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1. chinaXiv:202004.00026 [pdf]

Learning an Adaptive Model for Extreme Low-light Raw Image Processing

付清旭; 遆晓光; 张雨1
Subjects: Computer Science >> Computer Application Technology

Low-light images suffer from severe noise and low illumination. Current deep learning models that are trained with real-world images have excellent noise reduction, but a ratio parameter must be chosen manually to complete the enhancement pipeline. In this work, we propose an adaptive low-light raw image enhancement network to avoid parameter-handcrafting and to improve image quality. The proposed method can be divided into two sub-models: Brightness Prediction (BP) and Exposure Shifting (ES). The former is designed to control the brightness of the resulting image by estimating a guideline exposure time t 1 . The latter learns to approximate an exposure-shifting operator ES, converting a low-light image with real exposure time t 0 to a noise-free image with guideline exposure time t 1 . Additionally, structural similarity (SSIM) loss and Image Enhancement Vector (IEV) are introduced to promote image quality, and a new Campus Image Dataset (CID) is proposed to overcome the limitations of the existing datasets and to supervise the training of the proposed model. In quantitative tests, it is shown that the proposed method has the lowest Noise Level Estimation (NLE) score compared with BM3D-based low-light algorithms, suggesting a superior denoising performance. Furthermore, those tests illustrate that the proposed method is able to adaptively control the global image brightness according to the content of the image scene. Lastly, the potential application in video processing is briefly discussed.

submitted time 2020-04-14 Hits2773Downloads398 Comment 0

2. chinaXiv:202004.00007 [pdf]


张锦; 田恬恬
Subjects: Computer Science >> Computer Application Technology


submitted time 2020-04-03 Hits4454Downloads395 Comment 0

3. chinaXiv:202002.00063 [pdf]

Perspectives on Active Preventive Measures of Wuhan People against COVID-19 Epidemic at Home: A Comparative Study

zhidong,Xue; Lei,Zhao; Tailang,Yin; Yan,Fu; Zehua,Lyu; yiping,Dang; Yujiang,Zeng; Silou,Huang; Bing,Qu; Hongya,Lyu; Chen,Huang; Zhiyou,Kong; Kepei,Xu; Feipeng,Zhou; Hexun,Dong; He,Hu; Jing,Tang; Senyuan,Xue; Zhixiang,Fang; Jinxiang,Lu
Subjects: Computer Science >> Computer Application Technology

Background:The COVID-19 Epidemic emerged in Wuhan, Hubei province, China. Ever since Wuhan lockdown on January 23rd, mass quarantines were exercised on Wuhan and other epidemic areas of China. We aimed to clarify how ordinary Wuhan people defend against COVID-19 epidemic at home through the Internet survey. Methods:A questionnaire survey, consisting of 30 questions were posted on the Internet. The following aspects were investigated: household preventive measures, self-monitoring of discomfort symptoms, immunity boosting against the epidemic, frequency and reasons of outgoing and mental status of the isolated people. The questionnaire was circulated on Wechat. We marked the areas based on the surveyed network IP addresses and categorized respondents into group A(Wuhan), B(Hubei Province excluding Wuhan ), C, and D based on the epidemic severity of their areas announced by at 17:00 on February 8, 2020. And a comparative study was conducted to illustrate how Wuhan people took the anti-COVID-19 strategies and how efficient these preventive measures were. Findings:In terms of discomfort symptoms, Wuhan, as Group A, had the lowest asymptomatic percentages (70.2%), compared to the average 78.5% (±7%). Considering the three typical symptoms for the COVID-19, i.e., cough, fever and fatigue, Wuhan (9.67%) greatly deviated from the average (7.68%). The fatigue was the most significant factor in the deviation, exceeding the average by 1.35%. In terms of household protection measures, most people or families were able to take effective protection measures with very low frequency of going out, but the percentage of those who took this practice was obviously smaller in Wuhan and Hubei Province. From the aspect of going out, most of the people in Wuhan only went out for shopping and work, with a small number of people for social gathering. In terms of immunity boosting, compared with Group C and D, it was relatively lower in Wuhan. Overall, most people chose to enhance their immunity through regular schedule, exercise, sufficient nutrition. Only 33.44% of people in Group A did not go out, and 59.97% had to go out for living supplies, which was the highest level among the four groups. However, the percentage of people who went out for work and unnecessary activities remains the lowest while 1% of the population went out for public welfare activities, higher than other groups. Worry about the family health topped all the parameters for all the groups. Among them, Wuhan has reached a maximum of 49.61%, higher than the average level of 36.62% (± 10.69%). Mental status except for feeling bored and lonely were the highest in Wuhan. Suggestions:When the epidemic prevention and control is still in a sticky state, and Wuhan started a stricter control measure, the closed management of communities, on Feb 11, 2020, it is expected that our findings can provide some insights into the current household preventive actions and arouse more attentions of the public to some ignored preventive precautions. Unnecessary outgoing should be strictly abandoned. Regular schedule, exercises and nutrition were the top 3 measures participants would choose to enhance their own immunity system. It seems that people in Wuhan would choose nutrition and regular scheduler rather than exercises as the primary immunity-boosting ways. Exercise should be especially advocated as an effective way to enhance the immunity system. In terms of physical condition, people in Wuhan should take more active measures when symptoms occurred. The mentality is also an important aspect requiring intensive attention with the conduct of stricter control management in Wuhan while the rest groups gradually resume to work and ordinary life.

