11250nam 2200505 450 991061638380332120230226063230.03-031-16364-8(MiAaPQ)EBC7101995(Au-PeEL)EBL7101995(CKB)24950450300041(OCoLC)1347262422(EXLCZ)992495045030004120230226d2022 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierComputational intelligence in data science 5th IFIP TC 12 International Conference, ICCIDS 2022, virtual event, March 24-26, 2022, revised selected papers /Lekshmi Kalinathan [and three others]Cham, Switzerland :Springer,[2022]©20221 online resource (381 pages)IFIP Advances in Information and Communication TechnologyPrint version: Kalinathan, Lekshmi Computational Intelligence in Data Science Cham : Springer International Publishing AG,c2022 9783031163630 Intro -- Preface -- Organization -- Contents -- Comparative Analysis of Sensor-Based Human Activity Recognition Using Artificial Intelligence -- 1 Introduction -- 2 Related Work -- 3 Materials and Methodology -- 3.1 Data Collection -- 3.2 Preprocessing -- 3.3 Methodology and Models -- 3.4 Evaluation Metrics -- 4 The Results -- 4.1 Hyperparameter Tuning -- 4.2 Deep Belief Networks -- 5 Conclusion -- 6 Limitations and Future Work -- References -- A Survey on Cervical Cancer Detection and Classification Using Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Data Collection -- 3.2 Object Detection Techniques -- 3.3 Image Classification Techniques -- 4 Models Used -- 4.1 ResNet -- 4.2 AlexNet and SqueezeNet -- 4.3 Inception V3 -- 4.4 GoogleNet -- 4.5 CapsNet -- 4.6 CervixNet -- 4.7 RetinaNet and Deep SVDD -- 5 Discussion -- 6 Conclusion -- References -- Counting Number of People and Social Distance Detection Using Deep Learning -- 1 Introduction -- 2 Existing System -- 3 Proposed System -- 4 YOLO Detector -- 5 COCO Dataset -- 6 Centroid Tracking Algorithm -- 7 Module Description -- 7.1 Detection Module -- 7.2 Social Distance Module -- 7.3 People Counting Module -- 7.4 Restriction Module -- 8 Results and Conclusion -- 9 Conclusion and Future Work -- References -- Analysis of Age Sage Classification for Students' Social Engagement Using REPTree and Random Forest -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 RepTree -- 3.2 Random Forest -- 4 Results and Discussion -- 5 Conclusion -- References -- Factual Data Protection Procedure on IoT-Based Customized Medicament Innovations -- 1 Introduction -- 2 Literature Survey -- 3 Proposed System -- 4 Results and Discussion -- 5 Conclusions -- References -- Deep Learning Based Covid-19 Patients Detection -- 1 Introduction -- 2 Methods -- 3 Results -- References.A Progressive Approach of Designing and Analysis of Solar and Wind Stations Integrated with the Grid Connected Systems -- 1 Introduction -- 2 System Description -- 3 Design and Control of PV, Wind and Battery Systems -- 3.1 Model and Operation of Wind Controller -- 3.2 Model and Operation of PV Controller -- 3.3 Model and Operation of Bidirectional Controller for Battery -- 4 Bi-directional Topologies -- 5 Fuzzy Logic Controller Operational Process -- 6 Simulation Analysis and Results -- 7 Summary -- References -- A Survey on Techniques and Methods of Recommender System -- 1 Introduction -- 2 Traditional Methods -- 2.1 Content-Based -- 2.2 Collaborative Filter Based -- 2.3 Demographic-Based Recommender System -- 2.4 Knowledge-Based Recommender System -- 2.5 Utility-Based Recommender System -- 2.6 Hybrid Recommender System [5] -- 3 Review Work -- 3.1 Deep Learning Based Systems -- 3.2 Transfer Learning Based Systems -- 3.3 