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Found 12 papers, 6 papers with code
DocStormer: Revitalizing Multi-Degraded Colored Document Images to Pristine PDF
Thus, we propose DocStormer, a novel algorithm designed to restore multi-degraded colored documents to their potential pristine PDF.
Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning
In practice, a set of formulaic alphas is often used together for better modeling precision, so we need to find synergistic formulaic alpha sets that work well together.
Style Miner: Find Significant and Stable Explanatory Factors in Time Series with Constrained Reinforcement Learning
In high-dimensional time-series analysis, it is essential to have a set of key factors (namely, the style factors) that explain the change of the observed variable.
Stable Attribute Group Editing for Reliable Few-shot Image Generation
SAGE takes use of all given few-shot images and estimates a class center embedding based on the category-relevant attribute dictionary.
Unsupervised Coherent Video Cartoonization with Perceptual Motion Consistency
Furthermore, we devise the spatio-temporal correlative map as a style-independent, global-aware regularization on the perceptual motion consistency.
Intrinsic Bias Identification on Medical Image Datasets
However, scientists and practitioners are difficult to identify implicit biases in the datasets, which causes lack of reliable unbias test datasets to valid models.
Attribute Group Editing for Reliable Few-shot Image Generation
Few-shot image generation is a challenging task even using the state-of-the-art Generative Adversarial Networks (GANs).
Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence
Artificial intelligence (AI) provides a promising substitution for streamlining COVID-19 diagnoses.
DuCN: Dual-children Network for Medical Diagnosis and Similar Case Recommendation towards COVID-19
Our proposed network contains two stages: the first one is a lung region segmentation step and is used to exclude irrelevant factors, and the second is a detection and recommendation stage.
Trust the Model When It Is Confident: Masked Model-based Actor-Critic
In complex and noisy settings, model-based RL tends to have trouble using the model if it does not know when to trust the model.
Learning Directional Feature Maps for Cardiac MRI Segmentation
Cardiac MRI segmentation plays a crucial role in clinical diagnosis for evaluating personalized cardiac performance parameters.
Face Detection Using Improved Faster RCNN
Faster RCNN has achieved great success for generic object detection including PASCAL object detection and MS COCO object detection.
Ranked #9 on
Face Detection
on WIDER Face (Hard)
