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1.
Small object detection is challenging and far from satisfactory. Most general object detectors suffer from two critical issues with small objects: (1) Feature extractor based on classification network cannot express the characteristics of small objects reasonably due to insufficient appearance information of targets and a large amount of background interference around them. (2) The detector requires a much higher location accuracy for small objects than for general objects. This paper proposes an effective and efficient small object detector YOLSO to address the above problems. For feature representation, we analyze the drawbacks in previous backbones and present a Half-Space Shortcut(HSSC) module to build a background-aware backbone. Furthermore, a coarse-to-fine Feature Pyramid Enhancement(FPE) module is introduced for layer-wise aggregation at a granular level to enhance the semantic discriminability. For loss function, we propose an exponential L1 loss to promote the convergence of regression, and a focal IOU loss to focus on prime samples with high classification confidence and high IOU. Both of them significantly improves the location accuracy of small objects. The proposed YOLSO sets state-of-the-art results on two typical small object datasets, MOCOD and VeDAI, at a speed of over 200 FPS. In the meantime, it also outperforms the baseline YOLOv3 by a wide margin on the common COCO dataset. 相似文献
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电路板在我们的日常生活中非常常见,这就使得印刷电路板的缺陷检测显得尤为重要。AOI作为新兴的检测PCB板缺陷的系统,在生产实际中正在被大家熟知并且应用。相较于传统的检测方式,AOI系统比较灵活,无论是在检测时间还是系统运算上,或者是对相关技术人员的要求相较于传统方式都比较有优势,本文就AOI系统在实际中的应用展开讨论,分析并且介绍了在实际应用中的具体细则。 相似文献
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Smartphones are being used and relied on by people more than ever before. The open connectivity brings with it great convenience and leads to a variety of risks that cannot be overlooked. Smartphone vendors, security policy designers, and security application providers have put a variety of practical efforts to secure smartphones, and researchers have conducted extensive research on threat sources, security techniques, and user security behaviors. Regrettably, smartphone users do not pay enough attention to mobile security, making many efforts futile. This study identifies this gap between technology affordance and user requirements, and attempts to investigate the asymmetric perceptions toward security features between developers and users, between users and users, as well as between different security features. These asymmetric perceptions include perceptions of quality, perceptions of importance, and perceptions of satisfaction. After scoping the range of smartphone security features, this study conducts an improved Kano-based method and exhaustively analyzes the 245 collected samples using correspondence analysis and importance satisfaction analysis. The 14 security features of the smartphone are divided into four Kano quality types and the perceived quality differences between developers and users are compared. Correspondence analysis is utilized to capture the relationship between the perceived importance of security features across different groups of respondents, and results of importance-satisfaction analysis provide the basis for the developmental path and resource reallocation strategy of security features. This article offers new insights for researchers as well as practitioners of smartphone security. 相似文献
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Xiaopo Wu Yangming Shi Weibo Meng Xiaofei Ma Nian Fang 《International Journal of Satellite Communications and Networking》2019,37(3):283-291
Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(±1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military. 相似文献
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Motor Imagery Electroencephalography (MI-EEG) has shown good prospects in neurorehabilitation, and the entropy-based nonlinear dynamic methods have been successfully applied to feature extraction of MI-EEG. Especially based on Multiscale Fuzzy Entropy (MFE), the fuzzy entropies of the τ coarse-grained sequences in τ scale are calculated and averaged to develop the Composite MFE (CMFE) with more feature information. However, the coarse-grained process fails to match the nonstationary characteristic of MI-EEG by a mean filtering algorithm. In this paper, CMFE is improved by assigning the different weight factors to the different sample points in the coarse-grained process, i.e., using the weighted mean filters instead of the original mean filters, which is conductive to signal filtering and feature extraction, and the resulting personalized Weighted CMFE (WCMFE) is more suitable to represent the nonstationary MI-EEG for different subjects. All the WCMFEs of multi-channel MI-EEG are fused in serial to construct the feature vector, which is evaluated by a back-propagation neural network. Based on a public dataset, extensive experiments are conducted, yielding a relatively higher classification accuracy by WCMFE, and the statistical significance is examined by two-sample t-test. The results suggest that WCMFE is superior to the other entropy-based and traditional feature extraction methods. 相似文献
6.
Hejia Hu Linlin Wu Mei Li Cun Xue Guangcheng Wang Siying Chen Yong Huang Lin Zheng Aimin Wang Yueting Li Zipeng Gong 《Biomedical chromatography : BMC》2020,34(1):e4714
Eucommia ulmoides Oliv. (E. ulmoides) is a valuable and nourishing medicinal herb in China that has been used in the treatment of hypertension. Given the fact that most traditional Chinese medicine is mainly used to treat disease, investigating the pharmacokinetics of traditional Chinese medicines in the pathological state is more useful than that in the normal state. However, the differences in the absorption kinetics of active ingredients of E. ulmoides extract between pathological and physiological conditions have not been reported. Therefore, in this study, the rat intestinal in situ circulatory perfusion model was used to investigate the differences in absorption kinetics of seven active ingredients of E. ulmoides extract in normal and spontaneously hypertensive rats, namely, genipinic acid, protocatechuic acid, neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, (+)-pinoresinol di-O-β-D -glucopyranoside and (+)-pinoresinol 4′-O-β-D -glucopyranoside. Our results indicate that the pathological state of spontaneous hypertension may change the absorption of active components of E. ulmoides extracts, and these findings may provide a reference for improving the rational use of E. ulmoides in the clinic. 相似文献
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实验确定了自行研制的L波段三维电子自旋共振成像(3D-ESRI)系统的检测灵敏度及成像分辨率指标. 用Tempo水溶液模型测量灵敏度结果表明: 样品体积为10 mm, 高30 mm,测量浓度1×10-4 mol/L水溶液的信噪比为S/N=4∶1;加梯度磁场后,样品浓度需>5×10-4 mol/L,样品体积为19 mm, 高30 mm时,获得的投影谱的信噪比可满足图像重建的需要. 用DPPH固体样品确定的成像分辨率结果<1 mm. 文中还对ESRI系统的
各项总体性能做了归纳总结. 相似文献
各项总体性能做了归纳总结. 相似文献
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