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Found 8 papers, 1 papers with code
Deep Reinforcement Learning with a Stage Incentive Mechanism of Dense Reward for Robotic Trajectory Planning
Extensive experiments show that the soft stage incentive reward function is able to improve the convergence rate by up to 46. 9% with the state-of-the-art DRL methods.
Single upper limb pose estimation method based on improved stacked hourglass network
Using the stacked hourglass network model, a single-person upper limb skeleton key point detection model was designed. Deconvolution was employed to replace the up-sampling operation of the hourglass module in the original model, solving the problem of rough feature maps.
Computer-aided diagnosis in histopathological images of the endometrium using a convolutional neural network and attention mechanisms
In the ten-fold cross-validation process, the CADx approach, HIENet, achieved a 76. 91 $\pm$ 1. 17% (mean $\pm$ s. d.) classification accuracy for four classes of endometrial tissue, namely normal endometrium, endometrial polyp, endometrial hyperplasia, and endometrial adenocarcinoma.
Parallel Statistical and Machine Learning Methods for Estimation of Physical Load
Several statistical and machine learning methods are proposed to estimate the type and intensity of physical load and accumulated fatigue .
Attention to Refine through Multi-Scales for Semantic Segmentation
This paper proposes a novel attention model for semantic segmentation, which aggregates multi-scale and context features to refine prediction.
Parallel Convolutional Networks for Image Recognition via a Discriminator
The discriminator is core which drives parallel networks to focus on different regions and learn different representations.
D-PCN: Parallel Convolutional Networks for Image Recognition via a Discriminator
The discriminator is core which drives parallel networks to focus on different regions and learn complementary representations.
