tag :: Machine learning, neural

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1Convolution Neural Network Based Method for Biometric Recognition
A. |. CENTRAL ASIAN JOURNAL OF THEORETICAL AND APPLIED SCIENCE, 4 (8): 58-68 (августа 2023)
9 месяцев назад , @centralasian_20
Ear
convolutional
extraction,
features
learning,
machine
network
networksneural
neural
recognition,
Earconvolutionalextraction,featureslearning,machinenetworknetworksneuralneuralrecognition,
(0)
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1The Use of Machine Learning and Neural Networks in the Digital Economy and International Digital Integration
D. Okhunov. Journal of Ethics and Diversity in International Communication, 3 (2): 79-84 (февраля 2023)
год назад , @openaccess_20
algorithms,
approach,
artificial
intelligence,
learning,
logical
machine
networks
neural
neurocybernetic
algorithms,approach,artificialintelligence,learning,logicalmachinenetworksneuralneurocybernetic
(0)
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2Can Machines Learn to Predict Weather? Using Deep Learning to Predict Gridded 500-hPa Geopotential Height From Historical Weather Data
J. Weyn, D. Durran, и R. Caruana. Journal of Advances in Modeling Earth Systems, 11 (8): 2680--2693 (2019)\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2019MS001705.
год назад , @jascal_panetzky
deep
ecomodelling
learning,
machine
network,
neural
prediction
weather
deepecomodellinglearning,machinenetwork,neuralpredictionweather
(0)
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1The Application of Machine Learning to the Prediction of Heart Attack
R. |. International Journal of Human Computing Studies, 5 (4): 5-25 (апреля 2023)
год назад , @researchpark_20
Algorithm
Attack,
Disease,
Electrocardiogram,
Heart
Learning,
Machine
Networks
Neural
Prediction
of
AlgorithmAttack,Disease,Electrocardiogram,HeartLearning,MachineNetworksNeuralPredictionof
(0)
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2Neural Process Mining: Multi-Headed Predictive Process Analytics in Practice
F. Oberdorf, M. Schaschek, N. Stein, и C. Flath. (2021)
3 лет назад , @winkelmann
Machine
Multi-headed
Predictive
Process
analytics
learning,
mining,
network,
neural
MachineMulti-headedPredictiveProcessanalyticslearning,mining,network,neural
(0)
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1A STRUCTURED DEEP NEURAL NETWORK FOR DATA-DRIVEN LOCALIZATION IN HIGH FREQUENCY WIRELESS NETWORKS
M. Marcus Z. Comiter, и and H. T. Kung. International Journal of Computer Networks & Communications (IJCNC), 9 (3): 21-39 (мая 2017)
8 лет назад , @laimbee
5G,
802.11ad,
Deep
Localization,
Machine
Millimeter
Mobile
Networks
Neural
learning,
networks,
wave,
5G,802.11ad,DeepLocalization,MachineMillimeterMobileNetworksNeurallearning,networks,wave,
(0)
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4Mastering the game of Go with deep neural networks and tree search
D. Silver, A. Huang, C. Maddison, A. Guez, L. Sifre, G. Van Den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot и 1 other автор(ы). Nature, 529 (7587): 484--489 (2016)
8 лет назад , @yourwelcome
Artificial
Intelligence,
Learning,
Machine
deep
gameplay,
learning,
networks
neural
ArtificialIntelligence,Learning,Machinedeepgameplay,learning,networksneural
(0)
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1Machine learning methods without tears: a primer for ecologists.
J. Olden, J. Lawler, и N. Poff. The Quarterly Review of biology, 83 (2): 171--193 (2008)
8 лет назад , @yourwelcome
Animals,
Artificial
Decision
Ecosystem,
Fishes:
Genetic,
Intelligence,
Learning,
Machine
Software,
Species
Specificity,
Trees,
\&
algorithms,
biology,
classification,
computational
data
ecology,
fish,
freshwater,
networks,
neural
numerical
statistics
Animals,ArtificialDecisionEcosystem,Fishes:Genetic,Intelligence,Learning,MachineSoftware,SpeciesSpecificity,Trees,\&algorithms,biology,classification,computationaldataecology,fish,freshwater,networks,neuralnumericalstatistics
(0)
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4Statistical modeling: the two cultures
L. Breiman. Statistical Science, 16 (3): 199--215 (2001)ArticleType: research-article / Full publication date: Aug., 2001 / Copyright © 2001 Institute of Mathematical Statistics.
8 лет назад , @yourwelcome
Learning,
Machine
algorithms,
modelling,
networks,
neural
prediction
Learning,Machinealgorithms,modelling,networks,neuralprediction
(0)
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1On neurobiological, neuro-fuzzy, machine learning, and statistical pattern recognition techniques
A. Joshi, N. Ramakrishman, E. Houstis, и J. Rice. Neural Networks, IEEE Transactions on, 8 (1): 18--31 (1997)
15 лет назад , @mozaher
(artificial
adaptation,
algorithm,
analysis,
classes,
classification,
clustering,
fuzzy
human
intelligence),
learning
learning,
machine
method,
min-max
minimax
multiresolution
mutually
nets,
neural
neuro-fuzzy
neurobiological
nonexclusive
one-pass
online
pattern
recognition
recognition,
set
statistical
techniques,
theory,
(artificialadaptation,algorithm,analysis,classes,classification,clustering,fuzzyhumanintelligence),learninglearning,machinemethod,min-maxminimaxmultiresolutionmutuallynets,neuralneuro-fuzzyneurobiologicalnonexclusiveone-passonlinepatternrecognitionrecognition,setstatisticaltechniques,theory,
