This book describes the design of a complete, flexible system for perceptual organization in computer vision using graph theoretic techniques, voting methods, and an extension of the Bayesian networks called perceptual inference networks (PINs).
This volume LNCS 15277 constitutes the refereed proceedings of the 18th Ibero-American Conference on AI, IBERAMIA 2024, held in Montevideo, Uruguay, during November 13-15, 2024.
This two-volume set, CCIS 2374 and CCIS 2375, constitutes the revised selected papers from the 37th International Conference on Computer Animation and Social Agents, CASA 2024, held in Wuhan, China, during June 5-7, 2024.
Master GenAI techniques to create images and text using variational autoencoders (VAEs), generative adversarial networks (GANs), LSTMs, and large language models (LLMs)Key FeaturesImplement real-world applications of LLMs and generative AIFine-tune models with PEFT and LoRA to speed up trainingExpand your LLM toolbox with Retrieval Augmented Generation (RAG) techniques, LangChain, and LlamaIndexPurchase of the print or Kindle book includes a free eBook in PDF formatBook DescriptionBecome an expert in Generative AI through immersive, hands-on projects that leverage today's most powerful models for Natural Language Processing (NLP) and computer vision.
This two-volume set, CCIS 2374 and CCIS 2375, constitutes the revised selected papers from the 37th International Conference on Computer Animation and Social Agents, CASA 2024, held in Wuhan, China, during June 5-7, 2024.
This volume LNCS 15277 constitutes the refereed proceedings of the 18th Ibero-American Conference on AI, IBERAMIA 2024, held in Montevideo, Uruguay, during November 13-15, 2024.
This two-volume set, CCIS 2374 and CCIS 2375, constitutes the revised selected papers from the 37th International Conference on Computer Animation and Social Agents, CASA 2024, held in Wuhan, China, during June 5-7, 2024.
Master reproducible ML and DL models with Python and PyTorch to achieve high performance, explainability, and real-world successKey FeaturesLearn how to improve performance of your models and eliminate model biasesStrategically design your machine learning systems to minimize chances of failure in productionDiscover advanced techniques to solve real-world challengesPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionDebugging Machine Learning Models with Python is a comprehensive guide that navigates you through the entire spectrum of mastering machine learning, from foundational concepts to advanced techniques.
The six-volume set, LNCS 15251-15256, constitutes the refereed proceedings of the 24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024, held in Macau, China, during October 29-31, 2024.
The six-volume set, LNCS 15251-15256, constitutes the refereed proceedings of the 24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024, held in Macau, China, during October 29-31, 2024.
The six-volume set, LNCS 15251-15256, constitutes the refereed proceedings of the 24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024, held in Macau, China, during October 29-31, 2024.
The six-volume set, LNCS 15251-15256, constitutes the refereed proceedings of the 24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024, held in Macau, China, during October 29-31, 2024.
The six-volume set, LNCS 15251-15256, constitutes the refereed proceedings of the 24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024, held in Macau, China, during October 29-31, 2024.