|
| |
 | 138.
N. Jain, S. Ghosh, and
A. Ghosh, "A parameter free relative density based biclustering method for identifying non-linear feature relations",
Heliyon,
Volume 10, issue 15, 2024. (pdf) |
| 137.
A. Mallick, A. Chowdhury, J. Mukherjee, S. Ghosh, A. Taron, , B. Holmatov, and
A. Ghosh, "Data-driven Future: Highlights from the National Workshop on Agriculture Management in a Changing Climate",
Journal of Geological Society of India,
761-761, 2024. (pdf) |
| 136.
R. Roy, S. Ghosh, and
A. Ghosh, " A. Speckle Noise Removal: A Local Structure Preserving Approach",
SN COMPUT. SCI,
5, 367 (2024).doi.org/10.1007/s42979-024-02655-1. (pdf) |
| 135.
S. Ghosh, A. Mallick, A. Dawn, K. Dey Sarkar, A. Chowdhury, S. Kour, A. Ghosh, and
B. Holmatov , "Digital data and tools for managing agriculture: focusing on earth observation data and climate change",
Proceedings of the Training Workshop on Digital Data and Tools for Managing Agriculture: Focusing on Earth Observation Data and Climate Change, Bhubaneswar, India, 21-23 December 2023. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Initiative on Low-Emission Food Systems; CGIAR Initiative on Resilient Cities,
2024. (pdf) |
| 134.
S. Ghosh, J. Mukherjee, , A. Chowdhury, K. Dey Sarkar, A. Taron, B. Biswas and
A. Ghosh, "Insights from the Five-day National Training Programme on “Earth Observation Data Analytics
for Disaster Management Focusing on Flood and Drought”",
Journal of the Geological Society of India, 99, 1787–1788 (2023).
doi.org/10.1007/s12594-023-2539-y. (pdf) |
| 133.
H. Dutta, S Bilgaiyan, S. Ghosh, BSP. Mishra, S Dehuri, A. Ghosh, "Genetically
Optimized UFLANN for Uncovering Clusters",
IEEE Access,
vol 11, pp. 95432-95442, 2023. (pdf) |
| 132.
D. Chakraborty, D. Goswami, S. Ghosh, A. Ghosh, J. H. Chan, and
L. Wang, "Transfer-recursive-ensemble learning for multi-day
COVID-19 prediction in India using recurrent neural
networks",
Scientific Reports,
Accepted. (pdf) |
| 131.
C. S. K. Dash, A. K. Behera, S. Dehuri and
A. Ghosh, "An outliers detection and elimination framework in classification task of data mining",
Decision Analytics Journal,
100164, 2023. (pdf) |
| 130.
S. Boral, M. Sarkar, and
A. Ghosh , "MEQA: Manifold Embedding Quality Assessment via Anisotropic Scaling and Kolmogorov-Smirnov Test",
Pattern Recognition,
109447, 2023. (pdf) |
| 129.
H. Singh, S. Suman, , B. N. Subudhi, V. Jakhetiya and
A. Ghosh, "Action recognition in dark videos using spatio-temporal features and bidirectional encoder representations from
transformers",
IEEE Transactions on Artificial Intelligence,
doi: 10.1109/TAI.2022.3221912. (pdf) |
| 128.
S. Samant, P. K. Nanda, A. Ghosh and
A. K. Panda, "Noisy
multimodal brain image registration using markov random field model",
Biomedical Signal Processing and Control,
103426, 2022. (pdf) |
| 127.
A. Law and A. Ghosh, "Multi-label Classification
using Binary Tree of Classifiers",
IEEE Transactions on Emerging Topics in Computational Intelligence,
pp. 1- 13, 2021. (pdf) |
| 126.
H. Kalia, S. Dehuri, and
A. Ghosh, "Fitness inheritance in multi-objective genetic algorithms: a case study on fuzzy classification rule mining",
International Journal of Advanced Intelligence Paradigms,
vol.23, pp. 89-112, 2022. |
| 125.
A. S. Saud, S. Shakya, and A. Ghosh, "Hill-climbing powered gated recurrent
unit network to predict stock trading signals using mean average convergence divergence indicator",
Journal of Theoretical and Applied Information Technology,
vol. 99(7), pp. 1493, 2021. (pdf) |
| 124.
A. Hatuaa, B. N. Subudhi, T. Veerakumar and A. Ghosh, "Early
detection of diabetic retinopathy from big data in hadoop framework",
Displays,
102061, 2021. (pdf) |
| 123.