submitted time 2020-02-24 Hits10120Downloads891 Comment 0

4. chinaXiv:202002.00015 [pdf]


王永桂; 李强; 余晴; 杨水化; 徐子怡; 谢天奕; 胡珊
Subjects: Computer Science >> Computer Application Technology

[目的]探究人工智能在新型冠状病毒(2019-nCoV)的诊断、治疗和控制中的应用场景和进展,以利用人工智能为新型冠状病毒肺炎的防控提供助力。 [方法]剖析新型冠状病毒肺炎防控的技术需求,从人工智能基因测序、辅助诊断、远程专家系统、药物筛查与研制等方面,分析当前的应用进展,挖掘应用的机遇。 [结果]中国是新型冠状病毒疫情最严重的国家,存在诸多的技术短板有待科技助力,AI能在疫情防控中发挥出重要的作用,但目前处于初步阶段,缺乏经过验证的落地成果;AI辅助诊断领域重复性研发较多,其他方面研究较少。 [局限]当前应用的数据大部分来自网站报道,如有更多的学术性成果,进展的分析将更全面。 [结论]需要加大投入和调控,在数据、算法和算力共享的基础上,各方面全面展开研发。

submitted time 2020-02-15 Hits17124Downloads1262 Comment 0

5. chinaXiv:202002.00006 [pdf]


杨晓飞; 徐暾; 贾鹏; 夏涵; 郭立; 叶凯
Subjects: Computer Science >> Computer Application Technology


submitted time 2020-02-03 Hits12090Downloads1134 Comment 0

6. chinaXiv:201911.00097 [pdf]

Review of Machine-Vision-Based Plant Detection Technologies for Robotic Weeding

Li,Nan; Zhang, Xiaoguang ; Zhang, Chunlong; Ge, Luzhen; He, Yong; Wu,Xinyu
Subjects: Computer Science >> Computer Application Technology

Controlling weeds with reduced reliance on herbicides is one of the main challenges to move toward a more sustainable agriculture. Robotic weeding is a thought to be a viable way to reduce the environmental loading of agrochemicals while keeping the operation efficiency high. One of the key technologies for performing robotic weeding is automatic detection of crops and weeds in fields. This paper presents an overview on various methods for detecting plants based on machine vision, mainly concentrating on two main challenges: dealing with changing light and crop/weed discrimination. To overcome the first challenge, both physical and algorithmic methods have been proposed. Physical methods can result in a more cumbersome machine while algorithmic methods are less robust. For crop/weed discrimination, deep-learning-based methods have shown obvious advantages over traditional methods based on hand-crafted features. However, traditional methods still hold some merits that can be leveraged to deep-learning-based methods. With the fast development of hardware technologies, researchers should take full advantage of advanced hardware to ease the algorithm design. In the future, the identification of crops and weeds can be more accurate and fine-grained with the support of online databases and computing resources based on the advances in artificial intelligence and communication technologies.

submitted time 2019-11-23 Hits12088Downloads735 Comment 0

7. chinaXiv:201905.00052 [pdf]


Zhiyang Xiang
Subjects: Computer Science >> Computer Application Technology


submitted time 2019-05-05 Hits14816Downloads542 Comment 0

8. chinaXiv:201811.00043 [pdf]


张佳影; 王祺; 张知行; 阮彤; 张欢欢; 何萍
Comment:CCIR2018 Accepted Paper
Subjects: Computer Science >> Computer Application Technology


submitted time 2018-11-13 Hits1772Downloads659 Comment 0

9. chinaXiv:201801.00508 [pdf]


陈永志; 韩守东; 黄飘; 陈阳
Subjects: Computer Science >> Computer Application Technology


submitted time 2018-01-23 Hits1758Downloads930 Comment 0

10. chinaXiv:201706.00748 [pdf]


闫昱; 李皓辰; 王燕飞; 经玲
Subjects: Computer Science >> Computer Application Technology


submitted time 2017-06-22 Hits16274Downloads2240 Comment 0

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