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Found 12 papers, 1 papers with code
SRGS: Super-Resolution 3D Gaussian Splatting
This approach relies on the representation power of Gaussian primitives to provide a high-quality rendering.
Simulating Nighttime Visible Satellite Imagery of Tropical Cyclones Using Conditional Generative Adversarial Networks
Visible (VIS) imagery of satellites has various important applications in meteorology, including monitoring Tropical Cyclones (TCs).
ZS-SRT: An Efficient Zero-Shot Super-Resolution Training Method for Neural Radiance Fields
This framework aims to guide the NeRF model to synthesize high-resolution novel views via single-scene internal learning rather than requiring any external high-resolution training data.
FLAIR: A Conditional Diffusion Framework with Applications to Face Video Restoration
Face video restoration (FVR) is a challenging but important problem where one seeks to recover a perceptually realistic face videos from a low-quality input.
Augmenting Black-box LLMs with Medical Textbooks for Clinical Question Answering
In this study, we present a system called LLMs Augmented with Medical Textbooks (LLM-AMT) designed to enhance the proficiency of LLMs in specialized domains.
YZR-net : Self-supervised Hidden representations Invariant to Transformations for profanity detection
Some miscreants use this framework to send profane messages which can have a negative impact on other students as well as the teacher of the class.
Looking For A Match: Self-supervised Clustering For Automatic Doubt Matching In e-learning Platforms
Results highlighted that, custom BYOL improves the top-1 matching accuracy by approximately 6\% and 5\% as compared to both BYOL and supervised learning instances, respectively.
Mitosis domain generalization in histopathology images -- The MIDOG challenge
The goal of the MICCAI MIDOG 2021 challenge has been to propose and evaluate methods that counter this domain shift and derive scanner-agnostic mitosis detection algorithms.
A Graph Policy Network Approach for Volt-Var Control in Power Distribution Systems
We conduct further analysis on the impact of both observations and actions: on the observation end, we examine the robustness of graph-based policy on two typical data acquisition errors in power systems, namely sensor communication failure and measurement misalignment.
Soft Actor-Critic With Integer Actions
Reinforcement learning is well-studied under discrete actions.
PowerGym: A Reinforcement Learning Environment for Volt-Var Control in Power Distribution Systems
We introduce PowerGym, an open-source reinforcement learning environment for Volt-Var control in power distribution systems.
Detecting Mitosis against Domain Shift using a Fused Detector and Deep Ensemble Classification Model for MIDOG Challenge
Mitotic figure count is an important marker of tumor proliferation and has been shown to be associated with patients' prognosis.
