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The STM architecture is constructed to enforce the learned deep representation to satisfy the intrinsic manifold structure from the data, which results in robust features that suit various application scenarios, such as digit recognition, image classification and object tracking.
Jan 28, 2020
Apr 1, 2018 · We propose a new representation learning method, termed Structure Transfer Machine (STM), which enables feature learning process to converge at ...
These newly designed transfer techniques exploit multitask learning frameworks to incorporate extra knowledge from other networks or additional datasets into ...
In this paper, we propose a new representation learning method, named Structure Transfer Machine (STM), which enables feature learning process to converge at ...
This paper proposes a new representation learning method, named Structure Transfer Machine (STM), which enables feature learning process to converge at the ...
Abstract—Representation learning is a fundamental but chal- lenging problem, especially when the distribution of data is unknown. In this paper, we propose ...
The Structure Transfer Machine Theory and Applications. Baochang Zhang, Wankou Yang, Ze Wang, Lian Zhuo, Jungong Han, Xiantong Zhen. January 2020. PDF Cite DOI.
Jun 22, 2023 · Using the structure-informed features the transfer machine learning approach in this work takes the advantage of accumulated existing data to ...
... transfer printing technique based on an air pressure-controlled stamp similar to the octopus-inspired stamp. (A) Illustration of the structure and transfer ...
The text covers the standard topics of heat transfer with an emphasis on physics and real-world applications. ... the structure or putting on more cloth ...