R. Roy, S. Ghosh, and A. Ghosh, "Clinical
Ultrasound Image Standardization using Histogram
Specification", Computers in Biology
and Medicine, vol. 120, pp. 103746, 2020. (pdf) |
| 122.
A. Law, B. Evani
and A. Ghosh, ''Optimized functional link artificial neural network
for multi-label classification", Australian Journal of Intelligent
Information Processing Systems, Special Issue: Neural Information
Processing, 26th International Conference on Neural
Information Processing (ICONIP
2019), Sydney, Australia, vol.16, issue 4, pp. 56-63, 2019. (pdf)
|
| 121. A. Ghosh,
D. Chakraborty and R. Roy, "Activities of IEEE-GRSS Kolkata
Chapter", IEEE Geoscience and Remote Sensing Magazine, 2019.
(accepted) |
| 120. B.
N. Subudhi, T. Veerakumar, S. Esakkirajan and A. Ghosh, "Kernelized
Fuzzy Modal Variation for Local Change Detection from Video Scenes", IEEE
Transactions on Multimedia, 2019. (pdf) |
| 119.
A. Law and
A. Ghosh,
"Multi-label
Classification using a Cascade of Stacked Autoencoder and Extreme Learning
Machines", Neurocomputing, vol. 358, pp. 222-234, 2019.
(pdf) |
| 118.
B. N. Subudhi, D. K. Rout and
A. Ghosh, "Big
Data Analytics for Video Surveillance", Multimedia Tools and
Applications, pp. 1-34, 2019. (pdf) |
| 117.
S. M. Roy and
A. Ghosh,
"Foreground Segmentation using Adaptive 3 Phase Background Model",
IEEE
Transactions on Intelligent Transportation Systems, 2019. (pdf) |
| 116. B. N. Subudhi,
T. Veerakumar, S. Esakkirajan,and
A. Ghosh, "Context
Dependent Fuzzy Associated Statistical Model for Intensity Inhomogeneity
Correction from Magnetic Resonance Images",
IEEE
Journal of Translational Engineering in Health and
Medicine,
vol. 7, pp. 1-9,
2019.
(pdf) |
| 115.
D. Chakraborty, V.
Narayanan and
A. Ghosh,
"Integration of Deep Feature Extraction and Ensemble Learning for Outlier
Detection", Pattern Recognition, vol. 89, pp. 161 171, 2019.
(CI-2) (pdf) |
| 114.
K. Ramachandra Murthy and
A. Ghosh,
Norm discriminant eigenspace transform for pattern classification
IEEE
Transactions on Cybernetics, vol. 49, issue 1, pp. 273 - 286, 2019.(pdf) |
| 113.
A. Mondal, A. Ghosh,
S. Ghosh, "Scaled and oriented object tracking using ensemble of multilayer perceptrons" Applied Soft Computing. vol. 73, pp. 1081-1094, 2018.
(CI-1) (pdf) |
| 112.
A. Ghosh, D.
Chakraborty, and A. Law, "Artificial
Intelligence in Internet of
Things",
CAAI Transactions on Intelligence Technology, vol. 3,
issue 4, pp. 208 218, 2018. (CI-6) (pdf)one of the most
highly cited papers on this topic |
| 110.
S.
M. Roy and A. Ghosh,"Real-time
Record Sensitive Background Classifier (RSBC)", Expert Systems and
Applications, vol. 119, issue 1, pp. 104-117, 2018.
(CI-1) (pdf) |
| 109.
R. Roy, S. Ghosh and
A.
Ghosh, "Speckle
de-noising of clinical ultrasound images based on fuzzy spel conformity in
its adjacency", Applied Soft Computing, vol. 73. pp. 394-417,
2018. (CI-2) (pdf) |
| 108. H. Kalia, S. Dehuri,
A. Ghosh and
S. B. Cho, Surrogate-assisted multiobjective genetic algorithms for
fuzzy-rule based classification , International Journal of Fuzzy Systems,
vol. 20, issue 6, pp. 1938 1955,
2018. |
| 107.
A. Ghosh and S. Bandyopadhyay, Image
Co-segmentation Using Dual Active Contour , Applied Soft Computing,
vol. 66,
pp. 413-427, 2018. (CI-3) (pdf) |
| 106. K. Ramachandra Murthy
and A. Ghosh, "Noisy-free
length discriminant analysis with cosine hyperbolic framework for
dimensionality reduction", Expert Systems with Applications, vol.
