Advances in cryptology - CRYPTO -86 ; Conference on the theory and applications of cryptographic techniques : Proceedings
This book is the proceedings of CRYPTO 86, one in a series of annual conferences devoted to cryptologic research. They have all been held at the University of California at Santa Barbara. The first conference in this series, CRYPTO 81, organized by A. Gersho, did not have a formal proceedings. The proceedings of the following four conferences in this series have been published as: Advances in Cryptology: Proceedings of Crypto 82, D. Chaum, R. L. Rivest, and A. T. Sherman, eds., Plenum, 1983. Advances in Cryptology: Proceedings of Crypto 83, D. Chaum, ed., Plenum, 1984. Advances in Cryptology: Proceedings of CRYPTO 84, G. R. Blakley and D. Chaum, eds., Lecture Notes in Computer Science #196, Springer, 1985. Advances in Cryptology - CRYPTO '85 Proceedings, H. C. Williams, ed., Lecture Notes in Computer Science #218, Springer, 1986. A parallel series of conferences is held annually in Europe. The first of these had its proceedings published as Cryptography: Proceedings, Burg Feuerstein 1982, T. Beth, ed., Lecture Notes in Computer Science #149, Springer, 1983.
كتب مشابهة
AI in drug discovery
Constitutes the refereed proceedings of the First international workshop on ai in Drug Discovery, AIDD 2024, held as a part of the 33rd International Conference on Artificial Neural Networks, ICANN 2024, in Lugano, Switzerland, on September 19, 2024. These papers focus on various aspects of the rapidly evolving field of Artificial Intelligence (AI)-driven drug discovery in chemistry, including Big Data and advanced Machine Learning, eXplainable AI (XAI), Chemoinformatics, Use of deep learning to predict molecular properties, Modeling and prediction of chemical reaction data and Generative models.
AI in banking : Practical applications and case studies
Delves into the application of AI from theory to practice, offering detailed insights into AI project design and code implementation across eleven business scenarios in four major sectors: retail banking, e-banking, bank credit, and tech operations. it provides hands-on examples of various technologies, including automatic machine learning, integrated learning, graph computation, recommendation systems, causal inference, generative adversarial networks, supervised learning, unsupervised learning, computer vision, reinforcement learning, fuzzy control, automatic control, speech recognition, semantic understanding, bayesian networks, edge computing, and more. this book stands as a rare and practical guide to AI projects in the banking industry.
Machine learning for cyber-physical systems: selected papers from the international conference ML4CPS 2023
Contains selected papers from the international conference ML4CPS – Machine Learning for Cyber-Physical Systems, which was held in Hamburg (Germany), from 29 to 31 March 2023. Cyber-physical systems are adaptive and learning: they analyze their environment and, based on observations, learn patterns, associations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnostics. Machine learning is the key technology for these developments.
Layce (Image data poisoning) = لايس (تسميم بيانات الصور )
The ongoing growth of image generative artificial intelligence models was paved with existing drawings and art pieces by great artists both past and present, and while generative models are very useful and helpful, there is the issue of the origin of the datasets trained on, and the morality of usage regarding copyrights and artistic identity. A novel line of defense that helps artists and visual content creators actively protect their pieces emerged, dubbed Data Poisoning and it works by misleading Artificial Intelligence models that attempt to use a Poisoned Image for training, or as a reference, as the Poisoned Image will appear to the human eye identical to the original art piece, while the Artificial Intelligence model will be seeing a remarkably different image, causing generative models to generate false positive results when given a prompt poisoned by the author or when trained on data poisoned by the original owner. This study aims to study image data poisoning methods and technologies, and build an application containing multiple image models, and poisoning models as well, accompanied by a Community for artists to share art and interact with each other.
