Trainable Regularization in Dense Image Matching Problems

Trainable Regularization in Dense Image Matching Problems

This study examines the development of specialized models designed to solve image-matching problems. The purpose of this research is to develop a technique based on energy tensor aggregation for dense image matching. This task is relevant within the framework of computer systems since image comparis...

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Bibliographic Details
Main Authors: Vladimir Zh. Kuklin, Aslan A. Tatarkanov, Alexander A. Umyskov
Format: Article
Language:English
Published: Ital Publication 2023-09-01
Series:HighTech and Innovation Journal
Subjects:
image matching
convolutional recurrent neural network
stereo reconstruction
method error
neural network architecture.
Online Access:https://hightechjournal.org/index.php/HIJ/article/view/437

Internet

https://hightechjournal.org/index.php/HIJ/article/view/437

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