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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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诱导式卫星欺骗干扰可诱导航空器逐渐偏离预定航迹,难以被发现,因此及时有效地检测干扰是飞行安全的保障。在现有紧组合导航体制基础上,设计了一种基于误差估值累加开环校正的紧组合导航结构,并证明了其性能与传统闭环校正紧组合导航性能等效。在此结构中,将紧组合导航系统与自适应序贯概率比检测方法结合,提出了一种基于误差估值累加开环校正的诱导式欺骗检测方法,融合紧组合导航信息与其他不受欺骗影响的导航信息,构建欺骗检测统计量进行诱导式欺骗检测。仿真结果表明,开环校正结构可避免随时间累加的惯性导航系统误差所导致的组合导航滤波器发散问题,同时欺骗检测方法可进一步提高算法对“最坏”情形下微小诱导式欺骗的检测效果。 相似文献
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《International Journal of Hydrogen Energy》2022,47(100):41994-42000
Hydrogen technology is widely considered a novel clean energy source, and electrolysis is an effective method for hydrogen evolution. Therefore, efficient hydrogen evolution reaction (HER) catalysts are urgently needed to replace precious metal catalysts and meet ecological and environmental protection standards. Herein, Ni–Mn–P electrocatalysts are synthesized using facile electrodeposition technology. The influence of the Mn addition on the catalytic behavior is studied by the comprehensive analysis of catalytic performance and morphology of the catalysts. Among them, the Ni–Mn–P0.01 catalyst exhibits small coral-like structures, greatly improving the adsorption and desorption of hydrogen ions and reducing the overpotential hydrogen evolution. Consequently, overpotential at 10 mA cm?2 electric current density is 113 mV, and the value of the Tafel slope achieves 74 mV/dec. Furthermore, the Ni–Mn–P catalyst shows long-time (20 h) stability at current densities of 10 and 60 mA/cm2. The results confirm that the synergistic effect of Ni, Mn, and P accelerates the electrochemical reaction. Meanwhile, the addition of manganese element can change the micromorphology of the catalyst, thereby exposing more active sites to participate in the reaction, enhancing water ionization, improving the catalytic performance. This study opens a new way toward improving the activity of the catalyst by adjusting Mn concentration during the electrodeposition process. 相似文献
6.
In actual engineering scenarios, limited fault data leads to insufficient model training and over-fitting, which negatively affects the diagnostic performance of intelligent diagnostic models. To solve the problem, this paper proposes a variational information constrained generative adversarial network (VICGAN) for effective machine fault diagnosis. Firstly, by incorporating the encoder into the discriminator to map the deep features, an improved generative adversarial network with stronger data synthesis capability is established. Secondly, to promote the stable training of the model and guarantee better convergence, a variational information constraint technique is utilized, which constrains the input signals and deep features of the discriminator using the information bottleneck method. In addition, a representation matching module is added to impose restrictions on the generator, avoiding the mode collapse problem and boosting the sample diversity. Two rolling bearing datasets are utilized to verify the effectiveness and stability of the presented network, which demonstrates that the presented network has an admirable ability in processing fault diagnosis with few samples, and performs better than state-of-the-art approaches. 相似文献
7.
