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1,252 results on '"Nasipuri, Mita"'

51. Human Gender Classification Based on Hand Images Using Deep Learning

Author

Mukherjee, Rajesh, Bera, Asish, Bhattacharjee, Debotosh, Nasipuri, Mita, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Sk, Arif Ahmed, editor, Turki, Turki, editor, Ghosh, Tarun Kumar, editor, Joardar, Subhankar, editor, and Barman, Subhabrata, editor

Published
2022
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52. Script Identification in Natural Scene Text Images by Learning Local and Global Features on Inception Net

Author

Dutta, Kalpita, Dastidar, Shuvayan Ghosh, Das, Nibaran, Kundu, Mahantapas, Nasipuri, Mita, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Raman, Balasubramanian, editor, Murala, Subrahmanyam, editor, Chowdhury, Ananda, editor, Dhall, Abhinav, editor, and Goyal, Puneet, editor

Published
2022
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55. Genetic Dropout: An Application to Handwritten Indic Script Classification

Author

Chakraborty, Saikat, Mondal, Riktim, Singh, Pawan Kumar, Sarkar, Ram, Nasipuri, Mita, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Mandal, Jyotsna Kumar, editor, and De, Debashis, editor

Published
2022
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58. Recognition of Offline Handwritten Devanagari Numerals using Regional Weighted Run Length Features

Author

Singh, Pawan Kumar, Das, Supratim, Sarkar, Ram, and Nasipuri, Mita

Subjects
Computer Science - Computer Vision and Pattern Recognition, 68T10, 68U10
Abstract

Recognition of handwritten Roman characters and numerals has been extensively studied in the last few decades and its accuracy reached to a satisfactory state. But the same cannot be said while talking about the Devanagari script which is one of most popular script in India. This paper proposes an efficient digit recognition system for handwritten Devanagari script. The system uses a novel 196-element Mask Oriented Directional (MOD) features for the recognition purpose. The methodology is tested using five conventional classifiers on 6000 handwritten digit samples. On applying 3-fold cross-validation scheme, the proposed system yields the highest recognition accuracy of 95.02% using Support Vector Machine (SVM) classifier., Comment: 6 pages

Published
2018
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59. Combining Multi-level Contexts of Superpixel using Convolutional Neural Networks to perform Natural Scene Labeling

Author

Das, Aritra, Ghosh, Swarnendu, Sarkhel, Ritesh, Choudhuri, Sandipan, Das, Nibaran, and Nasipuri, Mita

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Modern deep learning algorithms have triggered various image segmentation approaches. However most of them deal with pixel based segmentation. However, superpixels provide a certain degree of contextual information while reducing computation cost. In our approach, we have performed superpixel level semantic segmentation considering 3 various levels as neighbours for semantic contexts. Furthermore, we have enlisted a number of ensemble approaches like max-voting and weighted-average. We have also used the Dempster-Shafer theory of uncertainty to analyze confusion among various classes. Our method has proved to be superior to a number of different modern approaches on the same dataset., Comment: Accepted for publication in the Proceedings of Second International Conference on Computing and Communication 2018, Sikkim Manipal Institute of Technology, Sikkim, India

Published
2018

60. Handwritten Isolated Bangla Compound Character Recognition: a new benchmark using a novel deep learning approach

Author

Roy, Saikat, Das, Nibaran, Kundu, Mahantapas, and Nasipuri, Mita

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In this work, a novel deep learning technique for the recognition of handwritten Bangla isolated compound character is presented and a new benchmark of recognition accuracy on the CMATERdb 3.1.3.3 dataset is reported. Greedy layer wise training of Deep Neural Network has helped to make significant strides in various pattern recognition problems. We employ layerwise training to Deep Convolutional Neural Networks (DCNN) in a supervised fashion and augment the training process with the RMSProp algorithm to achieve faster convergence. We compare results with those obtained from standard shallow learning methods with predefined features, as well as standard DCNNs. Supervised layerwise trained DCNNs are found to outperform standard shallow learning models such as Support Vector Machines as well as regular DCNNs of similar architecture by achieving error rate of 9.67% thereby setting a new benchmark on the CMATERdb 3.1.3.3 with recognition accuracy of 90.33%, representing an improvement of nearly 10%.

Published
2018
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67. A Harmony Search Based Wrapper Feature Selection Method for Holistic Bangla word Recognition

Author

Das, Supratim, Singh, Pawan Kumar, Bhowmik, Showmik, Sarkar, Ram, and Nasipuri, Mita

Subjects
Computer Science - Computer Vision and Pattern Recognition, 68T10
Abstract

A lot of search approaches have been explored for the selection of features in pattern classification domain in order to discover significant subset of the features which produces better accuracy. In this paper, we introduced a Harmony Search (HS) algorithm based feature selection method for feature dimensionality reduction in handwritten Bangla word recognition problem. This algorithm has been implemented to reduce the feature dimensionality of a technique described in one of our previous papers by S. Bhowmik et al.[1]. In the said paper, a set of 65 elliptical features were computed for handwritten Bangla word recognition purpose and a recognition accuracy of 81.37% was achieved using Multi Layer Perceptron (MLP) classifier. In the present work, a subset containing 48 features (approximately 75% of said feature vector) has been selected by HS based wrapper feature selection method which produces an accuracy rate of 90.29%. Reasonable outcomes also validates that the introduced algorithm utilizes optimal number of features while showing higher classification accuracies when compared to two standard evolutionary algorithms like Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and statistical feature dimensionality reduction technique like Principal Component Analysis (PCA). This confirms the suitability of HS algorithm to the holistic handwritten word recognition problem.

