Year: 2017
Type: conference-paper
Abstract: In this paper we propose a joint optimization technique for coupled autoencoder which learns the autoencoder weights and coupling map (between source and target) simultaneously. The technique is applicable to any transfer learning problem. In this work, we propose a new formulation that recasts deblurring as a transfer learning problem; it is solved using the proposed coupled autoencoder. The proposed technique can operate on-the-fly; since it does not require solving any costly inverse problem. Experiments have been carried out on state-of-the-art techniques; our method yields better quality images in shorter operating times.
Authors: Kavya Gupta, Brojeshwar Bhowmick, Angshul Majumdar
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2952365877