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- image
- recognition,
- object
- Bayesian
- classification,
- visual
- detection,
- vision,
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- computer
- learning
- analysis,
- network
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- Tie Wang, J.W. Touchman, and Guoliang Xue. page 647-648. (August 2004)Tie Wang, J.W. Touchman, and Guoliang Xue. page 647-648. (August 2004)3 years and 8 months agoby mozaher2
- (artificial
- Bayesian
- Carlo
- K2
- Monte
- algorithm,
- annealing
- belief
- biology
- computing,
- genetic
- genetics,
- global
- inference
- inference,
- intelligence),
- learning
- learning,
- local
- mechanisms,
- method,
- methods,
- model,
- network
- networks,
- optimized
- optimizer,
- probability
- probability,
- problem,
- problems,
- search
- simulated
- strengthened
- structure
- two-level
(artificial Bayesian Carlo K2 Monte algorithm, annealing belief biology computing, genetic genetics, global inference inference, intelligence), learning learning, local mechanisms, method, methods, model, network networks, optimized optimizer, probability probability, problem, problems, search simulated strengthened structure two-level - Neural-network-based segmentation of multi-modal medical images: a comparative and prospective studyM. Ozkan, B.M. Dawant, and R.J. Maciunas. Medical Imaging, IEEE Transactions on 12(3):534--544 (1993)M. Ozkan, B.M. Dawant, and R.J. Maciunas. Medical Imaging, IEEE Transactions on 12(3):534--544 (1993)3 years and 8 months agoby mozaher1
- NMR,
- X-ray
- adaptive
- artificial
- biomedical
- brain,
- classical
- classification,
- classifier,
- computer
- computerised
- diagnostic
- generalization
- human
- image
- images
- images,
- imaging,
- intensity
- interslice
- learning
- likelihood
- magnetic
- maximum
- medical
- multimodal
- nets,
- networks,
- neural
- parameters
- parameters,
- processing,
- properties,
- resonance
- scheme,
- segmentation,
- tomography,
- topological
- variations,
NMR, X-ray adaptive artificial biomedical brain, classical classification, classifier, computer computerised diagnostic generalization human image images images, imaging, intensity interslice learning likelihood magnetic maximum medical multimodal nets, networks, neural parameters parameters, processing, properties, resonance scheme, segmentation, tomography, topological variations, - M.N. Omri. Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on (1999)M.N. Omri. Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on (1999)3 years and 8 months agoby mozaher1
- (artificial
- Bayes
- Bayesian
- Gallois
- analysis
- analysis,
- descriptive
- filtering,
- fuzzy
- goals,
- graph
- inductive
- intelligence),
- interfaces,
- interpretation,
- knowledge
- language
- languages,
- lattice,
- learning
- method,
- methods,
- natural
- net,
- network,
- networks,
- objects
- optimization
- processingBayesian
- representation
- representation,
- scheme,
- semantic
- systems,
- technique,
- unknown
- user
- verb,
- word
(artificial Bayes Bayesian Gallois analysis analysis, descriptive filtering, fuzzy goals, graph inductive intelligence), interfaces, interpretation, knowledge language languages, lattice, learning method, methods, natural net, network, networks, objects optimization processingBayesian representation representation, scheme, semantic systems, technique, unknown user verb, word - M. Marszalek, and C. Schmid. Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on (June 2007)M. Marszalek, and C. Schmid. Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on (June 2007)3 years and 8 months agoby mozaher2
- Y. LeCun, Fu Jie Huang, and L. Bottou. Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on, 2, page II-97--104 Vol.2. (2004)Y. LeCun, Fu Jie Huang, and L. Bottou. Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on, 2, page II-97--104 Vol.2. (2004)3 years and 8 months agoby mozaher2
- analysis,
- component
- computer
- convolutional
- databases,
- detection,
- error
- extraction,
- feature
- generic
- grayscale
- image
- images,
- invariance,
- large
- learning
- lighting
- low-resolution
- machines,
- methods,
- nearest
- neighbor
- networks,
- object
- pose
- principal
