Monocular depth estimation using deep learning: A review
In current decades, significant advancements in robotics engineering and autonomous
vehicles have improved the requirement for precise depth measurements. Depth estimation …
vehicles have improved the requirement for precise depth measurements. Depth estimation …
Deep learning-based monocular depth estimation methods—a state-of-the-art review
Monocular depth estimation from Red-Green-Blue (RGB) images is a well-studied ill-posed
problem in computer vision which has been investigated intensively over the past decade …
problem in computer vision which has been investigated intensively over the past decade …
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 …
Application of Machine Vision Techniques in Low-Cost Devices to Improve Efficiency in Precision Farming
In the context of recent technological advancements driven by distributed work and open-
source resources, computer vision stands out as an innovative force, transforming how …
source resources, computer vision stands out as an innovative force, transforming how …
A general framework for building surrogate models for uncertainty quantification in computational electromagnetics
R Hu, V Monebhurrun, R Himeno… - … on Antennas and …, 2021 - ieeexplore.ieee.org
In uncertainty analysis, surrogate modeling techniques demonstrate high efficiency and
reliable precision in estimating the uncertainty for the finite difference time domain (FDTD) …
reliable precision in estimating the uncertainty for the finite difference time domain (FDTD) …
[HTML][HTML] An efficient encoder–decoder model for portrait depth estimation from single images trained on pixel-accurate synthetic data
Depth estimation from a single image frame is a fundamental challenge in computer vision,
with many applications such as augmented reality, action recognition, image understanding …
with many applications such as augmented reality, action recognition, image understanding …
Sensor-aided EMF exposure assessments in an urban environment using artificial neural networks
This paper studies the time and space mapping of the electromagnetic field (EMF) exposure
induced by cellular base station antennas (BSA) using artificial neural networks (ANN). The …
induced by cellular base station antennas (BSA) using artificial neural networks (ANN). The …
An improved visual odometer based on Lucas-Kanade optical flow and ORB feature
L Zhong, L Meng, W Hou, L Huang - IEEE Access, 2023 - ieeexplore.ieee.org
Visual odometer is an important part of SLAM system. Visual odometer based on feature
points is the current mainstream. Featured based method completes the positioning by …
points is the current mainstream. Featured based method completes the positioning by …
A review of benchmark datasets and training loss functions in neural depth estimation
In many applications, such as robotic perception, scene understanding, augmented reality,
3D reconstruction, and medical image analysis, depth from images is a fundamentally ill …
3D reconstruction, and medical image analysis, depth from images is a fundamentally ill …
Deep learning for consumer devices and services 2—AI gets embedded at the edge
P Corcoran, J Lemley, C Costache… - IEEE Consumer …, 2019 - ieeexplore.ieee.org
The recent explosive growth of deep learning is enabling a new generation of intelligent
consumer devices. Specialized deep learning inference now provides data analysis …
consumer devices. Specialized deep learning inference now provides data analysis …