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Found 5 papers, 1 papers with code
Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathology
Unlike existing works that focus on pre-training powerful feature extractor or designing sophisticated instance aggregator, R$^2$T is tailored to re-embed instance features online.
Incorporating Domain Knowledge through Task Augmentation for Front-End JavaScript Code Generation
However, in some domain-specific scenarios, building such a large paired corpus for code generation is difficult because there is no directly available pairing data, and a lot of effort is required to manually write the code descriptions to construct a high-quality training dataset.
A Contact-Safe Reinforcement Learning Framework for Contact-Rich Robot Manipulation
In this paper, we propose a contact-safe reinforcement learning framework for contact-rich robot manipulation, which maintains safety in both the task space and joint space.
Super-Resolving Commercial Satellite Imagery Using Realistic Training Data
We propose a realistic training data generation model for commercial satellite imagery products, which includes not only the imaging process on satellites but also the post-process on the ground.
Automatic Parameter Selection for Denoising Algorithms Using a No-Reference Measure of Image Content
Across the field of inverse problems in image and video processing, nearly all algorithms have various parameters which need to be set in order to yield good results.
