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Found 6 papers, 2 papers with code
Knowledge Distillation via Route Constrained Optimization
However, we find that the representation of a converged heavy model is still a strong constraint for training a small student model, which leads to a high lower bound of congruence loss.
Correlation Congruence for Knowledge Distillation
Most teacher-student frameworks based on knowledge distillation (KD) depend on a strong congruent constraint on instance level.
Dynamic Multi-path Neural Network
Although deeper and larger neural networks have achieved better performance, the complex network structure and increasing computational cost cannot meet the demands of many resource-constrained applications.
SCAN: Sliding Convolutional Attention Network for Scene Text Recognition
Scene text recognition has drawn great attentions in the community of computer vision and artificial intelligence due to its challenges and wide applications.
Nonparametric Independence Screening via Favored Smoothing Bandwidth
As a first step, we propose a fast screening method based on the favored smoothing bandwidth of the marginal local constant regression.
Scene Text Recognition with Sliding Convolutional Character Models
In this paper, we investigate the intrinsic characteristics of text recognition, and inspired by human cognition mechanisms in reading texts, we propose a scene text recognition method with character models on convolutional feature map.
