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1. chinaXiv:201911.00097 [pdf]

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

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 Hits1145Downloads74 Comment 0

2. chinaXiv:201910.00076 [pdf]

Masked Sentence Model based on BERT for Move Recognition in Medical Scientific Abstracts

Yu, Gaihong; Zhang, Zhixiong; Liu, Huan ; Ding, Liangping
Subjects: Computer Science >> Natural Language Understanding and Machine Translation

Purpose: Move recognition in scientific abstracts is an NLP task of classifying sentences of the abstracts into different types of language unit. To improve the performance of move recognition in scientific abstracts, a novel model of move recognition is proposed that outperforms BERT-Base method. Design: Prevalent models based on BERT for sentence classification often classify sentences without considering the context of the sentences. In this paper, inspired by the BERT's Masked Language Model (MLM), we propose a novel model called Masked Sentence Model that integrates the content and contextual information of the sentences in move recognition. Experiments are conducted on the benchmark dataset PubMed 20K RCT in three steps. And then compare our model with HSLN-RNN, BERT-Base and SciBERT using the same dataset. Findings: Compared with BERT-Base and SciBERT model, the F1 score of our model outperforms them by 4.96% and 4.34% respectively, which shows the feasibility and effectiveness of the novel model and the result of our model comes closest to the state-of-the-art results of HSLN-RNN at present. Research Limitations: The sequential features of move labels are not considered, which might be one of the reasons why HSLN-RNN has better performance. And our model is restricted to dealing with bio-medical English literature because we use dataset from PubMed which is a typical bio-medical database to fine-tune our model. Practical implications: The proposed model is better and simpler in identifying move structure in scientific abstracts, and is worthy for text classification experiments to capture contextual features of sentences. Originality: The study proposes a Masked Sentence Model based on BERT which takes account of the contextual features of the sentences in abstracts in a new way. And the performance of this classification model is significantly improved by rebuilding the input layer without changing the structure of neural networks.

submitted time 2019-10-29 Hits5326Downloads147 Comment 0

3. chinaXiv:201905.00013 [pdf]

人工智能基础理论的过去、现在及发展趋势思考

辛欣; 郭平
Subjects: Information Science and Systems Science >> Other Disciplines of Information Science and Systems Science

本文回顾了人工智能的发展历史,分析了当前国内外研究现状,指出了目前以深度学习为代表的人工智能基础研究困境。包括可解释性神经网络模型问题、网络模型的结构设计问题、小样本学习问题等。给出了今后人工智能发展趋势,认为基于统计物理思维构建协同学习系统可能是通往通用人工智能的路线之一。

submitted time 2019-10-16 Hits1776Downloads571 Comment 0

4. chinaXiv:201910.00073 [pdf]

智慧中医:肺癌处方智能生成模型

阮春阳
Subjects: Computer Science >> Natural Language Understanding and Machine Translation

本文在中医知识挖掘工作积累的基础上,对中医肺癌临床处方数据调研分析,针对其数据特点,构建深度学习模型挖掘处方中症状和中药之间隐藏关系等规律,在此过程中与医生沟通验证模型的准确性,最终实现处方智能生成并达到较高的临床有效性,辅助医生诊断,提升临床效率,推动临床诊断创新发展。

submitted time 2019-10-15 Hits126Downloads75 Comment 0

5. chinaXiv:201909.00203 [pdf]

基于脑结构像的精神分裂症机器学习分类研究

郑泓; 蒲城城; 王毅; 陈楚侨
Subjects: Psychology >> Medical Psychology

将机器学习应用于精神疾患的临床和基础研究是近年来的趋势。研究者将机器学习应用于精神分裂症患者及高危人群的T1加权像和弥散张量成像的脑影像数据中,为了解疾病的生理病理学机制提供帮助。回顾以往研究发现额叶及颞叶的脑结构特征具有较高的区分能力,行为数据和脑影像数据结合的分类效果优于单模态数据。现阶段研究存在样本量不足和泛化能力欠缺的局限,未来研究应注意扩大样本量、制定标准化的分类方法,从而进一步探究机器学习在精神疾患中的作用。

submitted time 2019-09-28 Hits874Downloads172 Comment 0

6. chinaXiv:201905.00012 [pdf]

Transfer Learning for Scientific Data Chain Extraction in Small Chemical Corpus with BERT-CRF Model

Na Pang; Li Qian; Weimin Lyu; Jin-Dong Yang
Subjects: Computer Science >> Natural Language Understanding and Machine Translation