81, pp. 88-107, 2017. (CI-1) (pdf) |
| 105.
S. Roy and
A. Ghosh, "Real-time
Adaptive Histogram Min-Max Bucket (HMMB) Model for Background Subtraction ,
IEEE Transactions on Circuits and Systems for Video Technology, vol.
28, issue 7, pp. 1513-1525, 2017.
(CI-6) (pdf) |
| 104.
A. Datta, S. Ghosh
and A. Ghosh,
"Supervised Feature Extraction of Hyperspectral Images using Partitioned
Maximum Margin Criterion", IEEE Geoscience and
Remote Sensing Letters, vol. 14, issue 1, pp. 82-86 2016.
(CI-7)
(pdf) |
| 103.
A. Mondal, S. Ghosh and
A. Ghosh, "Partially
Camouflaged Object Tracking using Modified Probabilistic Neural Network and
Fuzzy Energy based Active Contour",
International Journal of Computer Vision, vol. 122,
issue 1, 2016. (CI-3) (pdf) |
| 102.
K. Ramachandra Murthy and
A. Ghosh, "Moments
discriminant analysis for supervised dimensionality reduction",
Neurocomputing, vol 237, pp. 114-132, 2016.
(CI-2) (pdf) |
| 101.
A. Datta, S. Ghosh and
A.
Ghosh, "Unsupervised Band
Extraction of Hyperspectral Images using Clustering and kernel Principal
Component Analysis" International Journal of Remote Sensing,
vol. 38, issue 3, pp. 850-873, 2016.
(CI-8) (pdf) |
| 100.
B. N. Subudhi T. Veerakumar, S.
Essakkiranjan and A. Ghosh,
"Tumor or Abnormality Identification from Magnetic Resonance Images using
Statistical Region Fusion based Segmentation", Magnetic Resonance Imaging,
vol. 34, issue 9, pp. 1292-1304, 2016. (CI-12) (pdf) |
| 99.
B. N. Subudhi, S. Ghosh, P. K. Nanda, and A. Ghosh,
"Moving
object detection using spatio-temporal multilayer compound Markov Random
Field and histogram thresholding based change detection",
Multimedia Tools and Applications, pp. 1-33, 2016. (CI-10) (pdf) |
| 98.
B. N. Subudhi, S. Ghosh, S. C. K. Shiu and A. Ghosh,
"Statistical
Feature Bag based Background Subtraction for Local Change Detection",
Information Sciences, vol. 366, issue 1, pp. 31-47, 2016. (CI-11) (pdf)
|
| 97.
A. Mondal, S. Ghosh, and A. Ghosh,
"Robust
Global and Local Fuzzy Energy based Active Contour for Image Segmentation",
Applied Soft Computing, Vol. 47, issue 1. pp. 191-215,
2016. (CI-24) (pdf) |
| 96.
A. Ghosh, "Big
Data and Its Utility", Consulting Ahead, vol. 10, issue 1, pp.
52-68, 2016. (pdf) |
| 95.
H.
Kalia, S. Dehuri, A. Ghosh,
S. B. Cho, "On
the mining of fuzzy association rules using multi-objective genetic
algorithms",
International Journal of Data Mining, Modelling and
Management, vol. 18, issue 1, pp. 1-31, 2016.
(CI-3) |
| 94.
B. N. Subudhi, S.
Ghosh and A. Ghosh, "Integration
of Fuzzy Markov Random Field and Local Information for Separation of Moving
Objects and Shadows", Information Sciences, vol. 331, pp. 15-31,
2016. (CI-8) (pdf) |
| 93.
P. Mahanta, D. K.
Bhattacharyya, A. Ghosh, "MIPCE:
An MI-based protein complex extraction technique", Journal of
Biosciences, vol. 40, issue 4, pp. 701-708, 2015. (CI-1) |
| 92. A. Datta, S.
Ghosh and A. Ghosh, "Combination
of clustering and ranking techniques for unsupervised band selection of
hyperspectral images", IEEE Journal of Selected Topics in Applied
Earth Observations and Remote Sensing, vol. 8, issue 6, pp. 2814-2823,
2015. (CI-24) (pdf) |
| 91. M. Roy,
F. Melgani, A. Ghosh, E. Blanzieri, and S. Ghosh, "Land-cover
classification of remotely sensed images using compressive sensing having
severe scarcity of labeled patterns", IEEE Geosciences and Remote
Sensing Letters, vol. 12, no. 6, pp. 1257-1261, 2015. (CI-8) (pdf) |
| 90. S. Dehuri, B. S.
