AIMC Topic: Vision, Ocular
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Laser-Based Door Localization for Autonomous Mobile Service Robots.
Sensors (Basel, Switzerland)
May 31, 2023
For autonomous mobile service robots, closed doors that are in their way are restricting obstacles. In order to open doors with on-board manipulation skills, a robot needs to be able to localize the door's key features, such as the hinge and handle, ...
Hierarchical Vision Navigation System for Quadruped Robots with Foothold Adaptation Learning.
Sensors (Basel, Switzerland)
May 30, 2023
Legged robots can travel through complex scenes via dynamic foothold adaptation. However, it remains a challenging task to efficiently utilize the dynamics of robots in cluttered environments and to achieve efficient navigation. We present a novel hi...
A Preliminary Study of Deep Learning Sensor Fusion for Pedestrian Detection.
Sensors (Basel, Switzerland)
Apr 21, 2023
Most pedestrian detection methods focus on bounding boxes based on fusing RGB with lidar. These methods do not relate to how the human eye perceives objects in the real world. Furthermore, lidar and vision can have difficulty detecting pedestrians in...
Artificial Intelligence for skeleton-based physical rehabilitation action evaluation: A systematic review.
Computers in biology and medicine
Mar 31, 2023
Performing prescribed physical exercises during home-based rehabilitation programs plays an important role in regaining muscle strength and improving balance for people with different physical disabilities. However, patients attending these programs ...
New Approaches to 3D Vision.
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Dec 13, 2022
New approaches to 3D vision are enabling new advances in artificial intelligence and autonomous vehicles, a better understanding of how animals navigate the 3D world, and new insights into human perception in virtual and augmented reality. Whilst tra...
Deep problems with neural network models of human vision.
The Behavioral and brain sciences
Dec 1, 2022
Deep neural networks (DNNs) have had extraordinary successes in classifying photographic images of objects and are often described as the best models of biological vision. This conclusion is largely based on three sets of findings: (1) DNNs are more ...
Understanding Human Object Vision: A Picture Is Worth a Thousand Representations.
Annual review of psychology
Nov 15, 2022
Objects are the core meaningful elements in our visual environment. Classic theories of object vision focus upon object recognition and are elegant and simple. Some of their proposals still stand, yet the simplicity is gone. Recent evolutions in beha...
On the role of feedback in image recognition under noise and adversarial attacks: A predictive coding perspective.
Neural networks : the official journal of the International Neural Network Society
Oct 27, 2022
Brain-inspired machine learning is gaining increasing consideration, particularly in computer vision. Several studies investigated the inclusion of top-down feedback connections in convolutional networks; however, it remains unclear how and when thes...
On the Sufficient Condition for Solving the Gap-Filling Problem Using Deep Convolutional Neural Networks.
IEEE transactions on neural networks and learning systems
Oct 27, 2022
Deep convolutional neural networks (DCNNs) are routinely used for image segmentation of biomedical data sets to obtain quantitative measurements of cellular structures like tissues. These cellular structures often contain gaps in their boundaries, le...
Sensor Data Fusion Based on Deep Learning for Computer Vision Applications and Medical Applications.
Sensors (Basel, Switzerland)
Oct 21, 2022
Sensor fusion is the process of merging data from many sources, such as radar, lidar and camera sensors, to provide less uncertain information compared to the information collected from single source [...].
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