Dec 1, 2016 · Our study provides an evaluation and analysis of several state-of-the-art domain adaptation techniques in the field of pattern recognition for ...
Unsupervised domain adaptation techniques based on auto-encoder for non-stationary EEG-based emotion recognition. Comput Biol Med. 2016 Dec 1:79:205-214.
Unsupervised domain adaptation techniques based on auto-encoder for non-stationary EEG-based emotion recognition · 122 Citations · 34 References.
It can be concluded that SAAE is a useful and effective tool for decreasing domain discrepancy and reducing performance degradation across subjects and sessions ...
In electroencephalography (EEG)-based emotion recognition systems, the distribution between the training samples and the testing samples may be mismatched ...
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What is unsupervised domain adaptation method?
It is proposed to apply domain adaptation to reduce the intersubject variance as well as technical discrepancies between datasets, and then train a ...
In this paper, we focus on a comparative study on several state-of-the-art domain adaptation techniques on two datasets: DEAP and SEED. We demonstrate that ...
Aug 19, 2024 · Unsupervised domain adaptation techniques based on auto-encoder for non-stationary eeg- based emotion recognition. Computers in biology and ...
Unsupervised domain adaptation techniques based on auto-encoder for non-stationary EEG-based emotion recognition. Comput. Biol. Med. 2016;79:205–214. doi ...
In this paper, we focus on a comparative study on several state-of-the-art domain adaptation techniques on two datasets: DEAP and SEED. We demonstrate that ...