Mishra, A. Ghosh, R. Mall, and G. N. Wang, "Data
clustering: review and investigation of parallel genetic algorithms for
revealing clusters", International Journal of Applied Management
Science, vol. 6, issue 3, pp. 212-243, 2014. (CI-2) |
| 89. B. N.
Subudhi, S. Ghosh, and A. Ghosh, "Application
of Gibbs Markov random field and Hopfield-type neural networks for detecting
moving objects from video sequences captured by static camera
", Soft Computing, vol. 19, no. 10, pp. 2769-2781, 2014.
(CI-8) (pdf) |
| 88.
H. Kalia, S. Dehuri,
A. Ghosh, "A
comprehensive survey of multi-objective genetic and fuzzy approaches in rule
mining problem of knowledge discovery in databases", International
Journal of Information Technology, Communications and Convergence, Vol.
3, no. 1, pp. 13 - 45, 2014. |
| 87. A. Mondal,
S. Ghosh, and A. Ghosh, "Efficient
silhouette-based contour tracking using local information", Soft Computing, vol. 20, pp.785-805, 2014.
(CI-7) (pdf) |
| 86.
P. Mahanta,
D. K. Bhattacharyya, A. Ghosh, "FUMET: A fuzzy network module extraction
technique for gene expression data",
Journal of Biosciences, vol. 9, no. 3, pp. 351-364,
2014. (CI-5) (pdf) |
| 85. M. Roy,
S. Ghosh and A. Ghosh,
"A novel approach for change detection of remotely sensed images using
semi-supervised multiple classifier system", Information Sciences, vol.
269, pp.
35-47, 2014. (CI-45) (pdf) |
| 84. M. Roy,
S. Ghosh and A. Ghosh,
"A neural approach under active learning mode for change detection in
remotely sensed images", IEEE Journal of Selected Topics in Applied
Earth Observations and Remote Sensing, vol. 7, no. 4,
pp. 1200-1206, 2014. (CI-10) (pdf) |
| 83.
A. Datta, S. Ghosh and A. Ghosh, "Band
elimination of hyperspectral
imagery using partitioned
band image
correlation and capacitory
discrimination", International Journal of
Remote Sensing, vol. 35, pp.
554-577, 2014. (CI-27) (pdf)
|
| 82.
A. Ghosh, A. Mondal and
S.
Ghosh, "Moving
object detection using Markov
random field and
distributed differential
evolution", Applied Soft Computing,
vol. 15, pp.
121-136, 2014. (CI-19) (pdf)
|
| 81. B. N.
Subudhi, F. Bovolo, A. Ghosh and L. Bruzzone, "Spatio-contextual
fuzzy clustering with Markov
random field model for
change detection in
remotely sensed
images", Optics & Laser Technology,
vol. 57, pp.
284-292, 2014. (CI-41) |
| 80.
S. Ghosh,
M. Roy, and A. Ghosh, "Semi-supervised
change detection using modified self-organizing feature map neural network",
Applied Soft Computing,
vol. 15, pp. 1-20, 2014.
(CI-39)
(pdf) |
| 79.
M. Roy, D. Routaray, S.
Ghosh and A. Ghosh, "Ensemble
of multilayer perceptrons for change detection in remotely sensed images",
IEEE Geosciences and Remote Sensing Letters, vol. 11, pp. 49-53, 2014.
(CI-8)
(pdf) |
| 78. M.
Roy, S. Ghosh, and A. Ghosh, "Change
detection in remotely sensed images using semi-supervised clustering
algorithms", International Journal of Knowledge
Engineering and Soft Data Paradigms,
vol. 4, pp.118-137, 2013. (CI-2) |
| 77.
S. Poddar, S.
Tewary, D. Sharma, V. Karar, A. Ghosh and S. K. Pal, "Non-parametric
modified histogram
equalization for contrast
enhancement", IET Image
Processing, vol. 7, pp. 641-652, 2013.
(CI-49)
(pdf) |
| 76. K. R. Murthy,
S. N. Biswas and A. Ghosh, "A fast and efficient clutter rejection
algorithm for SAR imagery", IEEE Transactions on
Aerospace and Electronic Systems,
vol. 49, pp. 2431-2439, 2013. (pdf) |
| 75.
S. Dehuri and A. Ghosh, "Revisiting
evolutionary algorithms in feature selection and nonfuzzy/fuzzy rule based
classification", WIREs Data Mining and Knowledge Discovery,
vol. 3, pp.