(0)
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1Fuzzy kernel perceptron
J. Chen, и C. Chen. Neural Networks, IEEE Transactions on, 13 (6): 1364--1373 (2002)
15 лет назад , @mozaher
(artificial
Mercer
classification,
feature
functions,
fuzzy
high-dimensional
intelligence),
kernel,
kernel-based
learning
learning,
machine
mapping
method,
nets,
neural
pattern
perceptron,
perceptrons,
space,
supervised
support
vector
(artificialMercerclassification,featurefunctions,fuzzyhigh-dimensionalintelligence),kernel,kernel-basedlearninglearning,machinemappingmethod,nets,neuralpatternperceptron,perceptrons,space,supervisedsupportvector
(0)
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2Object Class Recognition Using NEAT-Evolved Artificial Neural Network
M. Hasanat, S. Harun, D. Ramachandram, и M. Rajeswari. Computer Graphics, Imaging and Visualisation, 2008. CGIV '08. Fifth International Conference on, (августа 2008)
15 лет назад , @mozaher
(artificial
ANN
Augmenting
Evolution
NEAT-evolved
Neuro
SIFT
Topologies,
art
artificial
class
classifier,
computer
descriptor
feature,
histograms,
intelligence),
learning
learning,
machine
nets,
network,
neural
object
of
recognition,
recognitionNEAT-evolved
robust
statistical
support
vector
vision,
(artificialANNAugmentingEvolutionNEAT-evolvedNeuroSIFTTopologies,artartificialclassclassifier,computerdescriptorfeature,histograms,intelligence),learninglearning,machinenets,network,neuralobjectofrecognition,recognitionNEAT-evolvedrobuststatisticalsupportvectorvision,
(0)
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2A Domain-independent Window approach to Multiclass Object Detection using Genetic Programming
M. Zhang, V. Ciesielski, и P. Andreae. EURASIP Journal on Applied Signal Processing, 2003 (8): 841--859 (июля 2003)Special Issue on Genetic and Evolutionary Computation for Signal Processing and Image Analysis.
17 лет назад , @brazovayeye
algorithms,
computer
detection,
genetic
learning,
machine
networks,
neural
object
programming,
recognition,
target
vision
algorithms,computerdetection,geneticlearning,machinenetworks,neuralobjectprogramming,recognition,targetvision
(0)
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2Genetic Programming for Multiple Class Object Detection
M. Zhang, и V. Ciesielski. 12th Australian Joint Conference on Artificial Intelligence, том 1747 из LNAI, стр. 180--192. Sydney, Australia, Springer-Verlag, (6-10 December 1999)
17 лет назад , @brazovayeye
Machine
Neural
Vision
algorithms,
genetic
learning,
networks,
programming,
MachineNeuralVisionalgorithms,geneticlearning,networks,programming,
(0)
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2Internal reinforcement in a connectionist genetic programming approach
A. Teller, и M. Veloso. Artificial Intelligence, 120 (2): 165--198 (июля 2000)
17 лет назад , @brazovayeye
Bucket
Evolutionary
Internal
Machine
Neural
Signal
algorithms,
brigade
computation,
genetic
learning,
programming,
reinforcement,
understanding,
BucketEvolutionaryInternalMachineNeuralSignalalgorithms,brigadecomputation,geneticlearning,programming,reinforcement,understanding,
(0)
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2Balancing Accuracy and Parsimony in Genetic Programming
B. Zhang, и H. Mühlenbein. Evolutionary Computation, 3 (1): 17--38 (1995)
17 лет назад , @brazovayeye
Bayesian
Evolving
Machine
Minimum
Tree
algorithms,
comparison,
description
genetic
induction,
learning,
length
model
networks.
neural
principle,
programming,
BayesianEvolvingMachineMinimumTreealgorithms,comparison,descriptiongeneticinduction,learning,lengthmodelnetworks.neuralprinciple,programming,
(0)
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1An improved genetic programming technique for the classification of Raman spectra
K. Hennessy, M. Madden, J. Conroy, и A. Ryder. Knowledge Based Systems, 18 (4-5): 217--224 (августа 2005)AI-2004, Cambridge, England, 13th-15th December 2004.
17 лет назад , @brazovayeye
Machine
Neural
Raman
Spectroscopy,
algorithms,
genetic
learning,
networks,
programming,
MachineNeuralRamanSpectroscopy,algorithms,geneticlearning,networks,programming,
(0)
копироватьудалитьдобавить публикацию в буфер
1Can genetic programming improve software effort estimation? A comparative evaluation
C. Burgess, и M. Lefley. Information and Software Technology, 43 (14): 863--873 (2001)
17 лет назад , @brazovayeye
Case-based
Machine
Neural
Software
algorithms,
effort
estimation
genetic
learning,
networks,
programming,
reasoning,
Case-basedMachineNeuralSoftwarealgorithms,effortestimationgeneticlearning,networks,programming,reasoning,
(0)
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1Inductive, Evolutionary, and Neural Computing Techniques for Discrimination: A Comparative Study
S. Bhattacharyya, и P. Pendharkar. Decision Sciences, 29 (4): 871--899 (Fall 1998)
17 лет назад , @brazovayeye
Analysis,
Discriminant
Inductive
Learning,
Machine
Networks
Neural
algorithms,
and
genetic
programming,
Analysis,DiscriminantInductiveLearning,MachineNetworksNeuralalgorithms,andgeneticprogramming,
(0)
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1Convolution Neural Network Based Method for Biometric Recognition