Published
2017

68. Computational drug repurposing for viral infectious diseases: a case study on monkeypox.

Author

Saha, Sovan, Chatterjee, Piyali, Nasipuri, Mita, Basu, Subhadip, and Chakraborti, Tapabrata

Subjects
DRUG repositioning, VIRUS diseases, MONKEYPOX, COMMUNICABLE diseases, DRUG target
Abstract

The traditional method of drug reuse or repurposing has significantly contributed to the identification of new antiviral compounds and therapeutic targets, enabling rapid response to developing infectious illnesses. This article presents an overview of how modern computational methods are used in drug repurposing for the treatment of viral infectious diseases. These methods utilize data sets that include reviewed information on the host's response to pathogens and drugs, as well as various connections such as gene expression patterns and protein–protein interaction networks. We assess the potential benefits and limitations of these methods by examining monkeypox as a specific example, but the knowledge acquired can be applied to other comparable disease scenarios. [ABSTRACT FROM AUTHOR]

Published
2024
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70. Breast Abnormality Detection Using Texture Feature Extracted by Difference-Based Variable-Size Local Filter (DVLF)

Author

Pramanik, Sourav, Bhattacharjee, Debotosh, Nasipuri, Mita, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Pan, Indrajit, editor, Mukherjee, Anirban, editor, and Piuri, Vincenzo, editor

Published
2021
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71. Analysis of Large-Scale Human Protein Sequences Using an Efficient Spark-Based DBSCAN Algorithm

Author

Sekhar Bandyopadhyay, Soumyendu, Kumar Halder, Anup, Chatterjee, Piyali, Sroka, Jacek, Nasipuri, Mita, Basu, Subhadip, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Bhattacharjee, Debotosh, editor, Kole, Dipak Kumar, editor, Dey, Nilanjan, editor, Basu, Subhadip, editor, and Plewczynski, Dariusz, editor

Published
2021
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72. A Novel Approach to 3D Face Registration for Biometric Analysis Using RCompute_ICP

Author

Bagchi, Parama, Bhattacharjee, Debotosh, Nasipuri, Mita, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Bhattacharjee, Debotosh, editor, Kole, Dipak Kumar, editor, Dey, Nilanjan, editor, Basu, Subhadip, editor, and Plewczynski, Dariusz, editor

Published
2021
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77. Image Denoising Using Generative Adversarial Network

Author

Dey, Ratnadeep, Bhattacharjee, Debotosh, Nasipuri, Mita, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Mandal, J. K., editor, and Banerjee, Soumen, editor

Published
2020
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78. Pose Registration of 3D Face Images

Author

Dutta, Koushik, Bhattacharjee, Debotosh, Nasipuri, Mita, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Mandal, J. K., editor, and Banerjee, Soumen, editor

Published
2020
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79. A Multi-Scale Patch-Based Deep Learning System for Polyp Segmentation

Author

Banik, Debapriya, Bhattacharjee, Debotosh, Nasipuri, Mita, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Chaki, Rituparna, editor, Cortesi, Agostino, editor, Saeed, Khalid, editor, and Chaki, Nabendu, editor

Published
2020
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80. Object Detection in Rainy Condition from Video Using YOLO Based Deep Learning Model

Author

Dey, Ratnadeep, Bhattacharjee, Debotosh, Nasipuri, Mita, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Chaki, Rituparna, editor, Cortesi, Agostino, editor, Saeed, Khalid, editor, and Chaki, Nabendu, editor

Published
2020
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81. Closed-Set Device-Independent Speaker Identification Using CNN

Author

Chakraborty, Tapas, Barai, Bidhan, Chatterjee, Bikshan, Das, Nibaran, Basu, Subhadip, Nasipuri, Mita, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Bhateja, Vikrant, editor, Satapathy, Suresh Chandra, editor, Zhang, Yu-Dong, editor, and Aradhya, V. N. Manjunath, editor

Published
2020
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82. Automated Segmentation of Cervical Cells Using MSER Algorithm and Gradient Embedded Cost Function-Based Level-Set Method

Author

Roy, Kaushiki, Bhattacharjee, Debotosh, Nasipuri, Mita, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Gupta, Mousumi, editor, Konar, Debanjan, editor, Bhattacharyya, Siddhartha, editor, and Biswas, Sambhunath, editor

Published
2020
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83. Hand Segmentation from Complex Background for Gesture Recognition