83-108, 2013. (CI-4) (pdf) |
| 74. A. Ghosh,
B. N. Subudhi and L. Bruzzone, "Integration
of Gibbs Markov random field and
hopfield-type neural
networks for unsupervised
change
detection in remotely
sensed multitemporal
images",
IEEE Transactions on Image Processing, vol. 22, pp.
3087-3096, 2013. (CI-54) (pdf) |
| 73. B. Nath, D. K.
Bhattacharyya and A. Ghosh, "Incremental
Association Rule Mining: A Survey", WIREs Data Mining and Knowledge
Discovery, vol. 3, pp. 157-169, 2013.
(CI-39) |
| 72. B. N. Subudhi,
S. Ghosh and A. Ghosh,
"Change
detection for moving object segmentation with robust background construction
under Wronskian framework", Machine Vision and its Application,
vol 24, no. 4, pp. 795-809, 2013. (CI-24) (pdf) |
| 71. A. Halder, S. Ghosh and A. Ghosh,
"Aggregation
pheromone metaphor for semi-supervised classification" Pattern
Recognition, vol. 46, pp. 2239--2248, 2013.
(CI-10)
(pdf) |
| 70. A. Ghosh, A. Datta, and
S. Ghosh, "Self-adaptive
differential evolution for
feature selection in
hyperspectral image
data'", Applied Soft Computing,
vol. 13, pp. 1969-1977,
2013. (CI-68) (pdf) |
| 69.
H. Kalia, S.
Dehuri, A. Ghosh, "A
survey on fuzzy association rule
mining", International Journal of Data Warehousing
and Mining (IJDWM), vol. 9, pp. 1-27, 2013.
(CI-15) |
| 68. A. Ghosh, B. N. Subudhi and S. Ghosh, "Object
detection from videos
captured by moving
camera by using fuzzy
edge incorporated Markov random
field and local
histogram
matching", IEEE Transactions on Circuits and
Systems for Video Technology, vol
22, no. 8, pp. 1127-1135, 2012.
(CI-36)
(pdf) |
| 67.
S. Dehuri, R. Roy, S. B cho,
A. Ghosh, "An
improved swarm optimized
functional link
artificial neural
network (ISO-FLANN) for classification",
Journal of Systems and Software, vol 85, no.
6, pp. 1333-1345, 2012.
(CI-102)
(pdf) |
| 66.
N. S. Mishra, S. Ghosh and
A. Ghosh, ``Fuzzy
clustering
algorithms incorporating
local information for
change detection in emotely
sensed
images", Applied Soft Computing, vol
12, no.
8, pp. 2683-2692, 2012.
(CI-67) (pdf) |
| 65. B. S. P. Mishra, S. Dehuri, R. Mall and A. Ghosh "Parallel
single and multiple objectives genetic algorithms: a survey",International
Journal of Applied Evolutionary Computation, vol. 2, pp. 21-57, 2011.
(CI-11) |
| 64. S. Patra, S. Ghosh and A. Ghosh, "Histogram
thresholding for unsupervised change detection of remote sensing images",
International
Journal of Remote Sensing, vol 32, no. 21, pp. 6071-6089, 2011. (CI-50)
(pdf) |
| 63. B. N. Subudhi, P. K. Nanda and A. Ghosh, "Entropy
based region selection for moving object detection",
Pattern
Recognition Letters, vol. 32, no. 15, pp. 2097-2108, 2011.
(CI-19) (pdf) |
| 62. A. Halder, A. Ghosh and S. Ghosh, "Supervised and
unsupervised land-cover map generation from remotely sensed images using ant based systems",
Applied Soft Computing, vol. 11, no. 8, pp. 5770-5781, 2011.
(CI-37) (pdf) |
| 57. A. Ghosh, N. S. Mishra and S. Ghosh, "Fuzzy clustering algorithms for unsupervised change detection in remote
sensing images", Information Sciences, vol. 181, pp. 699-715,
2011. (CI-243) (pdf)
one of the most
highly cited papers on this topic
|
| 56. A. Ghosh, B. Uma Shankar, L. Bruzzone and S. K. Meher,
"Neuro-fuzzy-combiner:
An effective multiple
classifier system" International Journal of
Knowledge Engineering and Soft Data Paradigm, vol. 2, no. 2, pp. 107-129, 2010.
