Search Results for author:
Found 7 papers, 3 papers with code
Deep Learning Models for River Classification at Sub-Meter Resolutions from Multispectral and Panchromatic Commercial Satellite Imagery
In a novel approach, we then use results from the multispectral model to generate training data for FCN that only require panchromatic imagery, of which considerably more is available.
On the Importance and Applicability of Pre-Training for Federated Learning
To make our findings applicable to situations where pre-trained models are not directly available, we explore pre-training with synthetic data or even with clients' data in a decentralized manner, and found that they can already improve FL notably.
Learn Like The Pro: Norms from Theory to Size Neural Computation
The optimal design of neural networks is a critical problem in many applications.
Deep Learning for Strong Lensing Search: Tests of the Convolutional Neural Networks and New Candidates from KiDS DR3
Using the latter training set, about 67\% of the aforementioned 48 candidates are also found, and there are 11 more new strong lensing candidates identified.
Cosmology and Nongalactic Astrophysics
Neural Networks as Geometric Chaotic Maps
The use of artificial neural networks as models of chaotic dynamics has been rapidly expanding.
A Multi-Attention based Neural Network with External Knowledge for Story Ending Predicting Task
Enabling a mechanism to understand a temporal story and predict its ending is an interesting issue that has attracted considerable attention, as in case of the ROC Story Cloze Task (SCT).
3D Semantic Trajectory Reconstruction from 3D Pixel Continuum
This paper presents a method to reconstruct dense semantic trajectory stream of human interactions in 3D from synchronized multiple videos.
