Yang Song

TL;DR: A unified implementation of the Faster R-CNN, R-FCN and SSD systems is presented and the speed/accuracy trade-off curve created by using alternative feature extractors and varying other critical parameters such as image size within each of these meta-architectures is traced out.

TL;DR: This work designs a re-weighting scheme that uses the effective number of samples for each class to re-balance the loss, thereby yielding a class-balanced loss and introduces a novel theoretical framework to measure data overlap by associating with each sample a small neighboring region rather than a single point.

TL;DR: The results suggested that the novel Mg-Zn binary alloy had good biocompatibility in vivo, and no adverse effects of hydrogen generated by degradation had been observed and also no negative effects caused by the release of zinc were detected.

TL;DR: A deep ranking model that employs deep learning techniques to learn similarity metric directly from images has higher learning capability than models based on hand-crafted features and deep classification models.

TL;DR: Zhang et al. as mentioned in this paper proposed a deep ranking model that employs deep learning techniques to learn similarity metric directly from images, which has higher learning capability than models based on hand-crafted features.