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What is Rectified Linear Activation Function (RELU)

Enhancing Performance, Efficiency, and Security Through Complex Systems Control
Is the most commonly used activation function in many deep learning networks. It is easy to train and often leads to better performance. If it is positive, it returns the input directly; otherwise it turns back to the zero value.
Published in Chapter:
Intelligent Watermarking for Data Security: An Overview
Imen Fourati Kallel (Ecole Nationale d'Electronique et des Télécommunications de Sfax (ENET'Com), Tunisia) and Mohamed Kallel (Ecole Nationale d'Electronique et des Télécommunications de Sfax (ENET'Com), Tunisia)
DOI: 10.4018/979-8-3693-0497-6.ch015
Abstract
Artificial intelligence has become widely and increasingly used in various advanced applications, notably classification, optimization, object recognition, and segmentation. Recently, it has been extended into watermarking techniques. It brings some approaches implying innovative security means, which are adjusted to new communications and information technologies. As it generally believed that the use of artificial intelligence in digital watermarking schemes could revolutionize the way digital data is protected. This chapter is about an overview of recent developments in artificial intelligence techniques utilized for watermarking. It begins with the watermarking background. Next, it represents a review of machine and deep learning watermarking techniques followed by a delineation of their advantages and disadvantages. In this light, the main problems are pinpointed with a suggestion of some possible discussed and highlighted solutions. The last point of this chapter is about outlining future research directions.
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