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Model-Based Object Recognition from a Complex Binary Imagery Using Genetic Algorithm
[chapter]
1999
Lecture Notes in Computer Science
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This paper describes a technique for model-based object recognition in a noisy and cluttered environment, by extending the work presented in an earlier study by the authors. ...
A special form of template matching is used to deal with the noisy environment, where the templates are generated on-line by a Genetic Algorithm. ...
Object recognition in a complex image using GA has also been attempted 26]. ...
doi:10.1007/10704703_12
fatcat:twdxsfwdebf7vkjo54uti4j3ku
Satellite Imagery Classification Based On Deep Convolution Network
2016
Zenodo
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Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. ...
Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform ...
ACKNOWLEDGMENT The authors thank Tang Lei from Xi'an Microelectronics Technology Institute for his valuable comments to improve the quality of this paper. ...
doi:10.5281/zenodo.1125018
fatcat:tky2xdnbf5auzlcgjm3vfta7ue
Aerial Image Segmentation: A Survey
2017
International Journal of Applied Information Systems
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The main goal of image segmentation is to cluster the pixels of the regions corresponding to individual surfaces, objects, or natural parts of objects and to simplify and/or change the representation of ...
In this paper, we have presented a study of various segmentation techniques applied on aerial images. The processes have been explained in detail followed by a comparative table. ...
Mukhop
adhyay
Multi
objective
Genetic Clustering
for
Pixel
Classification
in
Remote
Sensing
Imagery
Pixel
Classification of
aerial images
Fuzzy Clustering,
Genetic Algorithm,
Multi-Objective ...
doi:10.5120/ijais2017451702
fatcat:bp3e4et2sng5bcjrvzqk7qbgfm
Feature Selection Method Based on High-Resolution Remote Sensing Images and the Effect of Sensitive Features on Classification Accuracy
2018
Sensors
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This paper proposes a novel feature selection approach, in which ReliefF, genetic algorithm, and support vector machine (RFGASVM) are integrated to extract buildings. ...
After eliminating the sorted features, the feature subset and the C and γ parameters of support vector machine (SVM) are encoded into the chromosome of the genetic algorithm. ...
Figure 8 . 8 Probability distribution density of different object features based on extraction from high-resolution images ((a) BJ-2 imagery, (b) UAV imagery, and (c) GF-2 imagery). ...
doi:10.3390/s18072013
pmid:29932436
pmcid:PMC6068868
fatcat:kjy5a6cnbvggjpmlzntkva5mxy
Page 2896 of Mathematical Reviews Vol. , Issue 2003d
[page]
2003
Mathematical Reviews
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The Internet Archive has digitized a microfilm copy of this work. It may be possible to borrow a copy for reading.
As ex- amples, we used binary vectors that represent text documents from different categories from the TIPSTER collection. ...
Pal, Genetic algorithms, pattern classification and neural networks de- sign (347-384); A. Skowron and R. Swiniarski, Rough sets in pattern recognition (385-425); L. I. ...
Front Matter: Volume 10033
2016
Eighth International Conference on Digital Image Processing (ICDIP 2016)
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using a Base 36 numbering system employing both numerals and letters. ...
SPIEDigitalLibrary.org Paper Numbering: Proceedings of SPIE follow an e-First publication model. A unique citation identifier (CID) number is assigned to each article at the time of publication. ...
variance minimum algorithm
SESSION 3 PATTERN RECOGNITION
0S Towards 3D object recognition with contractive autoencoders 10033 0U A new pixel-based granular fusion method for finger recognition ...
doi:10.1117/12.2257252
fatcat:v2ipfp2mp5gedjypzpecahpo7e
Multiclass Motor Imagery Recognition of Single Joint in Upper Limb Based on NSGA- II OVO TWSVM
2018
Computational Intelligence and Neuroscience
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This paper proposes a novel scheme that combined amplitude-frequency (AF) information of intrinsic mode function (IMF) with common spatial pattern (CSP), namely, AF-CSP to extract motor imagery (MI) features ...
, and to improve classification performance, the second generation nondominated sorting evolutionary algorithm (NSGA-II) is used to tune hyperparameters for linear and nonlinear kernel one versus one twin ...
The most widely used is the SMR BCI system based on motor imagery. ...
doi:10.1155/2018/6265108
pmid:30050566
pmcid:PMC6046167
fatcat:hdtbezrbdrbrvdnd7ydlcjaqim
Generative 3D images in a visual evolutionary computing system
2010
Computer Science and Information Systems
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Then a binary tree based genetic algorithm is presented. ...
This approach is illustrated by a 3D image generative example, which uses complex function expressions as chromosomes to form a binary tree, and all genetic operations are performed on the binary tree. ...
