Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2020-09-28 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at the problem of low face recognition accuracy caused by poor image quality and loss of detailed information of face pictures obtained in security surveillance scene, this paper proposed a low-resolution face recognition algorithm based on super-resolution reconstruction. The algorithm included two sub-networks: super-resolution reconstruction and face recognition, which could respectively realize super-resolution reconstruction of low-resolution face image and extraction of face features. Firstly, the algorithm increased the number of feature maps before the activation function of super-resolution reconstruction sub-network to achieve wide activation and ensure effective transfer of information flow, so as to reconstruct high-resolution images containing more effective detailed information. Then, the algorithm combined image content loss and identity loss during training to retain more identity information while reconstructing image, which could make extracted face features more discriminative. Experimental results show that the algorithm improves accuracy of low-resolution face recognition and has better performance than traditional algorithms on surveillance face dataset QMUL-SurFace.
Subjects: Biology >> Bioengineering submitted time 2017-07-24 Cooperative journals: 《中国生物工程杂志》
Abstract： Phenol is a typical environmental pollutant. Biodegradation of phenol Phenol is a typical environmental pollutant. Chlorella sp. is potential strain for wastewater treatment because of its fast growth and strong resistance. Chlorella sp. could degrade phenol in industrial wastewater but oxidative stress induced by high concentration of phenol could cause oxidative damage in algal cells. Adaptive evolution was performed to improve the tolerance to phenol of Chlorella sp (L5). in previous study. The response mechanism of Chlorella sp. to oxidative stress induced by high concentration phenol was explored by de novo comparative transcriptomic analysis on genome scale. It was shown that the evolved strain could tolerate and degrade phenol was related to metabolic regulations in multiple pathways. The results of de novo comparative transcriptomic analysis showed that the genes related to signal transduction, ABC transporter and heat shock protein were significantly up-regulated at 500 mg/L phenol concentration compared to those in the original (L3) cells. Those genes in nitrogen metabolism and tricarboxylic acid cycle (TCA) were also upregulated. The evolved strain (L5) could reduce oxidation pressure induced by high concentration of phenol through the metabolic regulations in these metabolic pathways.
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