6,075 research outputs found
Position-Dependent Urinary Retention in a Traumatic Brain Injury Patient: A Case Report
INTRODUCTION: Voiding disorders are common complication after traumatic brain injury. Usually, they are caused by neurogenic bladder although they can also occur as a result of other pathologic processes and conditions as well as side effects of medications. CASE PRESENTATION: A 62-year-old traumatic brain injury patient with position-dependent urinary retention is presented in this article. Neurogenic bladder with detrusor sphincter dyssynergia was suspected initially, with detection of multiple small bladder stones as the final cause of his urinary retention afterwards. CONCLUSION: Careful clinical, imaging, and urodynamic evaluation must be performed in traumatic brain injury patients to exclude the coexistence of two or more factors leading to urinary dysfunction in this population group
Local Descriptors Optimized for Average Precision
Extraction of local feature descriptors is a vital stage in the solution
pipelines for numerous computer vision tasks. Learning-based approaches improve
performance in certain tasks, but still cannot replace handcrafted features in
general. In this paper, we improve the learning of local feature descriptors by
optimizing the performance of descriptor matching, which is a common stage that
follows descriptor extraction in local feature based pipelines, and can be
formulated as nearest neighbor retrieval. Specifically, we directly optimize a
ranking-based retrieval performance metric, Average Precision, using deep
neural networks. This general-purpose solution can also be viewed as a listwise
learning to rank approach, which is advantageous compared to recent local
ranking approaches. On standard benchmarks, descriptors learned with our
formulation achieve state-of-the-art results in patch verification, patch
retrieval, and image matching.Comment: 13 pages, 8 figures. IEEE Conference on Computer Vision and Pattern
Recognition (CVPR), 201
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