The effective training of supervised Person Re-identification (Re-ID) models requires sufficient pairwise labeled data. However, when there is limited annotation resource, it is difficult to collect pairwise labeled data. We consider a challenging and practical problem called Early Active Learning, which is applied to the early stage of experiments when there is no pre-labeled sample available as references for human annotating. Previous early active learning methods suffer from two limitations for Re-ID. First, these instance-based algorithms select instances rather than pairs, which can result in missing optimal pairs for Re-ID. Second, most of these methods only consider the representativeness of instances, which can result in selecting less diverse and less informative pairs. To overcome these limitations, we propose a novel pair-based active learning for Re-ID. Our algorithm selects pairs instead of instances from the entire dataset for annotation. Besides representativeness, we further take into account the uncertainty and the diversity in terms of pairwise relations. Therefore, our algorithm can produce the most representative, informative, and diverse pairs for Re-ID data annotation. Extensive experimental results on five benchmark Re-ID datasets have demonstrated the superiority of the proposed pair-based early active learning algorithm.
BackgroundEpimedii herba is one of the most frequently used herbs in formulas that are prescribed for the treatment of osteoporosis in China and its main constituent is Epimedium pubescen flavonoid (EPF). However, it is unclear whether EPF during chronic exposure to cigarette smoke may have a protective influence on the skeleton. The present study investigated the effect of EPF on bone mineral status and bone turnover in a rat model of human relatively high exposure to cigarette smoke.MethodsFifty male Wistar rats were randomized into five groups: controls, passive smoking groups and passive smoking rats administered EPF at three dosage levels (75, 150 or 300 mg/kg/day) in drinking water for 4 months. A rat model of passive smoking was prepared by breeding male rats in a cigarette-smoking box. Bone mineral content (BMC), bone mineral density (BMD), bone turnover markers, bone histomorphometric parameters and biomechanical properties were examined.ResultsSmoke exposure decreased BMC and BMD, increased bone turnover (inhibited bone formation and stimulated its resorption), affected bone histomorphometry (increased trabecular separation and osteoclast surface per bone surface; decreased trabecular bone volume, trabecular thickness, trabecular number, cortical thickness, bone formation rate and osteoblast surface per bone surface), and reduced mechanical properties. EPF supplementation during cigarette smoke exposure prevented smoke-induced changes in bone mineral status and bone turnover.ConclusionThe results suggest that EPF can prevent the adverse effects of smoke exposure on bone by stimulating bone formation and inhibiting bone turnover and bone resorption.
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