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1.
基于声呐的水下目标检测是具有重要意义的研究课题。由于声呐图像质量差、对比度低、边缘模糊等,基于特征提取的识别方法在精度和速度上无法满足现有要求。鉴于此,将基于卷积神经网络的 YOLOv3 引入声呐图像的目标识别任务中,首先通过动态亮度分配和中值滤波对图像进行预处理建立数据集,然后对 YOLOv3 模型进行训练和测试,最后根据静态目标的位置不变去除虚假目标,降低误检率。实验结果表明： 较之现有的特征提取识别算法,本算法具有更高的效率和更低的误检率。 相似文献
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海底甲烷冷泉特征与冷泉生态系统的群落结构 总被引：6，自引：0，他引：6
海底冷泉及冷泉生态系统是现代海洋地质学和生物学研究的前沿领域,它提升了人类对深海资源的认识和利用,拓展了深海极端环境下生命的潜在界线。综述了海底甲烷冷泉的成因、冷泉喷发的类型及其特征,海底冷泉分布、形成的主要阶段(150—100Ma BP,42—28Ma BP和12Ma BP以来)以及指示海底冷泉系统的简要特征;综述了冷泉化能自养生态系统及其食物链构成和特征,专性种、潜在专性种和非专性种的生物组成及其特征,冷泉环境中有孔虫和轻小型底栖动物的主要变化;最后划分了我国近海的冷泉区(点)并简要介绍它们的分布和特征,为开展我国近海冷泉及其冷泉生物群落的调查和研究提供了基础资料。 相似文献
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基因组大小(或称C值)作为生物单倍体细胞中全套染色体的DNA总量,在一定程度上是恒定的,因而C值可以作为生物物种的一个特定参数。深海热液和冷泉为更好地理解C值与不同环境之间的关系提供了一个特征性的模型。本文采用流式细胞术,测定了来自热液和冷泉环境中的10种深海无脊椎动物的C值,其分布范围从0.87 pg到12.28 pg,其中,相比于软体动物和多毛类,甲壳生物基因组大小及变异均较大。对比热液和冷泉两个群落中共有种(深海偏顶蛤Bathymodiolus platifrons、柯氏潜铠虾Shinkaia crosnieri以及长角阿尔文虾Alvinocaris longirostris)的基因组大小,发现C值差异并不显著。同时,综合已有的数据,对深海化能极端环境与其他环境条件下的物种C值进行对比分析,结果显示深海化能极端环境下生物的基因组大小并没有发现明确的变化趋势。 相似文献
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随着海上交通运输业业务需求的不断增加,传统的目标检测方法已无法满足实际需求。由于卫星遥感技术的快速发展,基于合成孔径雷达（Synthetic Aperture Radar,SAR）图像舰船目标自动识别具有显著的应用潜力。近年来,深度学习技术在目标检测领域逐渐显现出优势,特别是YOLO (You Only Look Once)模型以其较高的精度和计算效率,为SAR舰船目标的识别提供了一种新的方法。为对比不同的YOLO模型在舰船目标识别领域的性能及其相比于两阶段深度学习算法的优势,本文首先对YOLO系列的结构进行了归纳总结;其次对当前广泛使用的数据集进行了对比分析,并基于SAR图像数据集（SAR Ship Detection Dataset,SSDD）的样本进行重新标注构建出本文的数据集;然后将YOLO系列模型与两阶段目标检测方法——更快速的区域卷积神经网络（Faster Region-based Convolutional Neural Network,Faster R-CNN）在SAR舰船目标检测的精度和速度两方面进行对比实验;最后在YOLOv5模型的基础上对主干网络（Backbone... 相似文献
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平端深海偏顶蛤(Gigantidasplatifrons)是广泛分布于西太平洋深海热液和冷泉生态系统中的优势种和共有种,也是深海化能生态系统中重要的生境营造种。以南海F冷泉平端深海偏顶蛤为研究对象,基于贝壳日生长轮方法,分析了平端深海偏顶蛤的年龄与生长速率,建立了其年龄与贝壳壳长关系的生长方程。同时,结合获得的生长方程,分析了南海F冷泉采样点(119.285 6°E,22.115 4°N)平端深海偏顶蛤种群的年龄结构。研究结果表明,采样获得的平端深海偏顶蛤种群的最大壳长为11.4 cm,最大寿命为13.5龄。研究区域的贝壳长度分布集中在4～7 cm,占比60%;年龄分布集中在2～4龄,占比49.7%。相关研究结果为进一步开展平端深海偏顶蛤的生长研究提供了基础数据,有助于深入了解冷泉区域的种群动态变化规律。 相似文献
6.
