… annotate image implied information(implicit), this paper proposes a double-layer multi-label
annotation … Firstly,the image ontology annotation and implicit annotation are regarded as two …

… in multi-label classification has become an important research direction. This paper proposes
an embedding-based multi-label … of class tags, with good scalability and short training time. …

… In this work, a multi-label attribute reduction algorithm based … multi-label classification for
automatic image annotation[J]. … Scalable extension of the ReliefF algorithm for weighting and …

… still some problems in the multi-label classification algorithm based on … In this paper,we
propose a multi-label image classification … 0%,which improves the accuracy of multi-label image …

… The improved weighting formula enables MML-RF to be used to the multi-label dataset.
MML-… on multi-label dataset, which can further enhance the efficiency of subsequent multi-label …

… Heterogeneous multimedia cooperative annotation based on multimodal correlation
learning[J]. Journal of Visual Communication and Image Representation, 2019, 58 (2): 544- 553. …

… Automatic image annotation via local multi-label classification. In: Proc. of the 7th ACM Int’l …
Efficient region-aware large graph construction towards scalable multi-label propagation. …

… Abstract:Complementary decision reduct is an effective attribute reduction approach for
multi-label data. However, the corresponding heuristic algorithm is computationally time…

… This paper reviews the research progress of multi-label feature … Scalable extensions of the
ReliefF algorithm for weighting … of image retrieval based on multi-label image annotation[C]//…

… attracted much attention due to its good scalability in real surveillance scenarios. The existing
… 2022 年,Li 等[13] 提出一种多标签学习引导的自节奏聚类 (multi-label learning guided self-…