Semi-Supervised Domain Adaptation for Holistic Counting under Label Gap

Semi-Supervised Domain Adaptation for Holistic Counting under Label Gap

This paper proposes a novel approach for semi-supervised domain adaptation for holistic regression tasks, where a DNN predicts a continuous value <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>y...

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Bibliographic Details
Main Authors: Mattia Litrico, Sebastiano Battiato, Sotirios A. Tsaftaris, Mario Valerio Giuffrida
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Journal of Imaging
Subjects:
domain adaptation
holistic counting
regression
label gap
Online Access:https://www.mdpi.com/2313-433X/7/10/198

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