Small object detection is an interesting topic in computer vision. With the rapid development in deep learning, it has drawn attention of several researchers with innovations in approaches to join a race. These innovations proposed comprise region proposals, divided grid cell, multiscale feature maps, and new loss function. As a result, performance of object detection has recently had significant improvements. However, most of the state-of-the-art detectors, both in one-stage and two-stage approaches, have struggled with detecting small objects. In this study, we evaluate current state-of-the-art models based on deep learning in both approaches such as Fast RCNN, Faster RCNN, RetinaNet, and YOLOv3. We provide a profound assessment of the advantages and limitations of models. Specifically, we run models with different backbones on different datasets with multiscale objects to find out what types of objects are suitable for each model along with backbones. Extensive empirical evaluation was conducted on 2 standard datasets, namely, a small object dataset and a filtered dataset from PASCAL VOC 2007. Finally, comparative results and analyses are then presented.
The study aims to examine the impact of productivity in addition to the policy of increasing the foreign investors' ownership rate on the performance of businesses which were listed on Vietnam's stock exchange market from 2010 to 2017. With the database of 3.961 observations, the study employs a statistical method -multiple regression to estimate the relationship between labor productivity, foreign ownership as well as other firm-level characteristics and firm performance. Research findings show that increasing labor productivity and increasing foreign ownership rates help increase firm performance. In addition, except for financial leverage, variables such as liquidity and firm size have positive effects on firm performance measured by Tobin's Q. These findings have theoretical contributions and practical implications for managers, investors and government in Vietnam. Managers should pay attention to improving labor productivity through employing incentive mechanisms, building a good working environment, investing in technology, etc. in order to enhance the firm performance. Investors could utilize the labor productivity and foreign ownership indicators to select stocks of good companies for investment. For Vietnamese government, relaxing the limit of foreign ownership and accelerating the divesting of State capital in Stateowned enterprises could help increase the investment scale of foreign investors and resulting in positive effects on the firm performance.
To seek improved methods for the diagnosis of Pick's disease, we reviewed imaging studies of four women and two men (ages 48 to 65 years at onset) and psychometric testing of three of them with autopsy or biopsy-proved Pick's. The presence of Pick bodies was required for the diagnosis. Seven patients with biopsy-proved Alzheimer's disease served as a comparison group. In the Pick's patients, CT in five of six showed marked frontal pole or temporal pole atrophy, which clearly differed from the pattern of cerebral atrophy seen in the Alzheimer's patients. Psychometric testing showed performance patterns that tended to differ from those of the Alzheimer's patients in that recent memory was relatively preserved despite marked impairment of executive functions. The distinctive psychometric pattern in the Pick's patients was evanescent, however. Thus, there were imaging and psychometric findings of potential diagnostic value for Pick's disease, but, for different reasons, they were imperfect.
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