Boosting cross‐task adversarial attack with random blur
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22932
Abstract: Deep neural networks are highly vulnerable to adversarial examples, and these adversarial examples stay malicious when transferred to other neural networks. Many works exploit this transferability of adversarial examples to execute black‐box attacks. However, most… read more here.
Keywords: random; cross task; adversarial examples; blur ... See more keywords
Automatic Detection of Simulated Motion Blur in Mammograms.
Sign Up to like & getrecommendations! Published in 2020 at "Medical physics"
DOI: 10.1002/mp.14069
Abstract: PURPOSE To use machine-learning algorithms and blur measure (BM) operators to automatically detect motion blur in mammograms. Motion blur has been reported to reduce lesion detection performance and mask small abnormalities, resulting in failure to… read more here.
Keywords: motion; motion blur; automatic detection; blur mammograms ... See more keywords
Three-dimensional binocular eye–hand coordination in normal vision and with simulated visual impairment
Sign Up to like & getrecommendations! Published in 2017 at "Experimental Brain Research"
DOI: 10.1007/s00221-017-5160-8
Abstract: Sensorimotor coupling in healthy humans is demonstrated by the higher accuracy of visually tracking intrinsically—rather than extrinsically—generated hand movements in the fronto-parallel plane. It is unknown whether this coupling also facilitates vergence eye movements for… read more here.
Keywords: visual impairment; accuracy; blur; hand ... See more keywords
Single image defocus blur segmentation using Local Ternary Pattern
Sign Up to like & getrecommendations! Published in 2020 at "ICT Express"
DOI: 10.1016/j.icte.2019.10.003
Abstract: Abstract This work presents an efficient LTP-based sharpness measure for blur detection and segmentation. The proposed method transforms each pixel into ternary codes depending on the differences of intensity of the central pixel with the… read more here.
Keywords: blur segmentation; segmentation; image defocus; defocus blur ... See more keywords
Defocus Blur Detection by Fusing Multiscale Deep Features With Conv-LSTM
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2996200
Abstract: Defocus blur detection aiming at distinguishing out-of-focus blur and sharpness has attracted considerable attention in computer vision. The present blur detectors suffer from scale ambiguity, which results in blur boundaries and low accuracy in blur… read more here.
Keywords: defocus blur; blur detection; blur; multiscale deep ... See more keywords
Blur-Countering Keypoint Detection via Eigenvalue Asymmetry
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3020561
Abstract: Well-known corner or local extrema feature based detectors such as FAST and DoG have achieved noticeable successes. However, detecting keypoints in the presence of blur has remained to be an unresolved issue. As a matter… read more here.
Keywords: blur; asymmetry; keypoint detection; blur countering ... See more keywords
A Reference-Free Image Index to Simultaneously Quantify Infrared-Imaging Fixed-Pattern-Noise and Blur Artifacts
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3109561
Abstract: A reference-free image index to jointly assess infrared-imaging fixed-pattern-noise and blur artifacts is proposed in this work. The proposed index is based on tuned-spatial-domain filtering, which works by combining two Laplace operators to simultaneously quantify… read more here.
Keywords: fixed pattern; pattern noise; blur; infrared imaging ... See more keywords
RAID-Net: Region-Aware Image Deblurring Network Under Guidance of the Image Blur Formulation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3194032
Abstract: Image deblurring is a challenging field in computational photography and computer vision. In the deep learning era, deblurring methods boosted with neural networks achieve significant results. However, the existing methods mainly focus on solving specific… read more here.
Keywords: blur; network; image deblurring; raid net ... See more keywords
Blur-Robust Object Detection Using Feature-Level Deblurring via Self-Guided Knowledge Distillation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3194898
Abstract: Images captured from real-world environments often include blur artifacts resulting from camera movement, dynamic object motion, or out-of-focus. Although such blur artifacts are inevitable, most object detection methods do not have special considerations for them;… read more here.
Keywords: blur; guided knowledge; self guided; detection ... See more keywords
BaMBNet: A Blur-Aware Multi-Branch Network for Dual-Pixel Defocus Deblurring
Sign Up to like & getrecommendations! Published in 2022 at "IEEE/CAA Journal of Automatica Sinica"
DOI: 10.1109/jas.2022.105563
Abstract: Reducing the defocus blur that arises from the finite aperture size and short exposure time is an essential problem in computational photography. It is very challenging because the blur kernel is spatially varying and difficult… read more here.
Keywords: blur; bambnet; defocus deblurring; dual pixel ... See more keywords
Adversarial Blur-Deblur Network for Robust UAV Tracking
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2023.3236584
Abstract: Unmanned aerial vehicle (UAV) tracking has been widely applied in real-world applications such as surveillance and monitoring. However, the inherent high maneuverability and agility of UAV often lead to motion blur, which can impair the… read more here.
Keywords: blur; blur deblur; adversarial blur; deblur network ... See more keywords