Bypass Enhancement RGB Stream Model for Pedestrian Action Recognition of Autonomous Vehicles

Pedestrian action recognition and intention prediction is one of the core issues in the field of autonomous driving. In this research field, action recognition is one of the key technologies. A large number of scholars have done a lot of work to im-prove the accuracy of the algorithm for the task. However, there are relatively few studies and improvements in the computational complexity of algorithms and sys-tem real-time. In the autonomous driving application scenario, the real-time per-formance and ultra-low latency of the algorithm are extremely important evalua-tion indicators, which are directly related to the availability and safety of the au-tonomous driving system. To this end, we construct a bypass enhanced RGB flow model, which combines the previous two-branch algorithm to extract RGB feature information and optical flow feature information respectively. In the train-ing phase, the two branches are merged by distillation method, and the bypass enhancement is combined in the inference phase to ensure accuracy. The real-time behavior of the behavior recognition algorithm is significantly improved on the premise that the accuracy does not decrease. Experiments confirm the superiority and effectiveness of our algorithm.Comment: Accepted to ACPR 2019 - Workshop on Computer Vision for Modern Vehicle

Hydrogen and nitrogen codoping of anatase TiO₂ for efficiency enhancement in organic solar cells

TiO2 has high chemical stability, strong catalytic activity and is an electron transport material in organic solar cells. However, the presence of trap states near the band edges of TiO2 arising from defects at grain boundaries significantly affects the efficiency of organic solar cells. To become an efficient electron transport material for organic photovoltaics and related devices, such as perovskite solar cells and photocatalytic devices, it is important to tailor its band edges via doping. Nitrogen p-type doping has attracted considerable attention in enhancing the photocatalytic efficiency of TiO2 under visible light irradiation while hydrogen n-type doping increases its electron conductivity. DFT calculations in TiO2 provide evidence that nitrogen and hydrogen can be incorporated in interstitial sites and possibly form NiHi, NiHO and NTiHi defects. The experimental results indicate that NiHi defects are most likely formed and these defects do not introduce deep level states. Furthermore, we show that the efficiency of P3HT:IC60BA-based organic photovoltaic devices is enhanced when using hydrogen-doping and nitrogen/hydrogen codoping of TiO2, both boosting the material n-type conductivity, with maximum power conversion efficiency reaching values of 6.51% and 6.58%, respectively, which are much higher than those of the cells with the as-deposited (4.87%) and nitrogen-doped TiO2 (4.46%).</p