Accurate and timely network traffic measurement is essential for network status monitoring, network fault analysis, network intrusion detection, and network security management. With the rapid development of the network, massive network traffic brings severe challenges to network traffic measurement. However, existing measurement methods suffer from many limitations for effectively recording and accurately analyzing big-volume traffic. Recently, sketches, a family of probabilistic data structures that employ hashing technology for summarizing traffic data, have been widely used to solve these problems. However, current literature still lacks a thorough review on sketch-based traffic measurement methods to offer a comprehensive insight on how to apply sketches for fulfilling various traffic measurement tasks. In this paper, we provide a detailed and comprehensive review on the applications of sketches in network traffic measurement. To this end, we classify the network traffic measurement tasks into four categories based on the target of traffic measurement, namely cardinality estimation, flow size estimation, change anomaly detection, and persistent spreader identification. First, we briefly introduce these four types of traffic measurement tasks and discuss the advantages of applying sketches. Then, we propose a series of requirements with regard to the applications of sketches in network traffic measurement. After that, we perform a fine-grained classification for each sketch-based measurement category according to the technologies applied on sketches. During the review, we evaluate the performance, advantages and disadvantages of current sketch-based traffic measurement methods based on the proposed requirements. Through the thorough review, we gain a number of valuable implications that can guide us to choose and design proper traffic measurement methods based on sketches. We also review a number of general sketches that are highly expected in modern network systems to simultaneously perform multiple traffic measurement tasks and discuss their performance based on the proposed requirements. Finally, through our serious review, we summarize a number of open issues and identify several promising research directions. 相似文献
8.
针对现有的混凝土裂缝检测算法在各种复杂环境中检测精度不够、鲁棒性不强的问题,根据深度学习理论和U-net模型,提出一种全U型网络的裂缝检测算法。首先,依照原U-net模型路线构建网络;然后,在每个池化层后都进行一次上采样,恢复其在池化层之前的特征图规格,并将其与池化之前的卷积层进行融合,将融合之后的特征图作为新的融合层与原U-net网络上采样之后的网络层进行融合;最后,为了验证算法的有效性,在测试集中进行实验。结果表明,所提算法的平均精确率可达到83.48%,召回率为85.08%,F1为84.11%,相较于原U-net分别提升了1.48%,4.68%和3.29%,在复杂环境中也能提取完整裂缝,保证了裂缝检测的鲁棒性。 相似文献
9.
《Ceramics International》2022,48(11):15462-15469
Due to its unique artistic value, mosaic ceramics are widely used in construction-related fields. To meet the artist's demand for high-quality mosaic ceramic to create artistic works, it is necessary to meet the needs for efficient screening of mosaic ceramic tiles. Different from the ordinary large-target ceramics, mosaic ceramics exhibit characteristics of small tile sizes, a variety of colors, large demand for quantities, and easy reflection on the surface. Common manual detection methods show problems of low efficiency or accuracy, easy to fatigue, and many others. To solve these problems, this paper proposes a new detection method to identify surface defects of mosaic ceramic tiles and designs a detection system platform to achieve rapid detection. The experiment proves that the detection system has a detection rate of 93.99% for small defects on the surface of mosaic ceramic tiles, and the detection time of a single mosaic ceramic tile is less than 0.06 s. The detection method can quickly and accurately screen out high-quality, defect-free mosaic ceramic tiles, which can effectively improve the quality and artistic value of mosaic ceramic art creation. 相似文献
10.
《Journal of dairy science》2022,105(12):9463-9475
Phenyllactic acid (PLA) has been demonstrated to possess antibacterial activity and capacity to prolong food shelf life. However, studies on the performance of PLA in inhibiting Staphylococcus aureus and its effectiveness when applied to dairy products are largely lacking. Here, antibacterial activity (planktonic and biofilm states) of PLA against S. aureus CICC10145 (S. aureus_45) were investigated. The results showed that PLA inhibited growth of S. aureus_45 and formation of S. aureus_45 biofilm. Next, the antibacterial action target of PLA was uncovered from both physiological and phenotypic perspectives. The results showed that PLA decreased cell metabolic activity and cell viability, damaged cell membrane integrity, triggered leakage of intracellular contents (DNA, proteins, and ATP), and caused oxidative stress damage and morphological deformation of S. aureus_45. In practical application, the antibacterial activity of PLA against S. aureus_45 cells was further confirmed in skim milk and cheese as dairy food models, and the antibacterial effects can be adequately maintained during storage for 21 d, at least at 4°C. These findings suggested that PLA could be a potential candidate for controlling S. aureus outgrowth in dairy foods. 相似文献