(CI-23) (pdf) |
| 55. A. Halder, A. Ghosh and
S. Ghosh,
"Aggregation
pheromone density based pattern classification",
Fundamenta
Informaticae, vol. 92, no. 4, pp 345-362, 2009. (CI-21)
(pdf) |
| 54. S. Ghosh, M. Kothari, A. Halder and A. Ghosh, "Use
of aggregation pheromone density for image segmentation”, Pattern
Recognition Letters, vol. 30, pp. 939-949, 2009. (CI-21)
(pdf) |
| 53. S. Ghosh, S. Patra and A. Ghosh, "An
unsupervised context-sensitive change detection technique based on modified
self-organizing feature map neural network", International Journal
of Approximate Reasoning, vol. 50, pp. 37-50, 2009. (CI-39)
(pdf) |
| 52. A. Ghosh, S. K. Meher and B. Uma Shankar, "A
novel approach to neuro-fuzzy classification", Neural Networks,
vol. 22, pp. 100-109, 2009. (CI-60) (pdf) |
| 51.
B. Nath, D.K. Bhattacharyya, A. Ghosh,
"Faster Generation of Association Rules", International Journal of
Information Technology and Knowledge Management, vol 1, pp 267-279, 2008. |
| 50. S. Dehuri, A. Ghosh and S.-B. Cho, "Particle
swarm optimized polynomial neural network for classification: a multi-objective view”,
International Journal of Intelligent Defence Support Systems, vol.1, pp.
225-253, 2008. (CI-4) |
| 49. A. Ghosh, A. Halder, M. Kothari and S. Ghosh,
"Aggregation
pheromone density based data clustering", Information Sciences,
vol. 178, no. 13, pp 2816-2831, 2008. (CI-60) (pdf) |
| 48. S. Patra, S. Ghosh and A. Ghosh, "Change detection of remote
sensing Images with semi-supervised multilayer perceptron" Fundamenta
Informaticae, vol. 84, no. 3/4, pp. 429-442, 2008. (CI-20)
(pdf) |
| 47. A. Ghosh and M. K. Das, "Non-dominated rank based
sorting genetic algorithm", Fundamenta Informatica, vol. 83, no. 3,
pp. 231-152, 2008. (CI-12) (pdf) |
| 46. A. Ghosh, S. K. Meher and B. Uma Shankar, "A
novel fuzzy classifier based on product aggregation operator", Pattern
Recognition, vol. 41, pp. 961-971, 2008. (CI-41) (pdf) |
| 45. S. Dehuri, S. Patnaik, A. Ghosh, and R. Mall, "Application
of elitist multi-objective genetic algorithm in classification
rule generation", Applied Soft Computing Journal,
vol. 8, pp. 477-487, 2008. (CI-98) (pdf) |
| 44. A. Ghosh
and B. Parai, "Protein
secondary structure prediction using distance based classifiers",
International Journal of Approximate Reasoning, vol. 47, pp. 37-44,
2008. (CI-13) (pdf) |
| 43. P. Kanungo, P. K. Nanda and A. Ghosh, "Classification of
objects and background using parallel genetic algorithm based clustering", Electronic
Letters on Computer Vision and Image Analysis, vol. 6, no. 3, pp. 42-53, 2007.
(CI-12) (pdf) |
| 42. A. Ghosh and A. Sen, "Hybrid-genetic algorithms
for flexible ligand docking", Journal of Intelligent and Fuzzy Systems,
vol. 18, no. 7, pp. 561-574, 2007. (CI-2) |
| 41. S. Dehuri, A. Ghosh and R. Mall, "Evolving
functional link artificial neural network for classification in data mining", Journal
of Systems, Science and Engineering, vol. 15, no. 2, pp. 34-41, 2007. |
| 40. A. Ghosh, U. Seiffert and L.C. Jain, "Evolutionary computation in
bioinformatics", Journal of Intelligent and Fuzzy Systems, vol. 18, no. 7,
pp. 25-26, 2007. |
| 39. S. K. Meher, B. Uma Shankar and A. Ghosh, "Wavelet-feature-based
classifiers for multispectral remote sensing images", IEEE Transactions on Geosciences and Remote Sensing, vol. 45, no. 6,
pp. 1881-1886, 2007. (CI-70)
(pdf) |
| 38. S. Dehuri, A. Ghosh and R. Mall, "Parallel multi-objective
genetic algorithm for classification rule mining",
IETE Journal of Research, vol. 53, no. 5, pp. 475-483, 2007.