- processing,
- rates
- recognition,
- segmentation,
- stereo
- support
- test
- vector
- very
- vision,
- visual
analysis, component computer convolutional databases, detection, error extraction, feature generic grayscale image images, invariance, large learning lighting low-resolution machines, methods, nearest neighbor networks, object pose principal processing, rates recognition, segmentation, stereo support test vector very vision, visual - Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner. Proceedings of the IEEE 86(11):2278--2324 (1998)Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner. Proceedings of the IEEE 86(11):2278--2324 (1998)3 years and 8 months agoby mozaher3
- 2D
- GTN,
- back-propagation,
- backpropagation,
- based
- character
- cheque
- complex
- convolution,
- convolutional
- decision
- digit
- document
- extraction,
- field
- gradient
- gradient-based
- graph
- handwritten
- high-dimensional
- language
- learning
- learning,
- measure
- minimization,
- modeling,
- multilayer
- multimodule
- network
- networks,
- neural
- optical
- patterns,
- perceptrons,
- performance
- reading,
- recognition
- recognition,
- recognizers,
- segmentation
- shape
- surface
- synthesis,
- systems,
- task,
- technique,
- transformer
- variability,
2D GTN, back-propagation, backpropagation, based character cheque complex convolution, convolutional decision digit document extraction, field gradient gradient-based graph handwritten high-dimensional language learning learning, measure minimization, modeling, multilayer multimodule network networks, neural optical patterns, perceptrons, performance reading, recognition recognition, recognizers, segmentation shape surface synthesis, systems, task, technique, transformer variability, - F. Kummert, G.A. Fink, G. Sagerer, and E. Braun. Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on, 2, page 1165--1170 vol.2. (1998)F. Kummert, G.A. Fink, G. Sagerer, and E. Braun. Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on, 2, page 1165--1170 vol.2. (1998)3 years and 8 months agoby mozaher1
- W. Buntine. Knowledge and Data Engineering, IEEE Transactions on 8(2):195-210 (April 1996)W. Buntine. Knowledge and Data Engineering, IEEE Transactions on 8(2):195-210 (April 1996)3 years and 8 months agoby mozaher7
- P.J. Brown, J.D. Bovey, and Xian Chen. Personal Communications, IEEE see also IEEE Wireless Communications 4(5):58--64 (1997)P.J. Brown, J.D. Bovey, and Xian Chen. Personal Communications, IEEE see also IEEE Wireless Communications 4(5):58--64 (1997)3 years and 8 months agoby mozaher2
- C. Breen, L. Khan, and A. Ponnusamy. Database and Expert Systems Applications, 2002. Proceedings. 13th International Workshop on, page 98--102. (2002)C. Breen, L. Khan, and A. Ponnusamy. Database and Expert Systems Applications, 2002. Proceedings. 13th International Workshop on, page 98--102. (2002)3 years and 8 months agoby mozaher2
- H.R. Naphide, and T.S. Huang. Multimedia, IEEE Transactions on 3(1):141-151 (March 2001)H.R. Naphide, and T.S. Huang. Multimedia, IEEE Transactions on 3(1):141-151 (March 2001)3 years and 8 months agoby mozaher1
- Markov
- ROC
- access
- access,
- belief
- by
- content
- content,
- content-based
- curves,
- data
- database
- databases,
- databasesBayesian
- example,
- filtering,
- graphical
- hidden
- indexing,
- inference,
- keywords,
- likelihood
- models,
- multimedia
- multinet,
- networks,
- pattern
- probabilistic
- problem,
- query
- query,
- ratio
- reasoning,
- recognition,
- repositories,
- representation
- retrieval,
- semantic
- test,
- understanding,
- video
Markov ROC access access, belief by content content, content-based curves, data database databases, databasesBayesian example, filtering, graphical hidden indexing, inference, keywords, likelihood models, multimedia multinet, networks, pattern probabilistic problem, query query, ratio reasoning, recognition, repositories, representation retrieval, semantic test, understanding, video - Jiebo Luo, and A. Savakis. Image Processing, 2001. Proceedings. 2001 International Conference on (October 2001)Jiebo Luo, and A. Savakis. Image Processing, 2001. Proceedings. 2001 International Conference on (October 2001)3 years and 8 months agoby mozaher2