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Pedestrian detection and re-identification technology is a research hotspot in the field of computer vision. This technology currently has issues such as insufficient pedestrian expression ability, occlusion, diverse pedestrian attitude, and difficulty of small-scale pedestrian detection. In this paper, we proposed an end-to-end pedestrian detection and re-identification model in real scenes, which can effectively solve these problems. In our model, the original images are processed with a non-overlapped image blocking data augmentation method, and then input them into the YOLOv3 detector to obtain the object position information. LCNN-based pedestrian re-identification model is used to extract the features of the object. Furthermore, the eigenvectors of the object and the detected pedestrians are calculated, and the similarity between them are used to determine whether they can be marked as target pedestrians. Our method is lightweight and end-to-end, which can be applied to the real scenes.

High quality blue emitting quantum dots (QDs) are regarded as promising nanomaterials for lasers, photovoltaic cells and displays. However, few reports realize high photoluminescence quantum yield (PL QY), narrow emission band width and pure blue emitting (450∼460 nm) simultaneously. Herein we propose a facile one-step synthesis of thick shell blue emitting CdZnS/ZnS QDs. ZnS shell was overcoated on the prepared cores by directly introducing zinc oleate/S TBP solution (zinc oleate powder and S dissolved in TBP) into mixture without any purification steps and the thickness of ZnS shell was controlled by adjusting the adding amount of zinc oleate/S TBP solution. The optimal QDs with ten monolayers of ZnS shell exhibit pure blue light (∼455 nm) with narrow line width (full width half maximum, FWHM 17.2 nm) and high photoluminescent quantum yield (QY) (92%). Due to the thick ZnS shell, nonradiative recombination of the QD solids is suppressed efficiently.