Advances in Neural Computation, Machine Learning, and Cognitive Research VI
Springer International Publishing (Verlag)
978-3-031-19031-5 (ISBN)
This book describes new theories and applications of artificial neural networks, with a special focus on answering questions in neuroscience, biology and biophysics and cognitive research. It covers a wide range of methods and technologies, including deep neural networks, large-scale neural models, brain-computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more. The book includes both selected and invited papers presented at the XXIV International Conference on Neuroinformatics, held on October 17-21, 2022, in Moscow, Russia.
Part I: Neuroinformatics and Artificial Intelligence.- Tree Inventory with LiDAR Data.- Towards Reliable Solar Atmospheric Parameters Neural-Based Inference.- Addressing Task Prioritization in Model-based Reinforcement Learning.- Automatic Generation of Conversational Skills from Dialog Datasets.- Part II: Neural Networks and Cognitive Sciences. Adaptive Behavior and Evolutionary Simulation.- Individual Topology Structure of Eye Movement Trajectories.- Neural Network Providing the Involvement of Voluntary Attention into the Processing and Conscious Perception of Sensory Information.- Alpha Rhythm Dynamics During Spoken Word Recognition.- Robotic Devices Control Based on Neuromorphic Classifiers of Imaginary Motor Commands.- A Software System for Training Motor Imagery in Virtual Reality.- On the Importance of Diversity.- "MYO-chat" - A New Computer Control System for People with Disabilities.- Low-bit Quantization of Transformer for Audio Speech Recognition.- A Model of Predicting andUsing Regularities by an Autonomous Agent.- A Review of One-Shot Neural Architecture Search Methods.- Does a Recurrent Neural Network Use Reflection During a Reflexive Game?.- A Gender Genetic Algorithm and its Comparison with Conventional Genetic Algorithm.- Associations of Morphometric Changes of the Brain with the Levels of IGF1, a Multifunctional Growth Factor, and with Systemic Immune Parameters Reflect the Disturbances of Neuroimmune Interactions in Patients with Schizophrenia.- Part III: Modern Methods and Technologies in Neurobiology.- Dynamics of Background and Evoked Activity of Neurons in the Auditory Cortex of the Unanaesthetized Cat.- Search for Markers of Moderate Cognitive Disorders through Phase Synchronization between Rhythmic Photostimulus and EEG Pattern.- Astrocytes Enhance Image Representation Encoded in Spiking Neural Network.- Classification of Neuron Type Based on Average Activity.- Comparative Analysis of Statistical and Neural Network Classification Methods onthe Example of Synthesized Data in the Stimulus-Independent Brain-Computer Interface Paradigm.- Shunting Effect of Synaptic Channels Located on Presynaptic Terminal.- Analysis of Appearances, Formation and Evolution of Biological Functional Systems.- The Reinforcement Learning Theory, Value Function, and the Nature of Value Function Calculation by the Insular Cortex.- To the Role of Inferior Olives in Cerebellar Neuromechanics.- Individual Differences in Mismatch-Induced c-Fos Expression in the Retrosplenial Cortex in Rats: Shift in Activity is Layer-Specific.- Sleep of Poor and Good Nappers under the Afternoon Exposure to Weak 2-Hz/8-Hz Electromagnetic Fields.- Part IV: Applications of Neural Networks.- Classification of Light Microscopy Image Using Probabilistic Bayesian Neural Network.- SPICE Model of Analog Content-Addressable Memory Based on 2G FeFET Crossbar.- IQ-GAN: Instance Quantized Image Synthesis.- Specifics of Crossbar Resistor Arrays.- Recurrent and Graph Neural Networksfor Particle Tracking at the BM@N Experiment.- Modeling of a Neural Network Algorithm for Suppressing Non-Stationary Interference in an Adaptive Antenna Array.- Learning Various Locomotion Skills from Scratch with Deep Reinforcement Learning.- Center3dAugNet: Effect of Rotation Representation on One-Stage Joint Car Detection and 6D-Pose Estimation.- Global memory transformer for processing long documents.- Development of the Convolutional Neural Network for Defining the Renal Pathology Using Computed Tomography Images.- Possibility of Using Various Architectures of Convolutional Neural Networks in the Problem of Determining the Type of Rhythm.- DeepPavlov Topics: Topic Classification Dataset for Conversational Domain in English.- Multi-Input Convolutional Neural Networks in Real-Time Semantic Segmentation Tasks.- Integration of Data and Algorithms in Solving Inverse Problems of Spectroscopy of Solutions by Machine Learning Methods.- Investigation of Pareto Front of Neural Network Approximation of Solution of Laplace Equation in Two Statements: with Discontinuous Initial Conditions or with Measurement Data?.- Multitask learning for extensive object description to improve scene understanding on monocular video.- Use of Classification Algorithms to Predict the Grade of Geomagnetic Disturbance.- Information processing in spiking neuron-astrocyte network in ageing.- Multilingual Case-insensitive Named Entity Recognition.- Multi-level Pipeline for Data Mining with Similar Structure.- Creating a Brief Review of Judicial Practice Using Clustering Methods.- Part V: Neural Network Theory, Concepts and Architectures.- "Gas" instead of "Liquid": which Liquid State Machine is Better?.- Using a Resistor Array to Tackle Optimization Problems.- Generative Adversarial Networks as an Approach to Unsupervised Link Prediction Problem.- DGAC: Dialog Graph AutoConstruction up on Data with a Regular Structure.- Relay System of Differential Equations with Delay as a Perceptron Model.- Analysis of Predictive Capabilities of Adaptive Multilayer Models with Physics-Based Architecture for Duffing Oscillator?.- An Attempt to Formalize the Formulation of the Network Architecture Search Problem for Convolutional Neural Networks.- Use of Conditional Variational Autoencoders and Partial Least Squares in Solving an Inverse Problem of Spectroscopy.- On the Similarities between Denoising Diffusion Models and Autoencoders.
| Erscheinungsdatum | 20.10.2022 |
|---|---|
| Reihe/Serie | Studies in Computational Intelligence |
| Zusatzinfo | XVI, 577 p. 216 illus., 110 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 1005 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Naturwissenschaften ► Biologie ► Humanbiologie | |
| Naturwissenschaften ► Biologie ► Zoologie | |
| Technik | |
| Schlagworte | Bayesian neural network • Convolutional Neural Network Architectures • Deep learning models • Denoising Diffusion Models • EEG Pattern Analysis • Image Segmentation with Machine Learning • Modeling Neural Activity • Neural Networks Applications in Bioimaging • Neural Networks Applications in Chatbots • Neuroinformatics 2022 • Neuromorphic Information Processing Systems • Perceptron Model • Recurrent Neural Networks • Reinforcement Learning Applications • Resistor Arrays • Spiking Dynamical Systems |
| ISBN-10 | 3-031-19031-9 / 3031190319 |
| ISBN-13 | 978-3-031-19031-5 / 9783031190315 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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