(CI-7) |
| 37. B. Uma Shankar, S. K. Meher and A. Ghosh, "Neuro-wavelet
classifier for multispectral remote sensing images", International
Journal of Wavelets, Multiresolution and Information Processing,
vol. 5, no. 4, pp. 589-612, 2007. (CI-15) (pdf) |
| 36. S. Ghosh, L. Bruzzone, S. Patra, F. Bovolo, and A. Ghosh,
"A
context-sensitive technique for unsupervised change detection
based on Hopfield type neural networks", IEEE Transactions on Geoscience
and Remote Sensing, vol. 45, pp. 778-789, 2007.
(CI-137) (pdf) |
| 35. S. Rakshit, A. Ghosh and B. Uma Shankar, "Fast
mean filtering technique", Pattern Recognition,
vol. 40, pp. 890-897, 2007. (CI-45) (pdf) |
| 34. S. Dehuri, A. Ghosh and R. Mall, "Genetic
algorithms for multi-criterion classification and clustering in data
mining", International Journal of Computing and Information Sciences vol.
4, no. 3, pp. 143-154, 2006. (CI-27) (pdf) |
| 33. S. Dehuri, A. K. Jagadev, A. Ghosh and R. Mall, "Multi-objective
genetic algorithm for association rule mining using a
homogeneous dedicated cluster of workstations", American Journal of Applied Sciences, vol. 3,
pp. 2086-2095, 2006. (CI-55) (pdf) |
| 32. S. Tsutsui, M. Pelikan and A. Ghosh, "Edge histogram based
sampling with local search for solving permutation problems",
International Journal of Hybrid Intelligent Systems, vol. 3, pp. 11-22, 2006.
(CI-9) (pdf) |
| 31. S. Dehuri, A. Ghosh and R. Mall, "Genetic k-medoid
clustering" ICFAI Journal of Information Technology,
vol. 2, pp. 17-28, 2006. |
| 30. S. Dehuri, C. Mohapatra, A. Ghosh and R. Mall, "A
comparative study of clustering algorithms", Information
Technology Journal, vol. 5, pp. 551-559, 2006.
(CI-12) (pdf) |
| 29. S. Ghosh, S. Patra, M. Kothari and A. Ghosh,
"Supervised change detection in multi-temporal remote-sensing
images using multi-layer perceptron", ANVESA: The Journal of F. M. University,
vol. 1, pp. 48-60, 2005. |
| 28. A. Ghosh and S. Dehuri, "Evolutionary algorithms for multi-criterion
optimization: a survey", International Journal of Computing and
Information Sciences, vol. 2, pp. 38-57, 2004.
(CI-160) (pdf) |
| 27. A. Ghosh and H. Muehlenbein, "Univariate marginal
distribution algorithms for non-stationary optimization problems", International Journal of Knowledge Based Intelligent
Engineering Systems, vol. 8, pp. 129-138, 2004.
(CI-10) |
| 26. A. Ghosh and B. Nath, "Multiple
objective rule mining using genetic algorithms", Information Sciences,
vol. 163. pp. 123-133, 2004. (CI-232) (pdf) |
| 25. S. K. Pal and A. Ghosh, "Soft
computing data mining", Information Sciences, vol. 163. pp. 1-3, 2004.
(CI-26) (pdf) |
| 24. A. Ghosh and A. A. Freitas, "Data mining and knowledge
discovery with evolutionary algorithms", IEEE Transactions on Evolutionary
Computations, vol. 7, no. 6, pp. 517-518, 2003. (CI-15)
(pdf) |
| 23. S. Ghosh, A. Ghosh and S.K. Pal, "Incorporating
ancestors' influence in genetic algorithms", Applied Intelligence,vol.
18, pp. 7-25, 2003. (CI-11) (pdf) |
| 22. S. Ghosh and A. Ghosh, "Image ambiguity
optimization for object extraction : a soft computing approach", International
Journal of Fuzzy Systems, vol. 4, no. 2, pp. 673-679, 2002.
(CI-1)
(pdf) |
| 21. S. K. Pal, A. Ghosh and B. Uma Shankar, "Segmentation
of remotely sensed images with fuzzy thresholding, and quantitative evaluation'', International
Journal of Remote Sensing, vol. 21, pp. 2269-2300, 2000. (CI-159)
(pdf) |
| 20. A. Ghosh, S. Tsutsui, H. Tanaka and D. Corne, "Genetic algorithms with substitution and re-entry of individuals",
International Journal of Knowledge Based Intelligent Engineering Systems,
vol. 4, pp. 64-71, 2000. (CI-5) (pdf)
|
| 19. A. Ghosh and H. Tanaka, "On making neural network
based learning systems robust'', IETE Journal of Research, vol. 44, pp.