Section 3 introduces genetic algorithms and genetic programming. In section 4, a binary tree based genetic algorithm is presented. ...
doi:10.2298/csis1001111l
fatcat:cnmhvtwpjvdc5is3qa4zdujezm
Hybrid genetic optimization and statistical model based approach for the classification of shadow shapes in sonar imagery
2000
IEEE Transactions on Pattern Analysis and Machine Intelligence
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AbstractÐWe present an original statistical classification method using a deformable template model to separate natural objects from man-made objects in an image provided by a high resolution sonar. ...
In this context, we compare the results obtained with a deterministic relaxation technique (a gradient-based algorithm) and two stochastic relaxation methods: Simulated Annealing (SA) and a hybrid Genetic ...
The main contribution of this paper lies in the use of deformable model to classify objects in sonar imagery. ...
doi:10.1109/34.825752
fatcat:irttqoqipnbvridkcbo55mxmdu
AN ENHANCEMENT REVIEW ON IMAGE SEGMENTATION METHODS
2018
International Journal of Advanced Research
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Expectation-Maximization (EM) algorithm, OSTU and Genetic algorithms are used to demonstrate the synergy between the segmented images and object recognition. ...
Central to this method is the combined use of image features from segmented objects and prior knowledge from historical thematic maps in a top-down segmentation procedure. ...
doi:10.21474/ijar01/6521
fatcat:5zsmpotkdzgbxbhidnqz56j5xe
Table of contents
2014
2014 International Conference on Informatics, Electronics & Vision (ICIEV)
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131
Analysis on Handwritten Bangla Character Recognition Using ANN
133
Developing a Cryptographic Algorithm Based on ASCII Conversions and a Cyclic Mathematical
Function
134
Indexed Binary ...
Direction of Migrating Procedural Paradigm to Object Based Architecture by forming
Cluster of Functions using Local Search Heuristics
309
An Optimized Design of Binary Comparator Circuit in Quantum ...
Implementation of vision based intelligent home automation and security system. 436 Analysis of the local frequency spectrum for the chirp signal 439 An Review of the e-JIKEI Network: Security camera system ...
doi:10.1109/iciev.2014.6850868
fatcat:y4gdctlg3zgajc3ge3drl6itcy
Subpixel Mapping Method of Hyperspectral Images Based on Modified Binary Quantum Particle Swarm Optimization
2017
Journal of Electrical and Computer Engineering
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This paper proposes a subpixel mapping method based on modified binary quantum particle swarm optimization (MBQPSO) to solve the above issues. ...
To reduce time complexity, a target optimization strategy of global iteration combined with local iteration is performed. ...
Immune clonal selection algorithms and differential evolution algorithms were used to solve the mathematical model using Verhoeye's data [22, 23] . ...
doi:10.1155/2017/2683248
fatcat:tesjvi5j7faepmor23g6onb7g4
Applied Imagery Pattern Recognition 2011
2011
2011 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)
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Abstract: Remote sensing imagery has been used in disaster response since Hurricane Camille in 1969; however limitations on the technology or our effective use of the information have prevented us from ...
The Applied Imagery Pattern Recognition Workshop promotes and encourages the interdisciplinary interchange of ideas. ...
Could these algorithms be used to classify and identify other objects, such as ships seen from electro-optical satellite imagery? ...
doi:10.1109/aipr.2011.6176381
fatcat:7bbefbxrnnfjvdtun4zixrckjy
Guest Editorial Introduction To The Special Issue On Automatic Target Detection And Recognition
1997
IEEE Transactions on Image Processing
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Munson and A. Bovik, for providing useful suggestions in the development of this special issue. We also extend our thanks to P. Wheeler and J. Handler for their support. ...
We are grateful to the referees who spent their valuable time in reviewing the manuscripts and worked under a tight schedule. ...
nets, and genetic algorithms. ...
doi:10.1109/tip.1997.552076
fatcat:hguhbyq5nffdxphleyqti5npyu
Introduction to the Special Issue on Learning in Computer Vision and Pattern Recognition
2005
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)
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Peng has served as the Program Co-Chair for the IEEE Workshop in Computer Vision and Pattern Recognition. ...
ACKNOWLEDGMENT We thank the authors who submitted and contributed their work to this special issue and worked under a tight schedule. ...
Synthetic aperture radar (SAR) imagery is used to demonstrate the results. The third paper, by Schneider et al., presents a biologically inspired hierarchical vision model for 3-D object recognition. ...
doi:10.1109/tsmcb.2005.847940
fatcat:avm2mj3cozaxxmqavlpseca5lm
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