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MCFL: multi-label contrastive focal loss for deep imbalanced pedestrian attribute recognition

Research article (Neural Computing and Applications, 2022) · cited 13× · AI/ML
academia openalex:W4281965046
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MCFL: multi-label contrastive focal loss for deep imbalanced pedestrian attribute recognition

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MCFL: multi-label contrastive focal loss for deep imbalanced pedestrian attribute recognition is a scholarly article[1].

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  • MCFL: multi-label contrastive focal loss for deep imbalanced pedestrian attribute recognition's instance of is recorded as scholarly article[2].

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Direct Wikidata claims

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). MCFL: multi-label contrastive focal loss for deep imbalanced pedestrian attribute recognition. Retrieved May 24, 2026, from https://4ort.xyz/entity/mcfl-multi-label-contrastive-focal-loss-for-deep-imbalanced-pedestrian-attribute-recognition
MLA “MCFL: multi-label contrastive focal loss for deep imbalanced pedestrian attribute recognition.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/mcfl-multi-label-contrastive-focal-loss-for-deep-imbalanced-pedestrian-attribute-recognition.
BibTeX @misc{4ortxyz_mcfl-multi-label-contrastive-focal-loss-for-deep-imbalanced-pedestrian-attribute-recognition_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{MCFL: multi-label contrastive focal loss for deep imbalanced pedestrian attribute recognition}}, year = {2026}, url = {https://4ort.xyz/entity/mcfl-multi-label-contrastive-focal-loss-for-deep-imbalanced-pedestrian-attribute-recognition}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): MCFL: multi-label contrastive focal loss for deep imbalanced pedestrian attribute recognition — https://4ort.xyz/entity/mcfl-multi-label-contrastive-focal-loss-for-deep-imbalanced-pedestrian-attribute-recognition (retrieved 2026-05-24)

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