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What is DNN

Recent Advancements in Multimedia Data Processing and Security: Issues, Challenges, and Techniques
Deep Neural Network
Published in Chapter:
A Comparative Analysis of Signature Recognition Methods
Ishrat Nabi (Cluster University of Srinagar, India), Akib Mohi Ud Din Khanday (United Arab Emirates University, UAE), Ishrat Rashid (Cluster University of Srinagar, India), Fayaz Ahmed Khan (Cluster University of Srinagar, India), and Rumaan Bashir (Islamic University of Science and Technology, India)
DOI: 10.4018/978-1-6684-7216-3.ch007
Abstract
Signature recognition is the process of automatically identifying or verifying an individual's signature to determine its authenticity. The basic motivation of developing signature recognition systems is to check whether a signature has been done by an authorized user /genuine user or an unauthorized user/a forger. The objective of this chapter is to study different algorithms that are used to authenticate and authorize the signatures of the individual. For personal identification and verification, Signatures are the most acceptable and economical way that is used for this purpose. Signature verification is used for documents like bank transactions and in offices as well. It is a huge time-consuming task for verifying a large number of documents. Hence the verification systems led to huge dramatic changes based on the physical characteristics and the behavioural characteristics of the individual. The verification methods used in the past suffer from flaws. This chapter provides a comparative analysis of various techniques used for recognizing signatures.
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Holistic View on Detecting DDoS Attacks Using Machine Learning
Deep Neural Networks. Supervised method used for classification and regression problems, built to simulate the activity of the human brain by feeding input data through several layers of simulated neural connections.
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