Text Segmentation and Recognition for Enhanced Image Spam Detection - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Text Segmentation and Recognition for Enhanced Image Spam Detection write by Mallikka Rajalingam. This book was released on 2020-08-10. Text Segmentation and Recognition for Enhanced Image Spam Detection available in PDF, EPUB and Kindle. This book discusses email spam detection and its challenges such as text classification and categorization. The book proposes an efficient spam detection technique that is a combination of Character Segmentation and Recognition and Classification (CSRC). The author describes how this can detect whether an email (text and image based) is a spam mail or not. The book presents four solutions: first, to extract the text character from the image by segmentation process which includes a combination of Discrete Wavelet Transform (DWT) and skew detection. Second, text characters are via text recognition and visual feature extraction approach which relies on contour analysis with improved Local Binary Pattern (LBP). Third, extracted text features are classified using improvised K-Nearest Neighbor search (KNN) and Support Vector Machine (SVM). Fourth, the performance of the proposed method is validated by the measure of metric named as sensitivity, specificity, precision, recall, F-measure, accuracy, error rate and correct rate. 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.
Computational Intelligence in Pattern Recognition
Computational Intelligence in Pattern Recognition - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Computational Intelligence in Pattern Recognition write by Asit Kumar Das. This book was released on 2022-06-20. Computational Intelligence in Pattern Recognition available in PDF, EPUB and Kindle. This book features high-quality research papers presented at the 4th International Conference on Computational Intelligence in Pattern Recognition (CIPR 2022), held at Indian Institute of Engineering Science and Technology, Shibpur, Howrah, West Bengal, India, during 23 – 24 April 2022. It includes practical development experiences in various areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.
Advanced Machine Learning
Advanced Machine Learning - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Advanced Machine Learning write by Dr. Amit Kumar Tyagi. This book was released on 2024-06-29. Advanced Machine Learning available in PDF, EPUB and Kindle. DESCRIPTION Our book is divided into several useful concepts and techniques of machine learning. This book serves as a valuable resource for individuals seeking to deepen their understanding of advanced topics in this field. Learn about various learning algorithms, including supervised, unsupervised, and reinforcement learning, and their mathematical foundations. Discover the significance of feature engineering and selection for enhancing model performance. Understand model evaluation metrics like accuracy, precision, recall, and F1-score, along with techniques like cross-validation and grid search for model selection. Explore ensemble learning methods along with deep learning, unsupervised learning, time series analysis, and reinforcement learning techniques. Lastly, uncover real-world applications of the machine and deep learning algorithms. After reading this book, readers will gain a comprehensive understanding of machine learning fundamentals and advanced techniques. With this knowledge, readers will be equipped to tackle real-world problems, make informed decisions, and develop innovative solutions using machine and deep learning algorithms. KEY FEATURES ● Basic understanding of machine learning algorithms via MATLAB, R, and Python. ● Inclusion of examples related to real-world problems, case studies, and questions related to futuristic technologies. ● Adding futuristic technologies related to machine learning and deep learning. WHAT YOU WILL LEARN ● Ability to tackle complex machine learning problems. ● Understanding of foundations, algorithms, ethical issues, and how to implement each learning algorithm for their own use/ with their data. ● Efficient data analysis for real-time data will be understood by researchers/ students. ● Using data analysis in near future topics and cutting-edge technologies. WHO THIS BOOK IS FOR This book is ideal for students, professors, and researchers. It equips industry experts and academics with the technical know-how and practical implementations of machine learning algorithms. TABLE OF CONTENTS 1. Introduction to Machine Learning 2. Statistical Analysis 3. Linear Regression 4. Logistic Regression 5. Decision Trees 6. Random Forest 7. Rule-Based Classifiers 8. Naïve Bayesian Classifier 9. K-Nearest Neighbors Classifiers 10. Support Vector Machine 11. K-Means Clustering 12. Dimensionality Reduction 13. Association Rules Mining and FP Growth 14. Reinforcement Learning 15. Applications of ML Algorithms 16. Applications of Deep Learning 17. Advance Topics and Future Directions
Malware Analysis Using Artificial Intelligence and Deep Learning
Malware Analysis Using Artificial Intelligence and Deep Learning - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Malware Analysis Using Artificial Intelligence and Deep Learning write by Mark Stamp. This book was released on 2020-12-20. Malware Analysis Using Artificial Intelligence and Deep Learning available in PDF, EPUB and Kindle. This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of challenging malware-related problems. DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed. This book fills a gap between the emerging fields of DL/AI and malware analysis. It covers a broad range of modern and practical DL and AI techniques, including frameworks and development tools enabling the audience to innovate with cutting-edge research advancements in a multitude of malware (and closely related) use cases.
Email Spam Filtering
Email Spam Filtering - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Email Spam Filtering write by Gordon V. Cormack. This book was released on 2008. Email Spam Filtering available in PDF, EPUB and Kindle. Email Spam Filtering: A Systematic Review surveys current and proposed spam filtering techniques with particular emphasis on how well they work. The primary focus is on spam filtering in email, while similarities and differences with spam filtering in other communication and storage media - such as instant messaging and the Web - are addressed peripherally. Email Spam Filtering: A Systematic Review examines the definition of spam, the user's information requirements and the role of the spam filter as one component of a large and complex information universe. Well known methods are detailed sufficiently to make the exposition self-contained; however, the focus is on considerations unique to spam. Comparisons, wherever possible, use common evaluation measures and control for differences in experimental setup. Such comparisons are not easy, as benchmarks, measures and methods for evaluating spam filters are still evolving. The author surveys these efforts, their results and their limitations. In spite of recent advances in evaluation methodology, many uncertainties (including widely held but unsubstantiated beliefs) remain as to the effectiveness of spam filtering techniques and as to the validity of spam filter evaluation methods. Email Spam Filtering: A Systematic Review outlines several uncertainties and proposes experimental methods to address them. Email Spam Filtering: A Systematic Review is a highly recommended read for anyone conducting research in the area or charged with controlling spam in a corporate environment.