1The Use of Machine Learning and Neural Networks in the Digital Economy and International Digital Integration

2Can Machines Learn to Predict Weather? Using Deep Learning to Predict Gridded 500-hPa Geopotential Height From Historical Weather Data

1The Application of Machine Learning to the Prediction of Heart Attack

2Neural Process Mining: Multi-Headed Predictive Process Analytics in Practice

1A STRUCTURED DEEP NEURAL NETWORK FOR DATA-DRIVEN LOCALIZATION IN HIGH FREQUENCY WIRELESS NETWORKS

4Mastering the game of Go with deep neural networks and tree search

1Machine learning methods without tears: a primer for ecologists.

4Statistical modeling: the two cultures

1On neurobiological, neuro-fuzzy, machine learning, and statistical pattern recognition techniques

1Fuzzy kernel perceptron

2Object Class Recognition Using NEAT-Evolved Artificial Neural Network

2A Domain-independent Window approach to Multiclass Object Detection using Genetic Programming

2Genetic Programming for Multiple Class Object Detection

2Internal reinforcement in a connectionist genetic programming approach

2Balancing Accuracy and Parsimony in Genetic Programming

1An improved genetic programming technique for the classification of Raman spectra

1Can genetic programming improve software effort estimation? A comparative evaluation

1Inductive, Evolutionary, and Neural Computing Techniques for Discrimination: A Comparative Study

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