Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision.
This self-contained guide will benefit those who seek to both understand the theory behind CNNs and to gain hands-on experience on the application of CNNs in computer vision. It provides a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs.The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision. Further, this text describes and discusses case studies that are related to the application of CNN in computer vision, including image classification, object detection, semantic segmentation, scene understanding, and image generation.
This book is ideal for undergraduate and graduate students, as no prior background knowledge in the field is required to follow the material, as well as new researchers, developers, engineers, and practitioners who are interested in gaining a quick understanding of CNN models.
Navigating the Future: Investor Attitudes Toward Equity Derivatives
Financial instruments known as equity derivatives get their value from an underlying equity security, like a stock or index. They can be used for a number of things, including as gaining exposure to a particular equity or basket of equities, speculating on price swings, and hedging against risk.
This piece looks at how investors currently feel about equities derivatives and what factors will likely influence how they are used in the future. It makes the case that while equity derivatives will always be a significant part of investor portfolios, their particular applications will change as investor preferences and market conditions change.
The first section of the article gives a summary of the various kinds of equity derivatives and their salient characteristics. The advantages and disadvantages of employing stock derivatives are then covered, emphasizing how crucial it is to comprehend these risks before making an investment.
The paper then looks at how investors now feel about equity derivatives. To give a thorough picture of investor sentiment, it consults a range of sources, such as market data, interviews, and polls.
The final section of the paper discusses the variables that will probably influence how equity derivatives are used in the future. It makes the case that the emergence of new technology, the expansion of emerging economies, and the growing sophistication of investors will all contribute to the future expansion of the equity derivatives market.
All things considered, the essay offers investors a useful resource for finding out more about stock derivatives and how they can affect future investment portfolios.