| 書目名稱 | Deep Learning Models |
| 副標(biāo)題 | A Practical Approach |
| 編輯 | Jonah Gamba |
| 視頻video | http://file.papertrans.cn/265/264576/264576.mp4 |
| 概述 | Offers a special chapter devoted to performance evaluation of deep learning algorithms.Demonstrates illustrative colorful block diagrams, figures, and full code examples to clearly present ideas invol |
| 叢書名稱 | Transactions on Computer Systems and Networks |
| 圖書封面 |  |
| 描述 | .This book focuses on and prioritizes a practical approach, minimizing theoretical concepts to deliver algorithms effectively. With deep learning emerging as a vibrant field of research and development in numerous industrial applications, there is a pressing need for accessible resources that provide comprehensive examples and quick guidance. Unfortunately, many existing books on the market tend to emphasize theoretical aspects, leaving newcomers scrambling for practical guidance. This book takes a different approach by focusing on practicality while keeping theoretical concepts to a necessary minimum. The book begins by laying a foundation of basic information on deep learning, gradually delving into the subject matter to explain and illustrate the limitations of existing algorithms. A dedicated chapter is allocated to evaluating the performance of multiple algorithms on specific datasets, highlighting techniques and strategies that can address real-world challenges when deep learning is employed. By consolidating all necessary information into a single resource, readers can bypass the hassle of scouring scattered online sources, gaining a one-stop solution to dive into deep learn |
| 出版日期 | Book 2024 |
| 關(guān)鍵詞 | Deep learning; Computer vision; Object detection; Object classification; Python programming; Remote sensi |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-981-99-9672-8 |
| isbn_softcover | 978-981-99-9674-2 |
| isbn_ebook | 978-981-99-9672-8Series ISSN 2730-7484 Series E-ISSN 2730-7492 |
| issn_series | 2730-7484 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
|Archiver|手機版|小黑屋|
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