… extend the applications of domain adaptation methods in real-… of open set domain adaptation
setting where the target domain … a multi-classifier based domain adversarial network for an …

… -Filtering Multi-Classifier Adversarial Network (UFMCAN) to enhance open-set domain
adaptation… The primary objective of our method is to leverage multiple classifiers and adversarial …

… open-set setting, this paper creatively proposes a hyperspectral open set domain adaptation
model based on adversarial … three-dimensional convolutional neural network as the feature …

… source domain are consistent with the target domain. However, open-set domain adaptation
… Here we propose an interactive dual adversarial neural network (IDANN) for this problem. …

… PGL [29] exploits a graph neural network … CMU [10] exploits a multi-classifier ensemble
together with an unknown scoring function that combines entropy, confidence, and consistency …

… domain to denote the dataset employed for neural network training, while the term target …
We have employed a multi-classifier approach to categorize samples into known and unknown …

… Domain adaptation settings can be divided into closed set, partial, open set domain adaptation
and universal domain … Ensemble naturally utilizes the current multi-classifier architecture …

… domain adaptation effect has been obtained through both minimization of MMD and domain
adversarial networks… A typical adversarial domain adaptation network generally consists of a …

… For example, adversarial network (AN) is used for adapting to frequency variation [15]
and … open-set SEI method based on multi-classifier fusion is proposed in this paper. Multi-classifier …

… the labeled data from multiple source domains, and the multi-classifier setup (Fig. 1a) …
We learn a deep neural network model having a CNN based feature extractor f : R224×224×…