219-225, 1998. |
| 18. S. Tsutsui, A. Ghosh and Y. Fujimoto, "Search
space division in GAs using phenotypic properties", Information Sciences,
vol. 109, pp. 119-133, 1998. (CI-14) (pdf) |
| 17. S. De, S.K. Pal and A. Ghosh,"Genotypic
and phenotypic assortative mating in genetic algorithms", Information
Sciences, vol. 105, pp. 209-226, 1998. (CI-28) (pdf) |
| 16. S. Tsutsui and A. Ghosh, "Genetic algorithms with
a robust solution searching scheme'', IEEE Transactions on Evolutionary
Computations, vol. 1, no. 3, pp. 201-208, 1997. (CI-332)
(pdf) |
| 15. S. K. Pal, S. De and A. Ghosh, "Designing Hopfield type
networks using genetic algorithms and its comparison with simulated annealing'',
International Journal of Pattern Recognition and Artificial Intelligence, vol.
11, no. 3, pp. 447-461, 1997. (CI-41) (pdf) |
| 14. A. Ghosh, "Research activities related to fuzzy sets and fuzzy logic at the Machine Intelligence Unit of the Indian Statistical Institute, Calcutta, India'', Fuzzy Sets and
Systems, vol. 88, pp. 130-131. 1997. (pdf) |
| 13. S. Tsutsui, Y. Fujimoto and A. Ghosh, "Forking GAs: GAs
with search space division schemes'', Evolutionary Computation vol. 5, no. 1,
pp. 61-80, 1997. (CI-140) (pdf) |
| 12. A. Ghosh, S. Tsutsui and H. Tanaka, "Genetic search
with aging of individuals'', International Journal of Knowledge Based
Intelligent Engineering Systems, vol. 1, pp. 86-103, 1997. (CI-57) |
| 11. S. K. Pal and A. Ghosh, "Neuro-fuzzy
computing for image processing and pattern recognition'', International
Journal of Systems Science, vol. 27, pp. 1179-1193, 1996. (CI-33) |
| 10. A. Ghosh, "Use
of fuzziness measures in layered networks for object extraction : a generalization'', Fuzzy
Sets and Systems, vol.72, no. 3, pp.331-348, 1995. (CI-58)
(pdf)
|
| 9. A. Ghosh, N. R. Pal and S. K. Pal, "Modeling
of component failure in neural networks for robustness evaluation : an application to
object extraction'', IEEE Transactions on Neural Networks, vol. 6,
pp.648-656, 1995. (CI-7) (pdf) |
| 8. A. Ghosh, N. R. Pal and S. K. Pal, "Neural computing
: an introduction and some applications'', Students' Journal of the Institute of
Electronics and Telecommunication Engineers, vol. 35, pp. 105-125, 1994.
(CI-2) |
| 7. A. Ghosh, N. R. Pal and S. K. Pal, "Self-organization
for object extraction using multilayer neural network and fuzziness measures'', IEEE
Transactions on Fuzzy Systems, vol-1, pp. 54-68, 1993. (CI-167)
(pdf) |
| 6. A. Ghosh, N. R. Pal and S. K. Pal, "Object background
classification using Hopfield type neural network'', International Journal of
Pattern Recognition and Artificial Intelligence, vol-6, no-5, pp. 989-1008, 1992.
(CI-47) |
| 5. S. K. Pal and A. Ghosh, "Fuzzy
geometry in image analysis'', Fuzzy Sets and Systems, vol-48, no-2, pp.
23-40, 1992. (CI-108) |
| 4. S. K. Pal and A. Ghosh, "Image
segmentation using fuzzy correlation'', Information Sciences, vol-62, no-3,
pp. 223-250, 1992. (CI-57) (pdf)
|
| 3. A. Ghosh and S. K. Pal, "Neural
network, self-organization and object extraction'', Pattern Recognition Letters,
vol-13, no-5, pp. 387-397, 1992. (CI-54) |
| 2. A. Ghosh, N. R. Pal and S. K. Pal, "Image segmentation using a
neural network'', Biological Cybernetics, vol-66, no-2, pp. 151-158, 1991.
(CI-61) (pdf) |
| 1. S. K. Pal and A. Ghosh, "Index
of area coverage of fuzzy image subsets and object extraction'', Pattern
Recognition Letters, vol-11, no-12, pp. 831-841, 1990. (CI-61)
(pdf) |
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