research
∙
09/17/2023
Deep Neighbor Layer Aggregation for Lightweight Self-Supervised Monocular Depth Estimation
With the frequent use of self-supervised monocular depth estimation in r...
share
research
∙
08/04/2023
Rethinking Class Activation Maps for Segmentation: Revealing Semantic Information in Shallow Layers by Reducing Noise
Class activation maps are widely used for explaining deep neural network...
research
∙
10/14/2021
Training Neural Networks for Solving 1-D Optimal Piecewise Linear Approximation
Recently, the interpretability of deep learning has attracted a lot of a...
research
∙
05/17/2021
How to Explain Neural Networks: A perspective of data space division
Interpretability of intelligent algorithms represented by deep learning ...
research
∙
04/24/2021
CFNet: LiDAR-Camera Registration Using Calibration Flow Network
As an essential procedure of data fusion, LiDAR-camera calibration is cr...
research
∙
04/01/2021
High-quality Low-dose CT Reconstruction Using Convolutional Neural Networks with Spatial and Channel Squeeze and Excitation
Low-dose computed tomography (CT) allows the reduction of radiation risk...
research
∙
12/27/2020
Lidar and Camera Self-Calibration using CostVolume Network
In this paper, we propose a novel online self-calibration approach for L...
research
∙
10/14/2020
Semantic Flow-guided Motion Removal Method for Robust Mapping
Moving objects in scenes are still a severe challenge for the SLAM syste...
research
∙
03/09/2018
