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Found 15 papers, 0 papers with code
The NiuTrans System for the WMT20 Quality Estimation Shared Task
This paper describes the submissions of the NiuTrans Team to the WMT 2020 Quality Estimation Shared Task.
Statistical Inference of Optimal Allocations I: Regularities and their Implications
Moreover, leveraging profound insights from geometric functional analysis on convex and local Lipschitz functionals, we obtain additional generic Fr\'echet differentiability results for the value functions of optimal allocation problems.
Unsupervised Spectral Demosaicing with Lightweight Spectral Attention Networks
This paper presents a deep learning-based spectral demosaicing technique trained in an unsupervised manner.
Statistical Tests for Replacing Human Decision Makers with Algorithms
This paper proposes a statistical framework with which artificial intelligence can improve human decision making.
Degradation-Noise-Aware Deep Unfolding Transformer for Hyperspectral Image Denoising
However, model-based approaches rely on hand-crafted priors and hyperparameters, while learning-based methods are incapable of estimating the inherent degradation patterns and noise distributions in the imaging procedure, which could inform supervised learning.
MSFA-Frequency-Aware Transformer for Hyperspectral Images Demosaicing
The advantage of Maformer is that it can leverage the MSFA information and non-local dependencies present in the data.
Inheriting Bayer's Legacy-Joint Remosaicing and Denoising for Quad Bayer Image Sensor
DJRD includes a newly designed Quad Bayer remosaicing (QB-Re) block, integrated denoising modules based on Swin-transformer and multi-scale wavelet transform.
Sparse Regularized Correlation Filter for UAV Object Tracking with adaptive Contextual Learning and Keyfilter Selection
Another approaches can alleviate the temporal degeneration of learned filters by introducing the temporal regularizer, which depends on the assumption that the filers between consecutive frames should be coherent.
TS4Net: Two-Stage Sample Selective Strategy for Rotating Object Detection
At present, most of the rotating object detection datasets focus on the field of remote sensing, and these images are usually shot in high-altitude scenes.
Dynamic Curriculum Learning for Low-Resource Neural Machine Translation
This eases training by highlighting easy samples that the current model has enough competence to learn.
Impact of Temperature and Relative Humidity on the Transmission of COVID-19: A Modeling Study in China and the United States
Primary outcome measures: Regression analysis of the impact of temperature and relative humidity on the effective reproductive number (R value).
The NiuTrans Machine Translation Systems for WMT19
We participated in 13 translation directions, including 11 supervised tasks, namely EN↔{ZH, DE, RU, KK, LT}, GU→EN and the unsupervised DE↔CS sub-track.
Decision Making with Machine Learning and ROC Curves
Our theoretical discussion is illustrated in the context of a large data set of pregnancy outcomes and doctor diagnosis from the Pre-Pregnancy Checkups of reproductive age couples in Henan Province provided by the Chinese Ministry of Health.
SVM-based Deep Stacking Networks
The deep network model, with the majority built on neural networks, has been proved to be a powerful framework to represent complex data for high performance machine learning.
Part-based Visual Tracking via Structural Support Correlation Filter
In addition, to mitigate the issue of drift away from object further, we introduce inter-frame consistencies of local parts into our model.
