Learning Optical Flow Using Deep Dilated Residual Networks
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2898988
Abstract: Nowadays, convolutional neural networks achieve remarkable performance on optical flow estimation because of its strong non-linear fitting ability. Most of them adopt the U-Net architecture, which contains an encoder part and a decoder part. In… read more here.
Keywords: learning optical; dilated residual; flow; optical flow ... See more keywords
From Pixels to Percepts: Highly Robust Edge Perception and Contour Following Using Deep Learning and an Optical Biomimetic Tactile Sensor
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2019.2899192
Abstract: Deep learning has the potential to have same the impact on robot touch as it has had on robot vision. Optical tactile sensors act as a bridge between the subjects by allowing techniques from vision… read more here.
Keywords: learning optical; optical biomimetic; biomimetic tactile; tactile ... See more keywords
Deep learning for optical tweezers
Sign Up to like & getrecommendations! Published in 2024 at "Nanophotonics"
DOI: 10.1515/nanoph-2024-0013
Abstract: Abstract Optical tweezers exploit light–matter interactions to trap particles ranging from single atoms to micrometer-sized eukaryotic cells. For this reason, optical tweezers are a ubiquitous tool in physics, biology, and nanotechnology. Recently, the use of… read more here.
Keywords: deep learning; learning optical; biology; optical tweezers ... See more keywords