태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.
Different from the setting of domain adaptation which uses all labeled source and unlabeled target domain examples for training, domain examples should be divided into two disjoint parts: training and test. UDE-DomainNet is built from DomainNet, so the performance of domain-adapted or domain-expanded models on the source and target domain can be evaluated.
Different from the setting of domain adaptation which uses all labeled source and unlabeled target domain examples for training, domain examples should be divided into two disjoint parts: training and test. UDE-Office-Home is built from Office-Home, so the performance of domain-adapted or domain-expanded models on the source and target domain can be evaluated.
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.