When searching real-world scenes, human attention is guided by knowledge of the plausible size of target object (if an object is six feet tall, it isn't your cat). Computer algorithms typically do not do this, but perhaps they should.
OBJECTIVE: Many computer vision and robotic applications require the implementation of robust and efficient target-tracking algorithms on a moving platform. However, deployment of a real-time system is challenging, even with the computational power o...
IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Jul 1, 2017
In this paper, we explore how the integration of auditory and visual cues can help teach the timing of motor skills for the purpose of motor function rehabilitation. We conducted a study using Amazon's Mechanical Turk in which 106 participants played...
What are the roles of central and peripheral vision in human scene recognition? Larson and Loschky (2009) showed that peripheral vision contributes more than central vision in obtaining maximum scene recognition accuracy. However, central vision is m...
Decoding of human brain activity has always been a primary goal in neuroscience especially with functional magnetic resonance imaging (fMRI) data. In recent years, Convolutional neural network (CNN) has become a popular method for the extraction of f...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Aug 1, 2016
Visual prosthesis holds hope of vision restoration for millions with retinal degenerative diseases. Machine learning techniques such as artificial neural networks could help in improving prosthetic devices as they could learn how the brain encodes in...