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Generative adversarial text to image synthesis
Synthesizing high-quality images from text descriptions is a challenging problem in computer vision and has many practical applications. Samples generated by existing text-to-image approaches can roughly reflect the meaning of the given descriptions, but they fail to contain necessary details and vivid object parts. In order to make the project more specialized, it was approved that the project be dedicated to fashion image generation, we present an effective approach for generating new clothing through generative adversarial learning. Generative Adversarial Networks (GANs) successfully show the capability of synthesizing sharper images compared to other generative models.
Electronic engineering for neuromedicine
Advances in electronics have revolutionized diagnostic tools and created mobile medicine, touch-sensitive prosthetics, remote surgery, and artificial organs such as hearts, retinas, and bionic skins. This reference text shows the number of ways in which electronic engineering feeds into neuromedicine namely: the modelling and simulation of the brain, providing access to the brain, analysis of the signals and activities of the brain and influencing the function of the brain for therapeutic purposes. The areas of electronic engineering considered are electronic circuits, spectral analysis, filtering of signals, electromagnetic fields and wave propagation. The book is a valuable source to medical students and practitioners as well as electronic engineering and physics students and graduates.
Bio-inspired computational intelligence and applications ; International conference on life system modeling, and simulation, LSMS 2007, Shanghai, China, September 14-17, 2007. Proceedings
It covers both micro and macro c- ponents ranging from cells, tissues and organs across to organisms and ecologic niches. These interact and evolve to produce an overall complex system whose beh- ior is difficult to comprehend and predict.The arrival of the 21st century has been marked by a resurgence of research interest both in arriving at a systems-level und- standing of biology and in applying such knowledge in complex real-world appli- tions. Consequently, computational methods and intelligence in systems, biology, as well as bio-inspired computational intelligence, have emerged as key drivers for new computational methods. For this reason papers dealing with theory, techniques and real-world applications relating to these two themes were especially solicited.
Beginning deep learning with TensorFlow : Work with Keras, MNIST data sets, and advanced neural networks
Stats with an introduction to AI, where you’ll learn the history of neural networks and what sets deep learning apart from other varieties of machine learning. Discovery the variety of deep learning frameworks and set-up a deep learning development environment. Next, you’ll jump into simple classification programs for hand-writing analysis. Once you’ve tackled the basics of deep learning, you move on to TensorFlow 2 specifically. Find out what exactly a Tensor is and how to work with MNIST datasets. Finally, you’ll get into the heavy lifting of programming neural networks and working with a wide variety of neural network types such as GANs and RNNs. Deep Learning is a new area of Machine Learning research widely used in popular applications, such as voice assistant and self-driving cars. Work through the hands-on material in this book and become a TensorFlow programmer! You will: Develop using deep learning algorithms Build deep learning models using TensorFlow 2 Create classification systems and other, practical deep learning applications
Artificial immune systems ; Vol. 3627 ; 4th International conference, ICARIS 2005, Banff, Alberta, Canada, August 14-17, 2005, Proceedings
Your immune system is unique. It is in many ways as complex as your brain, butit is not centred in one location, like the brain. It is not a single organ—it consistsof many different cell types, diverse methods of intercellular communication, andmany different organs. Its functionality is blurred throughout you—we can’textract the immune system, or point to where it begins and ends. The immunesystem is not separable from the system it protects. It has integral links to everyorgan of our bodies.This has radical implications for the field of Artificial Immune Systems (AIS),that we are only now beginning to comprehend. One of the first insights is thatmodelling the immune system, or developing any kind of immune algorithm, isdifficult. The immune system is one aspect of biology that we find difficult toapply simple reductionist explanations to. We can very successfully extract sub-processes of the whole and create immune algorithms based on those processes.
AI home decorator
Presents the development of “DesignMate”, an innovative AI home decorator application designed to revolutionize interior design. With three main features powered by artificial intelligence, DesignMate simplifies and enhances the process of home decoration. The first feature leverages an Autoregressive transformer model trained on the extensive 3Dfront dataset to suggest room decor based on room layouts. The second feature employs Generative Adversarial Networks (GANs) to enhance the colors of specific room layouts. The third feature introduces an expert system that tailors decor options to user-entered conditions. DesignMate also introduces an integrated e-commerce platform dedicated to furniture, offering users a wide selection of high-quality items that perfectly complement their preferred room designs.
