helmet Detection Using YOLO-v5 and Paddle OCR for Embedded Systems -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 Helmet Detection -- 3.2 License Plate Detection -- 4 Results -- 4.1 Dataset Description -- 4.2 Evaluations Metrics -- 5 Conclusion -- References -- DefogNet: A Residual Network for Removal of Fog Using Weighted Combination Loss -- 1 Introduction -- 2 Related Works -- 3 DefogNet: A Residual Network for Removal of Fog Using Weighted Combination Loss -- 3.1 Loss Functions Used -- 4 Results and Discussions -- 4.1 Dataset Description -- 4.2 Experimental Setup -- 4.3 Results -- References -- Text-to-Image Generation Model with DNN Architecture and Computer Vision for Embedded Devices Using Quantization Technique -- 1 Introduction -- 2 Literature Survey -- 2.1 Text-to-Image Generation by Using GAN -- 2.2 Quantization Techniques -- 2.3 Stable Diffusion Model Architecture -- 3 Proposed Methodology -- 3.1 Text-to-Image Generation -- 3.2 Quantization of the Baseline Model -- 3.3 Porting onto Edge Devices -- 4 Results and Analysis -- 4.1 Dataset Description -- 4.2 Experimental Results -- 5 Conclusion and Future Scope -- References. One-Shot Learning for Archaeological Site Data Using Deep Neural Network on Embedded Systems -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 4 Results and Discussion -- 5 Conclusion -- References -- EnhanceNet: A Deep Neural Network for Low-Light Image Enhancement with Image Restoration -- 1 Introduction -- 2 Related Works -- 2.1 Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement Author: Chunle Guo et al. -- 2.2 Kindling the Darkness: A Practical Low-light Image Enhancer Author: Yonghua Zhang et al. -- 2.3 Picture Denoising with Deep Neural Networks -- 2.4 Batch Normalization and Residual Learning -- 2.5 Simple Baselines for Image Restoration-NAFNet Author: Liangyu Chen et al. -- 2.6 Deblurring using Analysis-Synthesis Networks Pair Author: Adam Kaufman et al. -- 3 Methodology -- 3.1 Light-Enhancement Curve (LE-Curve) -- 3.2 DCE-Net -- 3.3 Unsupervised Loss Functions -- 3.4 NAFNet -- 4 Results -- 4.1 Datasets -- 4.2 Quantitative Comparisons -- 5 Conclusion -- References -- Indian Music Instrument Classification Using Deep Learning on Embedded Platforms -- 1 Introduction -- 2 Background Study -- 2.1 MFCC -- 2.2 RNNs and LSTM -- 3 Related Works -- 4 Proposed Methodology -- 4.1 Feature Extraction -- 4.2 Classifier Training -- 4.3 Quantization of the Model -- 5 Experimentation and Results -- 5.1 Dataset -- 5.2 Comparing the Results -- 5.3 Deploying the Model on an Edge Device -- 6 Conclusion -- References -- Facial Image Inpainting Using Vision-Based Quantized Conditional Generative Adversarial Network (QCGAN) on Edge Device -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 Method -- 3.2 Generator with Skip Connections -- 3.3 Discriminator -- 4 Experimentation -- 4.1 Dataset and Preprocessing -- 4.2 Training of the Model -- 4.3 Post-quantization -- 5 Results and Discussion -- 5.1 Visual Analysis. 5.2 Quantitative Comparison. |
| Record Nr. | UNINA-9910864198003321 |
|
Gunjan Vinit Kumar
|
||
| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||