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Found 7 papers, 0 papers with code
MolMiner: You only look once for chemical structure recognition
Due to a backlog of decades and an increasing amount of these printed literature, there is a high demand for the translation of printed depictions into machine-readable formats, which is known as Optical Chemical Structure Recognition (OCSR).
A New Weakly Supervised Learning Approach for Real-time Iron Ore Feed Load Estimation
Iron ore feed load control is one of the most critical settings in a mineral grinding process, directly impacting the quality of final products.
Multiple Sequential Learning Tasks Represented in Recurrent Neural Networks
From the computational perspective, we hypothesize that the working mechanism of a multitask model can provide a possible solution to that of brains.
Selective Pseudo-Labeling with Reinforcement Learning for Semi-Supervised Domain Adaptation
Inspired by the effectiveness of pseudo-labels in domain adaptation, we propose a reinforcement learning based selective pseudo-labeling method for semi-supervised domain adaptation.
Ensemble Model with Batch Spectral Regularization and Data Blending for Cross-Domain Few-Shot Learning with Unlabeled Data
In this paper, we present our proposed ensemble model with batch spectral regularization and data blending mechanisms for the Track 2 problem of the cross-domain few-shot learning (CD-FSL) challenge.
Feature Transformation Ensemble Model with Batch Spectral Regularization for Cross-Domain Few-Shot Classification
In this paper, we propose a feature transformation ensemble model with batch spectral regularization for the Cross-domain few-shot learning (CD-FSL) challenge.
Fair Loss: Margin-Aware Reinforcement Learning for Deep Face Recognition
Specifically, we train an agent to learn a margin adaptive strategy for each class, and make the additive margins for different classes more reasonable.