Abstract. Computational chemistry develops fast in recent years due to the rapid growth and breakthroughs in AI. Thanks for the progress in natural language processing, researchers can extract more fine-grained knowledge in publications to stimulate the development in computational chemistry. While the works and corpora in chemical entity extraction have been restricted in the biomedicine or life science field instead of the chemistry field, we build a new corpus in chemical bond field anno- tated for 7 types of entities: compound, solvent, method, bond, reaction, pKa and pKa value. This paper presents a novel BERT-CRF model to build scientific chemical data chains by extracting 7 chemical entities and relations from publications. And we propose a joint model to ex- tract the entities and relations simultaneously. Experimental results on our Chemical Special Corpus demonstrate that we achieve state-of-art and competitive NER performance.

submitted time 2019-05-12 Hits2054Downloads311 Comment 0

7. chinaXiv:201905.00014 [pdf]

一种基于DTMF信号的智能手机外部攻击方法

申兴发; 杨健; 冉德纲
Subjects: Computer Science >> Integration Theory of Computer Science

传统的针对智能手机内部攻击的方式容易被用户察觉及预防。作为一种常见的音频信号,DTMF信号在手机通信中具有非常重要的地位,但也面临严峻的安全风险。提出了一种基于DTMF信号的智能手机外部攻击方法,可以在用户不被察觉,且与用户手机无交互情况下进行有效攻击。首先,该方法对用户某些重要按键操作进行录音;然后对录音数据在时域上进行双阈值的端点检测,提取信号的有效区域;再将有效区域通过Goertzel算法转换到频域进行数字分类;最后,通过比照DTMF编码表得到用户所有按键数据。实验结果表明,该方法在10 db信噪比,且与用户手机无交互的条件下能破解80%以上的按键数据。

submitted time 2019-05-10 From cooperative journals:《计算机应用研究》 Hits1605Downloads362 Comment 0

8. chinaXiv:201905.00015 [pdf]

抗密钥泄露的在线/离线身份基加密机制

张秀洁
Subjects: Computer Science >> Integration Theory of Computer Science

在线离线身份基加密(IBOOE)方案是一种具有高效的密钥生成和加密算法的密码方案。然而,目前已有的IBOOE方案无法抵抗边信道攻击,它将引起密码系统秘密信息泄露问题。新方案通过将随机提取器嵌入在线加密算法来隐藏私钥泄露和密文之间的关系,提出首个有界泄露模型下安全的IBOOE方案;新方案基于合数阶双线性群上的三个静态假设,利用双系统加密技术在标准模型下抵抗选择明文攻击达到完全安全性和泄露弹性。此外,与传统的IBOOE方案相比较,新方案特别适用于敏感数据存储且资源受限的场景。

submitted time 2019-05-10 From cooperative journals:《计算机应用研究》 Hits1395Downloads285 Comment 0

9. chinaXiv:201905.00016 [pdf]

基于PN码随机化的MSAC攻击防御方法

许新忠; 张连成; 燕菊维
Subjects: Computer Science >> Integration Theory of Computer Science

基于流速率的直序扩频(DSSS)流水印技术在嵌入多比特的水印信息时采用同一伪随机(PN)码,使得已标记数据流具有自相似性,均方自相关(MSAC)攻击通过单条已标记数据流就可检测DSSS流水印的存在性,严重破坏了DSSS流水印的隐蔽性。PN码正交化方法虽可消除已标记数据流的自相关性,进而抵御MSAC攻击的检测,但正交PN码难以生成,应用范围受限。为此,提出基于PN码随机化的MSAC攻击防御方法,在向目标数据流嵌入每个水印位时均采用随机选择的不同长度的PN码进行扩展,使得已嵌入DSSS流水印的数据流速率的均方自相关不再呈现周期性峰值,进而可在MSAC攻击面前保持隐蔽性。理论分析与实验结果表明,基于PN码随机化的MSAC攻击防御方法可有效抵御MSAC攻击的检测,且所采用的PN码易于生成,便于部署和应用。

submitted time 2019-05-10 From cooperative journals:《计算机应用研究》 Hits1746Downloads600 Comment 0

10. chinaXiv:201905.00017 [pdf]

考虑量化不匹配问题的信息物理系统的安全控制

贾欣婷; 郑柏超; 裴斌
Subjects: Computer Science >> Integration Theory of Computer Science

针对一类包含执行器攻击、外部干扰和编码器/解码器不匹配的信息物理系统(cyber-physical systems,CPS),设计一种新型鲁棒控制器确保其安全稳定运行。控制器线性部分的增益由优化H2性能的线性矩阵不等式给出;控制器的非线性结构包含两部分,一部分用于消除外部干扰、量化误差,另一部分利用对未知执行器攻击参数的自适应估计来实现对攻击的补偿。最后,仿真算例结果表明控制器能保证闭环系统的一致最终有界性,说明了所提方法的有效性。

submitted time 2019-05-10 From cooperative journals:《计算机应用研究》 Hits906Downloads271 Comment 0

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