TY  - GEN
T1  - Applications of Computational Intelligence
A2  - Wu, Yue
LA  - eng
PB  - MDPI - Multidisciplinary Digital Publishing Institute
YR  - 2023
UL  - https://ebooks.jgu.edu.in/Record/doab-20.500.12854-100013
AB  - Computational Intelligence (CI) is the theory, design, application, and development of biologically and linguistically motivated computational paradigms. Traditionally, the three main pillars of CI have been neural networks, fuzzy systems, and evolutionary computation. However, in time, many nature-inspired computing paradigms have evolved. Thus, CI is an evolving field, and, at present, in addition to the three main constituents, it encompasses computing paradigms such as ambient intelligence, artificial life, cultural learning, artificial endocrine networks, social reasoning, and artificial hormone networks. CI plays a major role in developing successful intelligent systems, including games and cognitive developmental systems. Over the last few years, there has been an explosion of research on deep learning, specifically deep convolutional neural networks, and deep learning has become the core method for artificial intelligence. In fact, some of the most successful AI systems today are based on CI. Therefore, this reprint focuses on the theoretical study of computational intelligence and its applications.
SN  - 9783036570389
SN  - 9783036570396
KW  - artificial intelligence
KW  - deep learning
KW  - AlphaZero
KW  - NoGo games
KW  - reinforcement learning
KW  - evolutionary algorithm
KW  - convolutional neural network
KW  - transfer learning
KW  - image classification
KW  - large-scale multiobjective optimization
KW  - sparse unmixing
KW  - hyperspectral image
KW  - opponent exploitation
KW  - no-limit Texas hold’em
KW  - neuroevolution
KW  - online update
KW  - reliable evaluation strategy
KW  - active–frozen memory model
KW  - visual tracking
KW  - evolutionary multitasking
KW  - particle swarm optimization
KW  - multipopulation optimization
KW  - computational intelligence
KW  - medical image segmentation
KW  - convolutional neural networks
KW  - weakly supervised segmentation
KW  - attention mechanism
KW  - HCNNs
KW  - progressive deep learning
KW  - disease screening
KW  - multi-target tracking
KW  - evolutionary optimization
KW  - random finite set
KW  - joint integrated probabilistic data association
KW  - few-shot learning
KW  - medical image classification
KW  - spatial attention
KW  - crop insect pest identification
KW  - convolutional neural network (CNN)
KW  - capsule network (CapsNet)
KW  - multi-scale convolution-capsule network (MSCCN)
KW  - image retrieval
KW  - Transformer
KW  - self-attention
KW  - knowledge distillation
KW  - hashing learning
KW  - Kuroshio Extension Observatory
KW  - sound speed profile
KW  - self-organizing map
KW  - circle chaotic map
KW  - Levy flight
KW  - nonlinear adaptive weight
KW  - tuna swarm optimization
KW  - quality of experience
KW  - human perception
KW  - electroencephalogram
KW  - crop disease leaf image segmentation (CDLIS)
KW  - U-Net
KW  - dilated convolution
KW  - lightweight multi-scale dilated U-Net (LWMSDU-Net)
KW  - crystal structure algorithm
KW  - golden sine algorithm
KW  - levy flight
KW  - engineering optimization problems
KW  - people counting
KW  - CSI
KW  - cross-modal learning network
KW  - graph neural network
KW  - propagation mechanism
KW  - data-driven method
KW  - gastrointestinal stromal tumor
KW  - semi-supervised learning
KW  - self-training
KW  - object detection
KW  - thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
KW  - thema EDItEUR::U Computing and Information Technology::UY Computer science
ER  -