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Simple Semantic-Aided Few-Shot Learning
This limitation severely constrains the potential of semantics in Few-Shot Learning.
Analysis and Applications of Deep Learning with Finite Samples in Full Life-Cycle Intelligence of Nuclear Power Generation
The advent of Industry 4. 0 has precipitated the incorporation of Artificial Intelligence (AI) methods within industrial contexts, aiming to realize intelligent manufacturing, operation as well as maintenance, also known as industrial intelligence.
Attribute Localization and Revision Network for Zero-Shot Learning
Second, we propose Attribute Revision Module (ARM), which generates image-level semantics by revising the ground-truth value of each attribute, compensating for performance degradation caused by ignoring intra-class variation.
RMBR: A Regularized Minimum Bayes Risk Reranking Framework for Machine Translation
Recently, Minimum Bayes Risk (MBR) decoding has been proposed to improve the quality for NMT, which seeks for a consensus translation that is closest on average to other candidates from the n-best list.
A Data-Driven Column Generation Algorithm For Bin Packing Problem in Manufacturing Industry
The bin packing problem exists widely in real logistic scenarios (e. g., packing pipeline, express delivery), with its goal to improve the packing efficiency and reduce the transportation cost.