Author

Paul, Soumi, Bhattacharyya, Arpan, Mollah, Ayatullah Faruk, Basu, Subhadip, Nasipuri, Mita, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Mandal, Jyotsna Kumar, editor, and Bhattacharya, Debika, editor

Published
2020
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84. Volumetric Density of Triangulated Range Images for Face Recognition

Author

Dutta, Koushik, Bhattacharjee, Debotosh, Nasipuri, Mita, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Gavrilova, Marina L., editor, Tan, C. J. Kenneth, editor, Saeed, Khalid, editor, and Chaki, Nabendu, editor

Published
2020
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89. An Improved Feature Descriptor for Recognition of Handwritten Bangla Alphabet

Author

Das, Nibaran, Basu, Subhadip, Sarkar, Ram, Kundu, Mahantapas, Nasipuri, Mita, and Basu, Dipak kumar

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Appropriate feature set for representation of pattern classes is one of the most important aspects of handwritten character recognition. The effectiveness of features depends on the discriminating power of the features chosen to represent patterns of different classes. However, discriminatory features are not easily measurable. Investigative experimentation is necessary for identifying discriminatory features. In the present work we have identified a new variation of feature set which significantly outperforms on handwritten Bangla alphabet from the previously used feature set. 132 number of features in all viz. modified shadow features, octant and centroid features, distance based features, quad tree based longest run features are used here. Using this feature set the recognition performance increases sharply from the 75.05% observed in our previous work [7], to 85.40% on 50 character classes with MLP based classifier on the same dataset., Comment: In proceedings of ICSIP 2009, pp. 451 to 454, August 2009, Mysore, India. arXiv admin note: substantial text overlap with arXiv:1203.0882, arXiv:1002.4040, arXiv:1410.0478

Published
2015

90. A GA Based approach for selection of local features for recognition of handwritten Bangla numerals

Author

Das, Nibaran, Basu, Subhadip, Saha, Punam Kumar, Sarkar, Ram, Kundu, Mahantapas, and Nasipuri, Mita

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Soft computing approaches are mainly designed to address the real world ill-defined, imprecisely formulated problems, combining different kind of novel models of computation, such as neural networks, genetic algorithms (GAs. Handwritten digit recognition is a typical example of one such problem. In the current work we have developed a two-pass approach where the first pass classifier performs a coarse classification, based on some global features of the input pattern by restricting the possibility of classification decisions within a group of classes, smaller than the number of classes considered initially. In the second pass, the group specific classifiers concentrate on the features extracted from the selected local regions, and refine the earlier decision by combining the local and the global features for selecting the true class of the input pattern from the group of candidate classes selected in the first pass. To optimize the selection of local regions a GA based approach has been developed here. The maximum recognition performance on Bangla digit samples as achieved on the test set, during the first pass of the two pass approach is 93.35%. After combining the results of the two stage classifiers, an overall success rate of 95.25% is achieved., Comment: In proceedings of UB NE ASEE 2009 conference, University of Bridgeport, USA

Published
2015

95. Face Image Retrieval Using Discriminative Ternary Census Transform and Spatial Pyramid Matching

Author

Hasnat, Abul, Halder, Santanu, Bhattacharjee, Debotosh, Nasipuri, Mita, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Yuan, Junsong, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Mandal, Jyotsna Kumar, editor, Mukhopadhyay, Somnath, editor, Dutta, Paramartha, editor, and Dasgupta, Kousik, editor

Published
2019
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96. Target Protein Function Prediction by Identification of Essential Proteins in Protein-Protein Interaction Network

Author

Basak, Soukhindra Nath, Biswas, Ankur Kumar, Saha, Sovan, Chatterjee, Piyali, Basu, Subhadip, Nasipuri, Mita, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Yuan, Junsong, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Mandal, Jyotsna Kumar, editor, Mukhopadhyay, Somnath, editor, Dutta, Paramartha, editor, and Dasgupta, Kousik, editor

Published
2019
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98. Pose-Invariant Hand Geometry for Human Identification Using Feature Weighted k-NN Classifier

Author

Bera, Asish, Bhattacharjee, Debotosh, Nasipuri, Mita, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Chandra, Peeyush, editor, Giri, Debasis, editor, Li, Fagen, editor, Kar, Samarjit, editor, and Jana, Dipak Kumar, editor

Published
2019
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99. A Two-Stage Approach for Text and Non-text Separation from Handwritten Scientific Document Images

Author

Bhowmik, Showmik, Kundu, Soumyadeep, De, Bikram Kumar, Sarkar, Ram, Nasipuri, Mita, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Chandra, Peeyush, editor, Giri, Debasis, editor, Li, Fagen, editor, Kar, Samarjit, editor, and Jana, Dipak Kumar, editor

Published
2019
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100. 3D Face Recognition Based on Volumetric Representation of Range Image

Author

Dutta, Koushik, Bhattacharjee, Debotosh, Nasipuri, Mita, Poddar, Anik, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Chaki, Rituparna, editor, Cortesi, Agostino, editor, Saeed, Khalid, editor, and Chaki, Nabendu, editor

Published
2019
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