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Found 9 papers, 4 papers with code
Revisiting the Encoding of Satellite Image Time Series
Satellite Image Time Series (SITS) representation learning is complex due to high spatiotemporal resolutions, irregular acquisition times, and intricate spatiotemporal interactions.
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Source-Free Adaptive Gaze Estimation by Uncertainty Reduction
In light of this, we present an unsupervised source-free domain adaptation approach for gaze estimation, which adapts a source-trained gaze estimator to unlabeled target domains without source data.
Tampered VAE for Improved Satellite Image Time Series Classification
We hope the proposed framework can serve as a baseline for crop classification with SITS for its modularity and simplicity.
AlphaFold Accelerates Artificial Intelligence Powered Drug Discovery: Efficient Discovery of a Novel Cyclin-dependent Kinase 20 (CDK20) Small Molecule Inhibitor
The AlphaFold computer program predicted protein structures for the whole human genome, which has been considered as a remarkable breakthrough both in artificial intelligence (AI) application and structural biology.
Gaze Estimation with an Ensemble of Four Architectures
This paper presents a method for gaze estimation according to face images.
FlatteNet: A Simple Versatile Framework for Dense Pixelwise Prediction
In this paper, we focus on devising a versatile framework for dense pixelwise prediction whose goal is to assign a discrete or continuous label to each pixel for an image.
An overlapping-free leaf segmentation method for plant point clouds
The proposed method can also facilitate the automatic traits estimation of each single leaf (such as the leaf area, length, and width), which has potential to become a highly effective tool for plant research and agricultural engineering.
An Integrated Image Filter for Enhancing Change Detection Results
In this paper, we present an integrated filter which comprises a weighted local guided image filter and a weighted spatiotemporal tree filter.
Bayesian inverse regression for dimension reduction with small datasets
We consider supervised dimension reduction problems, namely to identify a low dimensional projection of the predictors $\-x$ which can retain the statistical relationship between $\-x$ and the response variable $y$.
