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575 results on '"Cheng, Shanshan"'

17. Robust Lane Marking Detection Algorithm Using Drivable Area Segmentation and Extended SLT

Author

Ozgunalp, Umar, Fan, Rui, Cheng, Shanshan, Sun, Yuxiang, Zuo, Weixun, Zhu, Yilong, Xue, Bohuan, Zheng, Linwei, Liang, Qing, and Liu, Ming

Subjects
Computer Science - Robotics, Computer Science - Computer Vision and Pattern Recognition
Abstract

In this paper, a robust lane detection algorithm is proposed, where the vertical road profile of the road is estimated using dynamic programming from the v-disparity map and, based on the estimated profile, the road area is segmented. Since the lane markings are on the road area and any feature point above the ground will be a noise source for the lane detection, a mask is created for the road area to remove some of the noise for lane detection. The estimated mask is multiplied by the lane feature map in a bird's eye view (BEV). The lane feature points are extracted by using an extended version of symmetrical local threshold (SLT), which not only considers dark light dark transition (DLD) of the lane markings, like (SLT), but also considers parallelism on the lane marking borders. The segmentation then uses only the feature points that are on the road area. A maximum of two linear lane markings are detected using an efficient 1D Hough transform. Then, the detected linear lane markings are used to create a region of interest (ROI) for parabolic lane detection. Finally, based on the estimated region of interest, parabolic lane models are fitted using robust fitting. Due to the robust lane feature extraction and road area segmentation, the proposed algorithm robustly detects lane markings and achieves lane marking detection with an accuracy of 91% when tested on a sequence from the KITTI dataset., Comment: 4 pages, 3 figures, 2019 IEEE International Conference on Robotics and Biomimetics

Published
2019

26. Road Crack Detection Using Deep Convolutional Neural Network and Adaptive Thresholding

Author

Fan, Rui, Bocus, Mohammud Junaid, Zhu, Yilong, Jiao, Jianhao, Wang, Li, Ma, Fulong, Cheng, Shanshan, and Liu, Ming

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Crack is one of the most common road distresses which may pose road safety hazards. Generally, crack detection is performed by either certified inspectors or structural engineers. This task is, however, time-consuming, subjective and labor-intensive. In this paper, we propose a novel road crack detection algorithm based on deep learning and adaptive image segmentation. Firstly, a deep convolutional neural network is trained to determine whether an image contains cracks or not. The images containing cracks are then smoothed using bilateral filtering, which greatly minimizes the number of noisy pixels. Finally, we utilize an adaptive thresholding method to extract the cracks from road surface. The experimental results illustrate that our network can classify images with an accuracy of 99.92%, and the cracks can be successfully extracted from the images using our proposed thresholding algorithm., Comment: 6 pages, 8 figures, 2019 IEEE Intelligent Vehicles Symposium

Published
2019

31. Erbium‐Induced Boost in Self‐Trapped Exciton Emission of Double Perovskites for Highly Sensitive Multimodal and Multiplexed Optical Thermography

Author

Li, Gaoqiang, primary, Cheng, Shanshan, additional, Chen, Xu, additional, Wang, Meng, additional, Zhang, Fei, additional, Chen, Zhipeng, additional, Liang, Yurun, additional, Li, Xu, additional, Ji, Huifang, additional, Yang, Dongwen, additional, Han, Yanbing, additional, Li, Xinjian, additional, Xu, Wen, additional, Jia, Mochen, additional, Shan, Chongxin, additional, and Shi, Zhifeng, additional

Published
2024
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41. CSGALNACT2 restricts ovarian cancer migration and invasion by modulating MAPK/ERK pathway through DUSP1

Author

Ma, Mingjun, primary, Wang, Chao, additional, Wu, Meixuan, additional, Gu, Sijia, additional, Yang, Jiani, additional, Zhang, Yue, additional, Cheng, Shanshan, additional, Xu, Shilin, additional, Zhang, Minghai, additional, Wu, Yongsong, additional, Zhao, Yaqian, additional, Tian, Xiu, additional, Voon, Dominic Chih-Cheng, additional, Takahashi, Chiaki, additional, Sheng, Jindan, additional, and Wang, Yu, additional

Published
2023
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46. Optimal Scheduling Framework of Integrated Energy System Based on Carbon Emission in Electricity Spot Market.

Author

Cai, Xiangyu, Wang, Haixin, Dong, Jian, Lu, Xinyi, Yang, Zihao, Cheng, Shanshan, Ma, Yiming, Yang, Junyou, and Chen, Zhe

Subjects
CARBON emissions, ELECTRICITY markets, LAGRANGE multiplier, EMISSIONS trading, LEAD, CARBON dioxide
Abstract

Micro coal-fired units (MCFU) and combined heat and power plants (CHP) in integrated energy system (IES) will emit a large amount of carbon dioxide when providing loads to customers, which will lead to higher operating costs of IES. To solve this challenge, an optimal dispatch model of power-to-gas (P2G) and methane reactor (MR) considering the reward and punishment costs based on carbon emission trading mechanism is proposed, to reduce carbon emissions of IES and enhance the accommodation of renewable energy (RE). Subsequently, considering the uncertainty of RE, a combination optimization method for MCFU and CHP units is developed based on the Lagrange multiplier method. Finally, considering the mechanism of electricity spot market (ESM), a transaction strategy for IES participating in ESM is proposed to further enhance the accommodation of RE. The effectiveness of the proposed framework is demonstrated through simulations. [ABSTRACT FROM AUTHOR]

Published
2024
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48. Trans-ethnic genome-wide association study of severe COVID-19

Author

Wu, Peng, Ding, Lin, Li, Xiaodong, Liu, Siyang, Cheng, Fanjun, He, Qing, Xiao, Mingzhong, Wu, Ping, Hou, Hongyan, Jiang, Minghui, Long, Pinpin, Wang, Hao, Liu, Linlin, Qu, Minghan, Shi, Xian, Jiang, Qin, Mo, Tingting, Ding, Wencheng, Fu, Yu, Han, Shi, Huo, Xixiang, Zeng, Yingchun, Zhou, Yana, Zhang, Qing, Ke, Jia, Xu, Xi, Ni, Wei, Shao, Zuoyu, Wang, Jingzhi, Liu, Panhong, Li, Zilong, Jin, Yan, Zheng, Fang, Wang, Fang, Liu, Lei, Li, Wending, Liu, Kang, Peng, Rong, Xu, Xuedan, Lin, Yuhui, Gao, Hui, Shi, Limei, Geng, Ziyue, Mu, Xuanwen, Yan, Yu, Wang, Kai, Wu, Degang, Hao, Xingjie, Cheng, Shanshan, Qiu, Gaokun, Guo, Huan, Li, Kezhen, Chen, Gang, Sun, Ziyong, Lin, Xihong, Jin, Xin, Wang, Feng, Sun, Chaoyang, and Wang, Chaolong

Published
2021
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