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Table of Contents
Preface #8,0,-32767Editors #10,0,-32767Contributors #14,0,-327671: Artificial Intelligence for Document Image Analysis #16,0,-32767 1.1 Introduction #17,0,-32767 1.2 Optical Character Recognition #17,0,-32767 1.2.1 Dealing with Noise #18,0,-32767 1.2.2 Segmentation #21,0,-32767 1.2.3 Applications #21,0,-32767 1.2.3.1 Legal Industry
1.2.3.2 Banking
1.2.3.3 Healthcare
1.2.3.4 CAPTCHA
1.2.3.5 Automatic Number Recognition
1.2.3.6 Handwriting Recognition
1.3 Natural Language Processing #23,0,-32767 1.3.1 Tokenization #23,0,-32767 1.3.2 Stop Word Removal #24,0,-32767 1.3.3 Stemming #24,0,-32767 1.3.4 Part of Speech Tagging #24,0,-32767 1.3.5 Parsing #25,0,-32767 1.3.6 Applications #25,0,-32767 1.3.6.1 Text Summarization
1.3.6.2 Question Answering
1.3.6.3 Text Categorization
1.3.6.4 Sentiment Analysis
1.3.6.5 Word Sense Disambiguation
1.4 Conclusion #26,0,-32767 References #26,0,-327672: An Approach toward Character Recognition of Bangla Handwritten Isolated Characters #30,0,-32767 2.1 Introduction #30,0,-32767 2.2 Proposed Framework #31,0,-32767 2.2.1 Database #32,0,-32767 2.2.2 Feature Extraction #33,0,-32767 2.2.3 Attribute Selection and Classification #33,0,-32767 2.3 Results and Discussion #35,0,-32767 2.3.1 Comparative Study #36,0,-32767 2.4 Conclusion #41,0,-32767 References #41,0,-327673: Artistic Multi-Character Script Identification #44,0,-32767 3.1 Introduction #44,0,-32767 3.2 Literature Review #45,0,-32767 3.3 Data Collection and Preprocessing #46,0,-32767 3.4 Feature Extraction #49,0,-32767 3.4.1 Topology-Based Features #49,0,-32767 3.4.2 Texture Feature #51,0,-32767 3.5 Experiments #53,0,-32767 3.5.1 Estimation Procedure #53,0,-32767 3.5.2 Results and Analysis #53,0,-32767 3.6 Conclusion #54,0,-32767 References #55,0,-327674: A Study on the Extreme Learning Machine and Its Applications #58,0,-32767 4.1 Introduction #58,0,-32767 4.2 Preliminaries #59,0,-32767 4.3 Activation Functions of ELM #60,0,-32767 4.3.1 Sigmoid Function #61,0,-32767 4.3.2 Hardlimit Function (‘Hardlim’) #61,0,-32767 4.3.3 Radial Basis Function (‘Radbas’) #61,0,-32767 4.3.4 Sine Function #61,0,-32767 4.3.5 Triangular Basis Function (‘Tribas’) #62,0,-32767 4.4 Metamorphosis of an ELM #62,0,-32767 4.5 Applications of ELMs #63,0,-32767 4.5.1 ELMs in Document Analysis #63,0,-32767 4.5.2 ELMs in Medicine #64,0,-32767 4.5.3 ELM in Audio Signal Processing #64,0,-32767 4.5.4 ELM in Other Pattern Recognition Problems #64,0,-32767 4.6 Challenges of ELM #64,0,-32767 4.7 Conclusion #65,0,-32767 References #65,0,-327675: A Graph-Based Text Classification Model for Web Text Documents #68,0,-32767 5.1 Introduction #68,0,-32767 5.2 Related Works #69,0,-32767 5.2.1 English #69,0,-32767 5.2.2 Chinese, Japanese and Persian #70,0,-32767 5.2.3 Arabic and Urdu #71,0,-32767 5.2.4 Indian Languages except Bangla #71,0,-32767 5.2.5 Bangla #72,0,-32767 5.3 Proposed Methodology #73,0,-32767 5.3.1 Data Collection #73,0,-32767 5.3.2 Pre-Processing #74,0,-32767 5.3.3 Graph-Based Representation #75,0,-32767 5.3.4 Classifier #75,0,-32767 5.4 Results and Analysis #76,0,-32767 5.4.1 Comparison with Existing Methods #78,0,-32767 5.5 Conclusion #79,0,-32767 Acknowledgment #79,0,-32767 References #79,0,-327676: A Study of Distance Metrics in Document Classification #84,0,-32767 6.1 Introduction #85,0,-32767 6.2 Literature Survey #85,0,-32767 6.2.1 Indo–European #85,0,-32767 6.2.2 Sino–Tibetan #86,0,-32767 6.2.3 Japonic #87,0,-32767 6.2.4 Afro–Asiatic #87,0,-32767 6.2.5 Dravidian #87,0,-32767 6.2.6 Indo–Aryan #87,0,-32767 6.3 Proposed Methodology #88,0,-32767 6.3.1 Data Collection #89,0,-32767 6.3.2 Pre-Processing #89,0,-32767 6.3.3 Feature Extraction and Selection #90,0,-32767 6.3.4 Distance Measurement #91,0,-32767 6.3.4.1 Squared Euclidean Distance
