This book uncovers the stakes and possibilities of handling pandemic diseases with the help of Computational Intelligence, using cases and applications from the current Covid-19 pandemic.
An intense, psychologically charged domestic drama, The Return is a brilliant and haunting exploration of the insecurities that lie at the heart of human relationships.
The book aims to highlight the potential of deep learning (DL)-enabled methods in intelligent fault diagnosis (IFD), along with their benefits and contributions.
The story follows an unnamed narrator who visits a mental institution in southern France (more accurately, a "Maison de Sante") known for a revolutionary new method of treating mental illnesses called the "system of soothing".
Unlock the transformative potential of deep learning in your professional and academic endeavors with Deep Learning in Engineering, Energy and Finance: Principals and Applications.
An example-rich guide for beginners to start their reinforcement and deep reinforcement learning journey with state-of-the-art distinct algorithmsKey FeaturesCovers a vast spectrum of basic-to-advanced RL algorithms with mathematical explanations of each algorithmLearn how to implement algorithms with code by following examples with line-by-line explanationsExplore the latest RL methodologies such as DDPG, PPO, and the use of expert demonstrationsBook DescriptionWith significant enhancements in the quality and quantity of algorithms in recent years, this second edition of Hands-On Reinforcement Learning with Python has been revamped into an example-rich guide to learning state-of-the-art reinforcement learning (RL) and deep RL algorithms with TensorFlow 2 and the OpenAI Gym toolkit.
Bring magic to your mobile apps using TensorFlow Lite and Core MLKey FeaturesExplore machine learning using classification, analytics, and detection tasks.
This book aims to provide a comprehensive overview of the applications of Artificial Intelligence (AI) in the area of Cybersecurity and Digital Forensics.
Neural network models, in addition to being of intrinsic theoretical interest, have also proved to be a useful framework in which issues in theoretical biology can be put into perspective.
These proceedings present the state of the art in Spanish research on pattern recognition, image processing, speech recognition, and artificial neural networks and applications to medicine, geology, control etc.
This volume contains the proceedings of the seventh Italian Workshop on Neural Nets WIRN VIETRI '95, organized by the International Institute for Advanced Scientific Studies 'E R Caianiello' (IIASS) and Societa Italiana Reti Neuroniche (SIREN).
As perception stands for the acquisition of a real world representation by interaction with an environment, learning is the modification of this internal representation.
This book is of interest to researchers in universities, research centres and industries who are involved in measurements and need advanced mathematical tools to solve their problems, and to whoever is working in the development of these mathematical tools.
The papers appearing in this proceedings volume cover a broad range of subjects, owing to the highly cross-disciplinary character of the workshop, and include: experiments and models concerning the dynamics of the neural activity in the cortex (DMS experiments, attractor dynamics in the cortex, spontaneous activity.
Soft computing is the common name for a certain form of natural information processing that has its original form in biology, especially in the function of human brain.
This lecture note volume is mainly about the recent development that connected neural network modeling to the theoretical physics of disordered systems.
This book is a collection of real-world applications of neural networks, which were presented at the ICANN '95 conference of the European Neural Network Society.
Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic.
The neural network paradigm with its various advantages might be the next promising bridge between artificial intelligence and pattern recognition that will help with the conceptualization of new computational artifacts.
With increasing demands for high precision autonomous control over wide operating envelopes, conventional control engineering approaches are unable to adequately deal with system complexity, nonlinearities, spatial and temporal parameter variations, and with uncertainty.
