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 …
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 …
Visual slam: What are the current trends and what to expect?
In recent years, Simultaneous Localization and Mapping (SLAM) systems have shown
significant performance, accuracy, and efficiency gain. In this regard, Visual Simultaneous …
significant performance, accuracy, and efficiency gain. In this regard, Visual Simultaneous …
Atloc: Attention guided camera localization
Deep learning has achieved impressive results in camera localization, but current single-
image techniques typically suffer from a lack of robustness, leading to large outliers. To …
image techniques typically suffer from a lack of robustness, leading to large outliers. To …
Selective sensor fusion for neural visual-inertial odometry
Deep learning approaches for Visual-Inertial Odometry (VIO) have proven successful, but
they rarely focus on incorporating robust fusion strategies for dealing with imperfect input …
they rarely focus on incorporating robust fusion strategies for dealing with imperfect input …
Seqnet: Learning descriptors for sequence-based hierarchical place recognition
Visual Place Recognition (VPR) is the task of matching current visual imagery from a camera
to images stored in a reference map of the environment. While initial VPR systems used …
to images stored in a reference map of the environment. While initial VPR systems used …
LIFT-SLAM: A deep-learning feature-based monocular visual SLAM method
HMS Bruno, EL Colombini - Neurocomputing, 2021 - Elsevier
Abstract The Simultaneous Localization and Mapping (SLAM) problem addresses the
possibility of a robot to localize itself in an unknown environment and simultaneously build a …
possibility of a robot to localize itself in an unknown environment and simultaneously build a …
Beyond tracking: Selecting memory and refining poses for deep visual odometry
Most previous learning-based visual odometry (VO) methods take VO as a pure tracking
problem. In contrast, we present a VO framework by incorporating two additional …
problem. In contrast, we present a VO framework by incorporating two additional …
Deep reinforcement learning for soft, flexible robots: Brief review with impending challenges
The increasing trend of studying the innate softness of robotic structures and amalgamating
it with the benefits of the extensive developments in the field of embodied intelligence has …
it with the benefits of the extensive developments in the field of embodied intelligence has …
BIM-PoseNet: Indoor camera localisation using a 3D indoor model and deep learning from synthetic images
The ubiquity of cameras built in mobile devices has resulted in a renewed interest in image-
based localisation in indoor environments where the global navigation satellite system …
based localisation in indoor environments where the global navigation satellite system …