[HTML][HTML] A review of uncertainty quantification in deep learning: Techniques, applications and challenges
Uncertainty quantification (UQ) methods play a pivotal role in reducing the impact of
uncertainties during both optimization and decision making processes. They have been …
uncertainties during both optimization and decision making processes. They have been …
Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things
In the Internet-of-Things (IoT) era, billions of sensors and devices collect and process data
from the environment, transmit them to cloud centers, and receive feedback via the Internet …
from the environment, transmit them to cloud centers, and receive feedback via the Internet …
Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras
Z Teed, J Deng - Advances in neural information …, 2021 - proceedings.neurips.cc
We introduce DROID-SLAM, a new deep learning based SLAM system. DROID-SLAM
consists of recurrent iterative updates of camera pose and pixelwise depth through a Dense …
consists of recurrent iterative updates of camera pose and pixelwise depth through a Dense …
Co-slam: Joint coordinate and sparse parametric encodings for neural real-time slam
We present Co-SLAM, a neural RGB-D SLAM system based on a hybrid representation, that
performs robust camera tracking and high-fidelity surface reconstruction in real time. Co …
performs robust camera tracking and high-fidelity surface reconstruction in real time. Co …
Lite-mono: A lightweight cnn and transformer architecture for self-supervised monocular depth estimation
Self-supervised monocular depth estimation that does not require ground truth for training
has attracted attention in recent years. It is of high interest to design lightweight but effective …
has attracted attention in recent years. It is of high interest to design lightweight but effective …
Unsupervised scale-consistent depth and ego-motion learning from monocular video
Recent work has shown that CNN-based depth and ego-motion estimators can be learned
using unlabelled monocular videos. However, the performance is limited by unidentified …
using unlabelled monocular videos. However, the performance is limited by unidentified …
Deep learning sensor fusion for autonomous vehicle perception and localization: A review
Autonomous vehicles (AV) are expected to improve, reshape, and revolutionize the future of
ground transportation. It is anticipated that ordinary vehicles will one day be replaced with …
ground transportation. It is anticipated that ordinary vehicles will one day be replaced with …