Machine learning methods for small data challenges in molecular science
B Dou, Z Zhu, E Merkurjev, L Ke, L Chen… - Chemical …, 2023 - ACS Publications
Small data are often used in scientific and engineering research due to the presence of
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …
Approaches, challenges, and applications for deep visual odometry: Toward complicated and emerging areas
Visual odometry (VO) is a prevalent way to deal with the relative localization problem, which
is becoming increasingly mature and accurate, but it tends to be fragile under challenging …
is becoming increasingly mature and accurate, but it tends to be fragile under challenging …
Pseudo rgb-d for self-improving monocular slam and depth prediction
Abstract Classical monocular Simultaneous Localization And Mapping (SLAM) and the
recently emerging convolutional neural networks (CNNs) for monocular depth prediction …
recently emerging convolutional neural networks (CNNs) for monocular depth prediction …
Edplvo: Efficient direct point-line visual odometry
This paper introduces an efficient direct visual odometry (VO) algorithm using points and
lines. Pixels on lines are generally adopted in direct methods. However, the original …
lines. Pixels on lines are generally adopted in direct methods. However, the original …
islam: Imperative slam
Simultaneous Localization and Mapping (SLAM) stands as one of the critical challenges in
robot navigation. A SLAM system often consists of a front-end component for motion …
robot navigation. A SLAM system often consists of a front-end component for motion …
Self-supervised monocular depth estimation in dynamic scenes with moving instance loss
M Yue, G Fu, M Wu, X Zhang, H Gu - Engineering Applications of Artificial …, 2022 - Elsevier
Estimating depth from monocular images is a powerful method to perceive valuable
environmental information, which is essential for applications that require three-dimensional …
environmental information, which is essential for applications that require three-dimensional …
Georefine: Self-supervised online depth refinement for accurate dense mapping
We present a robust and accurate depth refinement system, named GeoRefine, for
geometrically-consistent dense mapping from monocular sequences. GeoRefine consists of …
geometrically-consistent dense mapping from monocular sequences. GeoRefine consists of …
Hybrid skip: A biologically inspired skip connection for the UNet architecture
In this work we introduce a biologically inspired long-range skip connection for the UNet
architecture that relies on the perceptual illusion of hybrid images, being images that …
architecture that relies on the perceptual illusion of hybrid images, being images that …
Deep learning based monocular depth prediction: Datasets, methods and applications
Estimating depth from RGB images can facilitate many computer vision tasks, such as indoor
localization, height estimation, and simultaneous localization and mapping (SLAM) …
localization, height estimation, and simultaneous localization and mapping (SLAM) …
[PDF][PDF] Modern Methods of Map Construction Using Optical Sensors Fusion
Map construction, or mapping, plays an important role in robotic applications. Mapping relies
on inherently noisy sensor measurements to construct an accurate representation of a …
on inherently noisy sensor measurements to construct an accurate representation of a …