Handbook of deep learning applications
著者
書誌事項
Handbook of deep learning applications
（Smart innovation, systems and technologies, v.136）
Springer, c2019
大学図書館所蔵 件 / 全7件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Includes bibliographical references
内容説明・目次
内容説明
This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain-computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.
目次
Designing a Neural Network from scratch for Big Data powered by Multi-node GPUs.- Deep Learning for Scene Understanding.- Deep Learning for Driverless Vehicles.- Deep Learning for Document Representation.- Deep learning for marine species recognition.- Deep molecular representation in Cheminformatics.- Deep Learning in eHealth.- Deep Learning for Brain Computer Interfaces.- Deep Learning in Gene Expression Modeling.
「Nielsen BookData」 より