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81.
The application of deep learning in the field of object detection has
experienced much progress. However, due to the domain shift problem, applying an
off-the-shelf detector to another domain leads to a significant performance drop. A
large number of ground truth labels are required when using another domain to train
models, demanding a large amount of human and financial resources. In order to avoid
excessive resource requirements and performance drop caused by domain shift, this
paper proposes a new domain adaptive approach to cross-domain vehicle detection. Our
approach improves the cross-domain vehicle detection model from image space and
feature space. We employ objectives of the generative adversarial network and cycle
consistency loss for image style transfer in image space. For feature space, we align
feature distributions between the source domain and the target domain to improve the
detection accuracy. Experiments are carried out using the method with two different
datasets, proving that this technique effectively improves the accuracy of vehicle
detection in the target domain. 相似文献
82.
Mani Balamurugan Hui‐Yun Jeong Venkata Surya Kumar Choutipalli Jung Sug Hong Hongmin Seo Natarajan Saravanan Jun Ho Jang Kang‐Gyu Lee Yoon Ho Lee Sang Won Im Venkatesan Subramanian Sun Hee Kim Ki Tae Nam 《Small (Weinheim an der Bergstrasse, Germany)》2020,16(25)
The electrochemical reduction of carbon dioxide (CO2) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO2 to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO2 to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO2 in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions. 相似文献
83.
Ohsaki Makoto Fujiwara Jun Takeda Fumiyoshi 《International Journal of Mechanics and Materials in Design》2020,16(4):883-896
International Journal of Mechanics and Materials in Design - A simple iterative method is presented for cutting pattern optimization of frame-supported and pneumatic membrane structures for... 相似文献
84.
85.
Wan Huan Wang Hui Scotney Bryan Liu Jun Ng Wing W. Y. 《Multimedia Tools and Applications》2020,79(39-40):29327-29352
Multimedia Tools and Applications - In many real-world classification problems there exist multiple subclasses (or clusters) within a class; in other words, the underlying data distribution is... 相似文献
86.
Creating the brain and interacting with the brain: an integrated approach to understanding the brain
In the past two decades, brain science and robotics have made gigantic advances in their own fields, and their interactions have generated several interdisciplinary research fields. First, in the ‘understanding the brain by creating the brain’ approach, computational neuroscience models have been applied to many robotics problems. Second, such brain-motivated fields as cognitive robotics and developmental robotics have emerged as interdisciplinary areas among robotics, neuroscience and cognitive science with special emphasis on humanoid robots. Third, in brain–machine interface research, a brain and a robot are mutually connected within a closed loop. In this paper, we review the theoretical backgrounds of these three interdisciplinary fields and their recent progress. Then, we introduce recent efforts to reintegrate these research fields into a coherent perspective and propose a new direction that integrates brain science and robotics where the decoding of information from the brain, robot control based on the decoded information and multimodal feedback to the brain from the robot are carried out in real time and in a closed loop. 相似文献
87.
88.
Yejun Wu Bowen Yan Juan Zhou Huizhang Lian Xiaojun Yu Jianxin Zhao Hao Zhang Wei Chen Daming Fan 《Journal of food science》2020,85(10):3282-3292
89.
Hechun Cao Hui Zheng Lining Fan Zifeng Cheng Jianwei Zhou Qiong Wu Peng Zheng Liang Zheng Yang Zhang 《International Journal of Applied Ceramic Technology》2020,17(2):813-822
In this study, yttrium iron garnet co-doped with Zn and Zr atoms with a chemical formula Y3ZnxZrxFe(5−2x)O12 (x = 0.0-0.3) has been successfully prepared by the solid-state reaction method. The effects of doping concentration on the microstructure, crystal structure, magnetic properties, and dielectric properties of Y3ZnxZrxFe(5−2x)O12 were investigated. The microstructure analysis indicates that co-doping of YIG with Zn and Zr can effectively reduce the grain size of the ceramic. The crystal structure results reveal that the doping concentration of Zn–Zr has substantial influence on the lattice parameters of YIG, such as, increases the lattice constant, crystal cell size, and interplanar spacing. However, the second phase of ZrO2 appears once x ≥ 0.15. Additionally, the dielectric properties of YIG ferrite can be regulated using this Zn–Zr co-doping method. Zn–Zr co-doping can improve the dielectric stability and reduce the dielectric loss at high temperature. The magnetization measurement shows that the saturation magnetization is stabilized at x < 0.15, and the magnetic loss is decreased with the increase in the doping concentration. Overall, the findings show that the ceramic with x = 0.1 exhibits better properties included high saturation magnetization (24.607 emu/g), low magnetic loss (0.0025 @ 1 MHz), and relatively low dielectric loss (496 @ 400°C). 相似文献
90.