Active Learning Based Systems -- 3.4 Reinforcement Learning Based Systems -- 3.5 Soft Computation Techniques: Fuzzy System and Evolutionary Algorithms -- 3.6 NLP Based -- 4 Summary -- 5 Observations and Research Gap -- 6 Future Directions and Conclusion -- References -- Live Social Spacing Tracker Based on Domain Detection -- 1 Introduction -- 2 Research Background -- 3 Proposed Work -- 3.1 Algorithm -- 4 Results and Discussions -- 5 Conclusion and Future Work -- References -- Assessing Layer Normalization with BraTS MRI Data in a Convolution Neural Net -- 1 Introduction -- 2 Literature Review -- 3 Normalization -- 4 Experimental Setup and Results -- 4.1 Dataset Description -- 4.2 3D U-Net Architecture -- 4.3 Experimental Results -- 5 Conclusion -- References -- Data Set Creation and Empirical Analysis for Detecting Signs of Depression from Social Media Postings -- 1 Introduction -- 2 Related Work.2.1 Modalities and Methodologies of Depression Detection -- 2.2 Data Collection from Applications of Social Network -- 3 Proposed Work -- 3.1 Data Set Creation -- 3.2 Data Annotation -- 3.3 Inter-rater Agreement -- 3.4 Corpus Analysis -- 3.5 Base Line Models -- 4 Implementation and Results -- 4.1 With Data Augmentation -- 5 Research Insights -- 6 Conclusions -- References -- Classification and Prediction of Lung Cancer with Histopathological Images Using VGG-19 Architecture -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Database Collection -- 3.2 Data Augmentation -- 3.3 Transfer Learning -- 3.4 VGG-19 Architecture -- 4 Results and Discussion -- 4.1 Plots of Accuracy and Loss -- 4.2 Heat Map Generation Using Vgg-19 -- 5 Conclusion -- References -- Analysis of the Impact of White Box Adversarial Attacks in ResNet While Classifying Retinal Fundus Images -- 1 Introduction -- 2 Literature Survey -- 3 Materials and Methods -- 3.1 Attacks Studied -- 3.2 Deep Neural Network Classifier Used -- 3.3 Defense Mechanisms Studied -- 3.4 Details of the Study on the Impact and Working of Adversarial Attacks -- 4 Results and Discussion -- 4.1 Dataset -- 4.2 Hyper Parameters Used for Tuning the Resnet Model -- 4.3 Attack Framework -- 4.4 Sample Images After the Adversarial Attacks -- 4.5 Metrics Used for Evaluation -- 4.6 Analysis of the Effect of the FGSM Attack -- 4.7 Defenses -- 5 Conclusion -- References -- Factors Influencing the Helpfulness of Online Consumer Reviews -- 1 Introduction -- 2 Literature Review and Hypothesis -- 3 Research Methodology -- 4 Results and Discussion -- 5 Conclusion and Future Research -- References -- Perspective Review on Deep Learning Models to Medical Image Segmentation -- 1 Introduction -- 2 Deep Learning Network Architectures and Related Work -- 2.1 Basic CNN (1989) -- 2.2 Alexnet (2012) -- 2.3 Resnet (2015).2.4 U-net (2015) -- 2.5 Volumetric Convolution Network (V-net, 2016) -- 3 Discussion and Conclusion -- References -- Real Time Captioning and Notes Making of Online Classes -- 1 Introduction -- 2 Related Work -- 3 Proposed System -- 3.1 Application Workflow -- 3.2 Architecture Diagram -- 4 Implementation -- 4.1 Dataset -- 4.2 Process of Collecting Dataset -- 4.3 Experimental Setup -- 4.4 Model Building -- 5 Results and Performance Analysis -- 5.1 Rouge (Metric) -- 5.2 BART Model -- 5.3 Inference -- 5.4 Screenshots of GUI -- 6 Conclusion and Future Work -- References -- Disease Identification in Tomato Leaf Using Pre-trained ResNet and Deformable Inception -- 1 Introduction -- 2 