| Description |
1 online resource |
| Series |
Studies in computational intelligence, 1860-949X ; volume 956 |
|
Studies in computational intelligence ; v. 956. 1860-949X
|
| Contents |
Using CNN to Predict Regressive STD Drug Efficacy Score -- Emotion Recognition in Hindi Speech Using CNN-LSTM Model -- Refinery Profit Planning via Evolutionary Many-Objective Optimization -- A Deep Learning Technique for Image Inpainting with GANs -- A Comparative Study on Distributed File Systems -- An Organized Approach for Analysis of Diabetic Nephropathy Images Using Watershed and Contrast Adaptive Thresholding -- A Literature Survey on Identification of Asthma Using Different Classifier and Clustering Techniques -- Adaptation and Evolution of Decision Support Systems--A Typological Survey -- Real-Time Implementation of Brain Emotional Controller for Sensorless Induction Motor Drive with Adaptive System -- Student Performance Prediction--A Data Science Approach -- HARfog: An Ensemble Deep Learning Model for Activity Recognition Leveraging IoT and Fog Architectures -- Performance Evaluation and Identification of Optimal Classifier for Credit Card Fraudulent Detection -- Potential Use-Cases of Natural Language Processing for a Logistics Organization -- Partial Consensus and Incremental Learning Based Intrusion Detection System -- AI Enabled Context Sensitive Information Retrieval System -- Personalization of News for a Logistics Organisation by Finding Relevancy Using NLP -- AI Model Compression for Edge Devices Using Optimization Techniques -- An Empirical Study and Analysis of Various Electroencephalography (EEG) Artefact Removal Methods -- Chatbot via Machine Learning and Deep Learning Hybrid -- Prediction Intervals for Macroeconomic Variables Using LSTM Based LUBE Method -- Intelligent Character Recognition with Shared Features from Resnet -- SVM and Naïve Bayes Models for Estimation of Key Process Variables in Nuclear Power Plant -- Face Recognition Using Transfer Learning on Facenet: Application to Banking Operations -- Deep Learning Chatbot with Feedback -- A Non-monotonic Activation Function for Neural Networks Validated on Benchmark Tasks -- Analysis of Approaches for Automated Glaucoma Detection and Prediction System -- Experiences in Machine Learning Models for Aircraft Fuel Flow and Drag Polar Predictions -- Wildlife Video Captioning Based on ResNet and LSTM -- Enhancement of Degraded Images via Fuzy Intensification Model -- Design and Investigation of the Performance of Composite Spiral Antenna for Direction Finding Applications -- Learning Based Approach for Subtle Maintenance in Large Institutions -- Temporal Localization of Topics Within Videos -- Fast Training of Deep Networks with One-Class CNNs -- Recognition of Isolated English Words of E-Lecture Video Using Convolutional Neural Network -- Indoor Object Location Finding Using UWB Technology -- Design and Tuning of Improved Current Predictive Control for PMSM -- Parametric Analysis of Texture Classification Using Modified Weighted Probabilistic Neural Network (MWPNN) -- Modeling and Simulation of Automatic Centralized Micro Grid Controller -- The VLSI Realization of Sign-Magnitude Decimal Multiplication Efficiency -- Image Encryption Algorithms Using Machine Learning and Deep Learning Techniques--A Survey |
| Summary |
This book provides a systematic and comprehensive overview of machine learning with cognitive science methods and technologies which have played an important role at the core of practical solutions for a wide scope of tasks between handheld apps, industrial process control, autonomous vehicles, environmental policies, life sciences, playing computer games, computational theory, and engineering development. The chapters in this book focus on readers interested in machine learning, cognitive and neuro-inspired computational systems theories, mechanisms, and architecture, which underline human and animal behaviour, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions to applications of machine learning and cognitive science such as healthcare products, medical electronics, and gaming. Overall, this book provides valuable information on effective, cutting-edge techniques and approaches for students, researchers, practitioners, and academicians working in the field of AI, neural network, machine learning, and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains |
| Subject |
Machine learning.
|
|
Artificial intelligence.
|
|
Cognitive science.
|
|
Artificial Intelligence
|
|
Machine Learning
|
|
artificial intelligence.
|
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Artificial intelligence
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Cognitive science
|
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Machine learning
|
| Form |
Electronic book
|
| Author |
Gunjan, Vinit Kumar, editor.
|
|
Zurada, Jacek M., editor.
|
| ISBN |
9783030682910 |
|
3030682919 |
|
