1,935 research outputs found
Repulsion Loss: Detecting Pedestrians in a Crowd
Detecting individual pedestrians in a crowd remains a challenging problem
since the pedestrians often gather together and occlude each other in
real-world scenarios. In this paper, we first explore how a state-of-the-art
pedestrian detector is harmed by crowd occlusion via experimentation, providing
insights into the crowd occlusion problem. Then, we propose a novel bounding
box regression loss specifically designed for crowd scenes, termed repulsion
loss. This loss is driven by two motivations: the attraction by target, and the
repulsion by other surrounding objects. The repulsion term prevents the
proposal from shifting to surrounding objects thus leading to more crowd-robust
localization. Our detector trained by repulsion loss outperforms all the
state-of-the-art methods with a significant improvement in occlusion cases.Comment: Accepted to IEEE Conference on Computer Vision and Pattern
Recognition (CVPR) 201
Geometric bionics: Lotus effect helps polystyrene nanotube films get good blood compatibility
Various biomaterials have been widely used for manufacturing biomedical applications including artificial organs, medical devices and disposable clinical apparatus, such as vascular prostheses, blood pumps, artificial kidney, artificial hearts, dialyzers and plasma separators, which could be used in contact with blood^1^. However, the research tasks of improving hemocompatibility of biomaterials have been carrying out with the development of biomedical requirements^2^. Since the interactions that lead to surface-induced thrombosis occurring at the blood-biomaterial interface become a reason of familiar current complications with grafts therapy, improvement of the blood compatibility of artificial polymer surfaces is, therefore a major issue in biomaterials science^3^. After decades of focused research, various approaches of modifying biomaterial surfaces through chemical or biochemical methods to improve their hemocompatibility were obtained^1^. In this article, we report that polystyrene nanotube films with morphology similar to the papilla on lotus leaf can be used as blood-contacted biomaterials by virtue of Lotus effect^4^. Clearly, this idea, resulting from geometric bionics that mimicking the structure design of lotus leaf, is very novel technique for preparation of hemocompatible biomaterials
Observation of electric current induced by optically injected spin current
A normally incident light of linear polarization injects a pure spin current
in a strip of 2-dimensional electron gas with spin-orbit coupling. We report
observation of an electric current with a butterfly-like pattern induced by
such a light shed on the vicinity of a crossbar shaped InGaAs/InAlAs quantum
well. Its light polarization dependence is the same as that of the spin
current. We attribute the observed electric current to be converted from the
optically injected spin current caused by scatterings near the crossing. Our
observation provides a realistic technique to detect spin currents, and opens a
new route to study the spin-related science and engineering in semiconductors.Comment: 15 pages, 4 figure
Plasma gelsolin levels and outcomes after aneurysmal subarachnoid hemorrhage
INTRODUCTION: Lower gelsolin levels have been associated with the severity and poor outcome of critical illness. Nevertheless, their link with clinical outcomes of aneurysmal subarachnoid hemorrhage is unknown. Therefore, we aimed to investigate the relationship between plasma gelsolin levels and clinical outcomes in patients with aneurysmal subarachnoid hemorrhage. METHODS: A total of 262 consecutive patients and 150 healthy subjects were included. Plasma gelsolin levels were measured by enzyme-linked immunosorbent assay. Mortality and poor long-term outcome (Glasgow Outcome Scale score of 1-3) at 6 months were recorded. RESULTS: Plasma gelsolin levels on admission were substantially lower in patients than in healthy controls (66.9 (26.4) mg/L vs. 126.4 (35.4) mg/L, P < 0.001), and negatively associated with World Federation of Neurological Surgeons score (r = -0.554, P < 0.001) and Fisher score (r = -0.538, P < 0.001), and identified as an independent predictor of poor functional outcome (odds ratio, 0.957; 95% confidence interval (CI), 0.933-0.983; P = 0.001) and death (odds ratio, 0.953; 95% CI, 0.917-0.990; P = 0.003) after 6 months. The areas under the ROC curve of gelsolin for functional outcome and mortality were similar to those of World Federation of Neurological Surgeons score and Fisher score (all P > 0.05). Gelsolin improved the predictive values of World Federation of Neurological Surgeons score and Fisher score for functional outcome (both P < 0.05), but not for mortality (both P > 0.05). CONCLUSIONS: Gelsolin levels are a useful, complementary tool to predict functional outcome and mortality 6 months after aneurysmal subarachnoid hemorrhage
Image Data Augmentation for Deep Learning: A Survey
Deep learning has achieved remarkable results in many computer vision tasks.
Deep neural networks typically rely on large amounts of training data to avoid
overfitting. However, labeled data for real-world applications may be limited.
By improving the quantity and diversity of training data, data augmentation has
become an inevitable part of deep learning model training with image data.
As an effective way to improve the sufficiency and diversity of training
data, data augmentation has become a necessary part of successful application
of deep learning models on image data. In this paper, we systematically review
different image data augmentation methods. We propose a taxonomy of reviewed
methods and present the strengths and limitations of these methods. We also
conduct extensive experiments with various data augmentation methods on three
typical computer vision tasks, including semantic segmentation, image
classification and object detection. Finally, we discuss current challenges
faced by data augmentation and future research directions to put forward some
useful research guidance
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