Related Works -- 3 Proposed Model -- 4 Dataset -- 4.1 PlantVillage Dataset -- 4.2 PlantDoc Dataset -- 4.3 New Mask Dataset Using Data Augmentation -- 5 Experimental Results -- 5.1 Training -- 5.2 Performance Evaluation -- 5.3 Ablation Study on the Neural Network Architecture -- 5.4 Benchmark Results -- 5.5 Hyperparameter Study -- 6 Conclusion -- 7 Future Work -- References -- Allowance of Driving Based on Drowsiness Detection Using Audio and Video Processing -- 1 Introduction -- 1.1 Facts About Drowsy Driving -- 1.2 Causes of Drowsy Driving -- 2 Existing Method -- 2.1 Limitations of Existing Method -- 3 Proposed Method -- 3.1 First Level Verification Process -- 3.2 Second Level Verification Process -- 4 Results and Discussion -- 4.1 Efficiency of the System -- 5 Conclusion -- References -- Identification and Classification of Groundnut Leaf Disease Using Convolutional Neural Network -- 1 Introduction -- 1.1 Problem Statement -- 2 Literature Review -- 3 Methodology of the Research -- 4 Proposed Methodology -- 4.1 Dataset Collection and Sampling Technique -- 4.2 Groundnut Images Sample Digitization -- 4.3 Image Pre-processing -- 4.4 Feature Extraction.4.5 Dataset Partitioning and Model Selection Methodology -- 4.6 Tool Selection -- 4.7 Technique for Evaluation -- 5 Designation of Groundnut Leaf Disease Detection Model -- 6 The Architecture Proposed for the CNN of the Model -- 6.1 Convolutional Layer -- 6.2 Pooling Layer -- 6.3 ReLU Layer -- 6.4 Fully Connected Layer -- 6.5 Loss Layer -- 7 Experimental Results -- 8 Results and Discussion -- 9 Conclusion -- References -- Enhanced Residual Connections Method for Low Resolution Images in Rice Plant Disease Classification -- 1 Introduction -- 2 Related Works -- 2.1 SRCNN -- 2.2 VDSR -- 2.3 Residual Networks -- 2.4 CARN -- 2.5 Generative Model -- 3 Problem Definition -- 4 Proposed Architecture -- 4.1 Proposed Residual Block -- 4.2 Loss Function -- 4.3 Proposed Model -- 5 Experimental Setup -- 5.1 Dataset -- 5.2 Training -- 5.3 Evaluation Metrics -- 6 Results and Discussion -- 6.1 Real World Performance -- 7 Conclusion -- References -- COVI-PROC -- 1 Introduction -- 2 Proposed Architecture -- 3 Working Modules -- 3.1 AIML Component Design -- 4 Output -- 4.1 Data Storage -- 5 Related Work -- 6 Conclusion -- References -- GPS Tracking Traffic Management System Using Priority Based Algorithm -- 1 Introduction -- 2 Related Works -- 3 Proposed System -- 3.1 Density Sensing -- 3.2 Decision Making -- 4 Circuit Design -- 5 Software Design -- 6 Experimental Results -- 7 Conclusion -- References -- Accident Detection System Using Deep Learning -- 1 Introduction -- 2 Literature Analysis -- 3 Proposed Approach -- 3.1 Two Stage Model -- 3.2 One Stage Model -- 3.3 Architecture of YOLOv5 -- 4 Experimental Design -- 4.1 Data Collection -- 4.2 Image Pre-processing -- 4.3 Feature Mining -- 4.4 Object Detection -- 4.5 Model Building -- 4.6 Model Evaluation -- 5 Proposed Architecture -- 6 Results and Discussion -- 7 Accident Detection Module -- 8 Conclusion -- References.Monitoring of PV Modules and Hotspot Detection Using Convolution Neural Network Based Approach.IFIP advances in information and communication technology.Computational intelligenceCongressesComputational intelligenceSimulation methodsComputational intelligenceComputational intelligenceSimulation methods.006.3Kalinathan LekshmiMiAaPQMiAaPQMiAaPQBOOK9910616383803321Computational Intelligence in Data Science2565845UNINA