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Found 4 papers, 2 papers with code
JCSE: Contrastive Learning of Japanese Sentence Embeddings and Its Applications
To overcome this, we propose a novel Japanese sentence representation framework, JCSE (derived from ``Contrastive learning of Sentence Embeddings for Japanese''), that creates training data by generating sentences and synthesizing them with sentences available in a target domain.
Segmentation of Weakly Visible Environmental Microorganism Images Using Pair-wise Deep Learning Features
The use of PDLFs enables the network to focus more on the foreground (EMs) by concatenating the pairwise deep learning features of each image to different blocks of the base model SegNet.
Generic Itemset Mining Based on Reinforcement Learning
In this framework, an agent for extracting any type of itemsets can be trained as long as a reward suitable for the type can be defined.
A New Pairwise Deep Learning Feature For Environmental Microorganism Image Analysis
In order to fasten, low the cost, increase consistency and accuracy of identification, we propose the novel pairwise deep learning features to analyze microorganisms.
