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04/14/2023
Multi-fidelity prediction of fluid flow and temperature field based on transfer learning using Fourier Neural Operator
Data-driven prediction of fluid flow and temperature distribution in mar...
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04/11/2023
SportsMOT: A Large Multi-Object Tracking Dataset in Multiple Sports Scenes
Multi-object tracking in sports scenes plays a critical role in gatherin...
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02/23/2023
Uncertainty Guided Ensemble Self-Training for Semi-Supervised Global Field Reconstruction
Recovering a globally accurate complex physics field from limited sensor...
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02/20/2023
RecFNO: a resolution-invariant flow and heat field reconstruction method from sparse observations via Fourier neural operator
Perception of the full state is an essential technology to support the m...
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02/08/2023
FR-LIO: Fast and Robust Lidar-Inertial Odometry by Tightly-Coupled Iterated Kalman Smoother and Robocentric Voxels
This paper presents a fast lidar-inertial odometry (LIO) system that is ...
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01/17/2023
Multi-fidelity surrogate modeling for temperature field prediction using deep convolution neural network
Temperature field prediction is of great importance in the thermal desig...
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03/10/2022
Semi-supervision semantic segmentation with uncertainty-guided self cross supervision
As a powerful way of realizing semi-supervised segmentation, the cross s...
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03/08/2022
Contrastive Enhancement Using Latent Prototype for Few-Shot Segmentation
Few-shot segmentation enables the model to recognize unseen classes with...
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02/14/2022
Deep Monte Carlo Quantile Regression for Quantifying Aleatoric Uncertainty in Physics-informed Temperature Field Reconstruction
For the temperature field reconstruction (TFR), a complex image-to-image...
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01/26/2022
A deep learning method based on patchwise training for reconstructing temperature field
Physical field reconstruction is highly desirable for the measurement an...
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01/01/2022
A Relaxed Energy Function Based Analog Neural Network Approach to Target Localization in Distributed MIMO Radar
Analog neural networks are highly effective to solve some optimization p...
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09/26/2021
Physics-informed Convolutional Neural Networks for Temperature Field Prediction of Heat Source Layout without Labeled Data
Recently, surrogate models based on deep learning have attracted much at...
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08/17/2021
TFRD: A Benchmark Dataset for Research on Temperature Field Reconstruction of Heat-Source Systems
Temperature field reconstruction of heat source systems (TFR-HSS) with l...
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07/09/2021
IDRLnet: A Physics-Informed Neural Network Library
Physics Informed Neural Network (PINN) is a scientific computing framewo...
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03/20/2021
A Deep Neural Network Surrogate Modeling Benchmark for Temperature Field Prediction of Heat Source Layout
Thermal issue is of great importance during layout design of heat source...
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11/02/2020
Deep Feature Augmentation for Occluded Image Classification
Due to the difficulty in acquiring massive task-specific occluded images...
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08/30/2019
Delay-Optimal and Energy-Efficient Communications with Markovian Arrivals
In this paper, delay-optimal and energy-efficient communication is studi...
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03/14/2019