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08/28/2023
End-to-End Driving via Self-Supervised Imitation Learning Using Camera and LiDAR Data
In autonomous driving, the end-to-end (E2E) driving approach that predic...
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05/10/2022
Self-supervised regression learning using domain knowledge: Applications to improving self-supervised denoising in imaging
Regression that predicts continuous quantity is a central part of applic...
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04/17/2022
Accelerated MRI With Deep Linear Convolutional Transform Learning
Recent studies show that deep learning (DL) based MRI reconstruction out...
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04/30/2021
Improved Real-Time Monocular SLAM Using Semantic Segmentation on Selective Frames
Monocular simultaneous localization and mapping (SLAM) is emerging in ad...
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04/01/2021
Improved and efficient inter-vehicle distance estimation using road gradients of both ego and target vehicles
In advanced driver assistant systems and autonomous driving, it is cruci...
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12/02/2020
An Improved Iterative Neural Network for High-Quality Image-Domain Material Decomposition in Dual-Energy CT
Dual-energy computed tomography (DECT) has been widely used in many appl...
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02/27/2020
Momentum-Net for Low-Dose CT Image Reconstruction
This paper applies the recent fast iterative neural network framework, M...
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08/04/2019
BCD-Net for Low-dose CT Reconstruction: Acceleration, Convergence, and Generalization
Obtaining accurate and reliable images from low-dose computed tomography...
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07/26/2019
Momentum-Net: Fast and convergent iterative neural network for inverse problems
Iterative neural networks (INN) are rapidly gaining attention for solvin...
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06/05/2019
Improved low-count quantitative PET reconstruction with a variational neural network
Image reconstruction in low-count PET is particularly challenging becaus...
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02/21/2019
Convolutional Analysis Operator Learning: Dependence on Training Data
Convolutional analysis operator learning (CAOL) enables the unsupervised...
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02/20/2018
Deep BCD-Net Using Identical Encoding-Decoding CNN Structures for Iterative Image Recovery
In "extreme" computational imaging that collects extremely undersampled ...
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02/15/2018
Convolutional Analysis Operator Learning: Acceleration, Convergence, Application, and Neural Networks
Convolutional operator learning is increasingly gaining attention in man...
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11/02/2017