6.3.4.2 Manhattan Distance
6.3.4.3 Mahalanobis Distance
6.3.4.4 Minkowski Distance
6.3.4.5 Chebyshev Distance
6.3.4.6 Canberra Distance
6.4 Results and Discussion #93,0,-32767 6.4.1 Comparison with Existing Methods #96,0,-32767 6.5 Conclusion #96,0,-32767 Acknowledgment #97,0,-32767 References #97,0,-327677: A Study of Proximity of Domains for Text Categorization #100,0,-32767 7.1 Introduction #100,0,-32767 7.2 Existing Work #101,0,-32767 7.3 Proposed Methodology #104,0,-32767 7.3.1 Data Collection #104,0,-32767 7.3.2 Pre-Processing #105,0,-32767 7.3.3 Feature Extraction and Selection #106,0,-32767 7.3.4 Classifiers #107,0,-32767 7.4 Results and Analysis #109,0,-32767 7.5 Conclusion #112,0,-32767 Acknowledgment #112,0,-32767 References #112,0,-327678: Supervised Learning for Aggression Identification and Author Profiling over Twitter Dataset #116,0,-32767 8.1 Introduction #116,0,-32767 8.2 Overview of Aggression Identification #117,0,-32767 8.2.1 Dataset #117,0,-32767 8.2.2 Data Characteristics #119,0,-32767 8.2.3 Data Preprocessing #120,0,-32767 8.2.4 Feature Extraction #121,0,-32767 8.2.5 Experimental Setup #122,0,-32767 8.2.6 System Modeling #122,0,-32767 8.2.7 Results #124,0,-32767 8.3 Overview of Author Profiling #124,0,-32767 8.3.1 Datasets #125,0,-32767 8.3.2 Preprocessing #125,0,-32767 8.3.3 Feature Extraction #126,0,-32767 8.3.4 Experimental Setup #126,0,-32767 8.3.5 Algorithm and Fine-Tuning the Model #127,0,-32767 8.3.6 Results #128,0,-32767 8.4 Conclusion and Future Work #131,0,-32767 References #131,0,-327679: The Effect of Using Features Computed from Generated Offline Images for Online Bangla Handwritten Character Recognition #136,0,-32767 9.1 Introduction #136,0,-32767 9.2 Literature Review #141,0,-32767 9.2.1 Direction Code-Based Feature [50] #141,0,-32767 9.2.2 Area and Local Features #143,0,-32767 9.2.2.1 Area Feature
9.2.2.2 Local Feature
9.2.3 Point-Based Feature [2, 48] #145,0,-32767 9.2.4 Transition Count Feature [61] #146,0,-32767 9.2.5 Topological Feature [61] #146,0,-32767 9.2.5.1 Crossing Point
9.3 Database Preparation and Pre-processing #148,0,-32767 9.3.1 Design of the Data Collection Form #148,0,-32767 9.4 Feature Extraction #149,0,-32767 9.4.1 Directed Hausdorff Distance (DHD)-Based Features #149,0,-32767 9.5 Experimental Results and Analysis #151,0,-32767 9.6 Conclusion #154,0,-32767 References #154,0,-3276710: Handwritten Character Recognition for Palm-Leaf Manuscripts #160,0,-32767 10.1 Introduction #160,0,-32767 10.2 Palm-Leaf Manuscripts #161,0,-32767 10.3 Challenges in OHCR for Palm-Leaf Manuscripts #161,0,-32767 10.4 Document Processing and Recognition for Palm-Leaf Manuscripts #163,0,-32767 10.4.1 Preprocessing #164,0,-32767 10.4.1.1 Binarization
10.4.1.2 Noise Reduction
10.4.1.3 Skew Correction
10.4.2 Segmentation #165,0,-32767 10.4.2.1 Text Line Segmentation
10.4.2.2 Character Segmentation
10.4.3 Recognition #167,0,-32767 10.4.3.1 Segmentation-Based Approach
10.4.3.2 Segmentation-Free Approach
