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Více informací o knize Visual Object Tracking from Correlation Filter to Deep Learning

• Parametry knihy
• Anotace
• Oblíbené z jiného soudku

Nákupem získáte 330 bodů

Anotace knihy

The book focuses on visual object tracking systems and approaches based on correlation filter and deep learning. Both foundations and implementations have been addressed. The algorithm, system design and performance evaluation have been explored for three kinds of tracking methods including correlation filter based methods, correlation filter with deep feature based methods, and deep learning based methods. Firstly, context aware and multi-scale strategy are presented in correlation filter based trackers; then, long-short term correlation filter, context aware correlation filter and auxiliary relocation in SiamFC framework are proposed for combining correlation filter and deep learning in visual object tracking; finally, improvements in deep learning based trackers including Siamese network, GAN and reinforcement learning are designed. The goal of this book is to bring, in a timely fashion, the latest advances and developments in visual object tracking, especially correlation filter and deep learning based methods, which is particularly suited for readers who are interested in the research and technology innovation in visual object tracking and related fields.

Parametry knihy

Zařazení knihy Knihy v angličtině Computing & information technology Computer science Artificial intelligence

• Plný název: Visual Object Tracking from Correlation Filter to Deep Learning
• Autor: Weiwei Xing, Weibin Liu, Jun Wang, Shunli Zhang, Lihui Wang, Yuxiang Yang, Bowen Song
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 193
• EAN: 9789811662447
• ID: 41927492
• Nakladatelství: Springer, Berlin
• Hmotnost: 326 g
• Rozměry: 235 × 155 × 12 mm
• Rok vydání: 2022

Oblíbené z jiného soudku

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