Text Segmentation and Recognition for Enhanced Image Spam Detection
Springer International Publishing (Verlag)
978-3-030-53046-4 (ISBN)
- Presents solutions to email spam detection and discusses its challenges such as text classification and categorization;
- Analyzes the proposed techniques' performance using precision, F-measure, recall and accuracy;
- Evaluates the limitations of the proposed research thereby recommending future research.
Mallikka Rajalingam received her M.Sc Information Technology from Bharathidasan University, Tiruchirappalli, India in 2005, M.Phil Computer Science from Madurai Kamaraj University, Madurai, India in 2008, M.Tech Computer Science & Engineering from SASTRA University, Thanjavur, India in 2009. She worked as a Research Officer (RO) at School of Computer Science, Universiti Sains Malaysia (USM), Malaysia. She is currently pursuing the Ph.D. degree at the Department of Computer Science & Engineering, Bharathidasan University, Trichy, India. She published 13 International journals, 07 International conferences and 09 workshops during her research. Her research interests include image processing, computer vision, pattern recognition, character recognition, document image analysis, text analysis and multimedia networking.
Chapter 1. Introduction.- Chapter 2. Review of Literature.- Chapter 3. Methodology.- Chapter 4. Character Segmentation.- Chapter 5. Character Recognition.- Chapter 6. Classification/Feature Extraction Using SVM and KNN Classifier.- Chapter 7. Experimentation and Result discussion.- Chapter 8. Conclusion.
Erscheinungsdatum | 17.08.2020 |
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Reihe/Serie | EAI/Springer Innovations in Communication and Computing |
Zusatzinfo | IX, 114 p. 31 illus., 23 illus. in color. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 360 g |
Themenwelt | Technik ► Elektrotechnik / Energietechnik |
Technik ► Nachrichtentechnik | |
Schlagworte | classification • IMAGE SPAM EMAIL • machine learning • Recognition • Segmentation |
ISBN-10 | 3-030-53046-9 / 3030530469 |
ISBN-13 | 978-3-030-53046-4 / 9783030530464 |
Zustand | Neuware |
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