Deep Learning Algorithms for Satellite Imagery
暫譯: 衛星影像的深度學習演算法

Basu, Saikat

Deep Learning Algorithms for Satellite Imagery

相關主題

商品描述

This book provides key insights into the world of Deep Learning pertaining to satellite image understanding. It highlights what differentiates satellite image datasets from other natural or synthetic images and how to tackle problems specific to these imagery data. From answering questions like how to select optimal training data to weekly supervised and unsupervised learning and how to tackle loosely labeled data, it is a valuable source of information for anyone interested in understanding the theory behind satellite image analytics and provides key insights on the application of various state-of-the-art Deep Learning algorithms on these datasets.

商品描述(中文翻譯)

本書提供了有關衛星影像理解的深度學習世界的關鍵見解。它突顯了衛星影像數據集與其他自然或合成影像之間的區別，以及如何解決這些影像數據特有的問題。從回答如何選擇最佳訓練數據到每週的監督學習和非監督學習，以及如何處理標籤不明確的數據，本書對於任何有興趣了解衛星影像分析背後理論的人來說，都是一個寶貴的信息來源，並提供了有關各種最先進的深度學習算法在這些數據集上的應用的關鍵見解。

作者簡介

Saikat Basu is working as a research scientist in the Facebook Maps team in Boston. He received his PhD in Computer Science from Louisiana State University in 2016. He received his Bachelor of Technology in Computer Science and Engineering from National Institute of Technology, Durgapur, India in 2011. During his doctoral program, he has been doing research on the analysis of various kinds of imagery data using Computer Vision and Deep Learning algorithms for the analysis of satellite imagery data. During his PhD, he has worked as a research associate at NASA Ames Research Center, Moffett Field, California and an intern at the Facebook Maps team in Boston.

作者簡介(中文翻譯)

Saikat Basu 目前在波士頓的 Facebook 地圖團隊擔任研究科學家。他於 2016 年在路易斯安那州立大學獲得計算機科學博士學位。2011 年，他在印度杜爾卡普爾國立技術學院獲得計算機科學與工程的技術學士學位。在他的博士課程中，他專注於使用計算機視覺和深度學習算法分析各種影像數據，特別是衛星影像數據的分析。在攻讀博士學位期間，他曾在加州的 NASA 艾姆斯研究中心擔任研究助理，並在波士頓的 Facebook 地圖團隊實習。

類似商品

最後瀏覽商品 (20)