664 research outputs found
Understanding and Diagnosing Visual Tracking Systems
Several benchmark datasets for visual tracking research have been proposed in
recent years. Despite their usefulness, whether they are sufficient for
understanding and diagnosing the strengths and weaknesses of different trackers
remains questionable. To address this issue, we propose a framework by breaking
a tracker down into five constituent parts, namely, motion model, feature
extractor, observation model, model updater, and ensemble post-processor. We
then conduct ablative experiments on each component to study how it affects the
overall result. Surprisingly, our findings are discrepant with some common
beliefs in the visual tracking research community. We find that the feature
extractor plays the most important role in a tracker. On the other hand,
although the observation model is the focus of many studies, we find that it
often brings no significant improvement. Moreover, the motion model and model
updater contain many details that could affect the result. Also, the ensemble
post-processor can improve the result substantially when the constituent
trackers have high diversity. Based on our findings, we put together some very
elementary building blocks to give a basic tracker which is competitive in
performance to the state-of-the-art trackers. We believe our framework can
provide a solid baseline when conducting controlled experiments for visual
tracking research
Bounded-Distortion Metric Learning
Metric learning aims to embed one metric space into another to benefit tasks
like classification and clustering. Although a greatly distorted metric space
has a high degree of freedom to fit training data, it is prone to overfitting
and numerical inaccuracy. This paper presents {\it bounded-distortion metric
learning} (BDML), a new metric learning framework which amounts to finding an
optimal Mahalanobis metric space with a bounded-distortion constraint. An
efficient solver based on the multiplicative weights update method is proposed.
Moreover, we generalize BDML to pseudo-metric learning and devise the
semidefinite relaxation and a randomized algorithm to approximately solve it.
We further provide theoretical analysis to show that distortion is a key
ingredient for stability and generalization ability of our BDML algorithm.
Extensive experiments on several benchmark datasets yield promising results
Stability Analysis of a Car-Following Model on Two Lanes
Considering lateral influence from adjacent lane, an improved car-following model is developed in this paper. Then linear and nonlinear stability analyses are carried out. The modified Korteweg-de Vries (MKdV) equation is derived with the kink-antikink soliton solution. Numerical simulations are implemented and the result shows good consistency with theoretical study
Hashimoto’s encephalopathy cases: Chinese experience
BACKGROUND: Hashimoto’s encephalopathy is a poorly understood syndrome consisting of heterogeneous neurological symptoms and high serum antithyroid antibody titers, typically responding to steroids. More clinical series studies are required to characterize the clinical, laboratory and imaging features, and outcomes, especially in the Chinese population. METHODS: We analyzed the clinical, laboratory, and imaging features and outcomes of thirteen consecutive patients with Hashimoto’s encephalopathy diagnosed in Xuan Wu Hospital, Beijing from 2005 to 2010 retrospectively. RESULTS: Cognitive impairment (84.6%) and psychiatric symptoms (38.5%) were the most frequent symptoms. Seizures (30.8%) and myoclonus (7.7%) were less common than previously described. Three (23.1%) patients showed abnormal signals in hippocampus or temporal lobe, which were believed related to their memory disorders or seizures. MRI changes showed resolution paralleling clinical improvement in one patient. Among eight patients who received steroid therapy, five patients recovered, one patient improved with residual deficits, and two patients relapsed or had no effect. Among five non-steroid treated patients, three patients experienced stable remission with antiepileptic drugs or general neurotrophic therapy, and two patients experienced continuous deterioration. CONCLUSIONS: Most patients with Hashimoto’s encephalopathy showed good response to steroids. Some patients improved without steroid therapy. Considering its reversible course, we recommend that Hashimoto’s encephalopathy should always be in the differential diagnosis while evaluating disorders of the central nervous system
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