热液和冷泉活动是现代深海环境中两个重要的极端系统,它们均是岩石圈与外部圈层之间进行物质、能量转移和交换的重要途径,它们之间既有显著差异,但也存在很多相似点。一系列调查研究表明,在某些特殊构造单元,热液和冷泉活动可能并不是彼此孤立的,而是在构造地质、生物生态和元素循环上存在某种相互作用或耦合关系。冲绳海槽作为西太平洋一个典型的弧后盆地,发育了繁盛的热液和冷泉活动,是研究这两个海底极端系统相互影响机制的天然实验室。在大量文献调研和野外精细探测结果的基础上,分析了冲绳海槽内相互毗邻的冷泉和热液之间的物质扩散过程及生物地球化学作用,初步建立了两个极端系统内两种不同流体相互作用的概念模型,认识到未来如对两个深海极端环境共生区构造发育特征、地层流体演化、生物群落以及矿物元素组成进行系统分析,将有助于建立更加完善的冷泉-热液两个系统在物质和能量上的耦合关系模型,同时也有助于揭示它们在生物生态之间的沟通融合规律,最终可建立盆地尺度上热液-冷泉区相互作用模式,从而加深对西太平洋甚至全球范围内冷泉-热液两个极端环境系统甚至"流体-固体"耦合的规律性认识。 相似文献
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海洋中尺度涡是一种常见的中尺度海洋现象,研究海洋中尺度涡的分布及运动特性对航运、气候、军事等具有重要作用,海洋中尺度涡的识别是海洋学和计算机科学领域的一个热门研究课题。运用深度学习的方法和框架,对中尺度涡的二维识别和三维结构构建展开研究分析。首先,获取全球海洋再分析数据并进行流线可视化,构建涡旋流线数据集;其次,利用YOLO v5s卷积神经网络对涡旋流线数据集进行训练,并对南海区域中尺度涡进行有效检测。实验结果表明,YOLO v5s训练后得到最优模型经过测试,平均检测精度均值达到了86.10%;最后,根据涡旋检测结果,对检测出的同时刻不同深度的涡旋判断是否属于同一涡旋,确定后进行该涡旋的三维结构构建。 相似文献
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SAR（synthetic aperture radar）图像溢油暗斑准确识别对海上溢油应急工作具有重要的意义。为减少SAR图像特征提取、特征选择过程中人为因素对溢油检测精度的影响,本文将Faster R-CNN卷积神经网络模型引入SAR图像溢油检测并进行了改进。针对溢油暗斑形状多样及SAR图像背景复杂的特点,选用结构一致且实用性强的VGG16卷积网络获取图像特征,并使用软化非极大值抑制算法（Soft-NMS）进行优化。同时基于相同的数据集,提取常用的SAR图像几何特征、灰度特征和纹理特征,构建反向传播（backpropagation,BP）人工神经网络溢油检测方法并与Faster R-CNN方法进行对比。实验结果表明,基于改进Faster-RCNN模型的溢油检测方法溢油检测率达到0.78,且溢油检测虚警率低于0.25,相比BP人工神经网络溢油检测方法样本识别率、溢油检测率分别提高了4%和5%,溢油虚警率降低了5%。 相似文献
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对鱼类的行为进行智能监测,精准地量化与识别其健康状态,已成为研究热点。为实现养殖鳗鲡行为状态精准识别,提出一种基于DenseNet双流卷积神经网络的鳗鲡行为状态检测方法。利用混合高斯背景模型进行前景提取构建数据集,针对传统卷积神经网络对于时间动态信息提取能力有限的问题,搭建关联空间特征与时间特征的双流网络结构(Two-stream),并使用DenseNet-121网络替换原网络,对比VGGNet、ResNet等网络,通过密集连接实现特征重用,在搭建更深的网络结构基础上加强了运动特征传递并减少了参数量,更好地提取具有代表性的行为特征。传统双流网络在两端的softmax层仅作简单的决策层平均融合,无法更深程度关联时空高级特征,提出在网络卷积层提取空间特征与时间特征后,加上一层卷积层将时空特征进行卷积融合以提升模型识别精度。实验结果表明:文中提出的基于DenseNet双流卷积神经网络对6种鳗鲡行为状态检测方法准确率达到96.8%,相较于单通道的空间流与时间流网络,准确率分别提升了10.1%和9.5%;相较于以VGGNet、ResNet搭建的双流网络,准确率分别提升了12.4%和4.2%;与决... 相似文献
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深海在黑暗、高静水压、低温（黑烟囱等热液系统除外）和寡营养的极端环境下形成了特殊的生境。对深海生物/微生物的研究,不仅可以揭示各种深海生物的生理代谢特性和动态变化规律,而且有助于深海生物资源的开发利用,特别是深海微生物碳循环机制的相关研究可为全球实现碳中和目标提供新的路线图。研究深海生物的首要条件是获得大量保持原位特性的样本,然而传统深海采样手段的局限可能导致深海相关研究结果无法反映深海环境下真实的生命过程,亟需发展满足深海生物原位研究的采样方法和生态监测技术。本文对深海生物研究现状,相关科学问题和原位组学研究进展,以及原位生态监测装备研发和应用进行综述,并对深海原位生物实验室进行了展望。 相似文献
12.
Little is known about species distribution patterns in deep-sea environments, primarily because sampling surveys in the high seas are expensive and time consuming. The increasing need to manage and protect vulnerable marine ecosystems, such as cold-water corals, has motivated the use of predictive modelling tools, which produce continuous maps of potential species or habitat distribution from limited point observations and full coverage environmental data. Rapid advances in acoustic remote sensing, oceanographic modelling and sampling technology now provide high quality datasets, facilitating model development with high spatial detail. This paper provides a short overview of existing methodologies for predicting deep-sea benthic species distribution, and illustrates emerging issues related to spatial and thematic data resolution, and the use of transect-derived species distribution data. In order to enhance the ecological relevance and reliability of deep-sea species distribution models, novel techniques are presented based on a case study predicting the distribution of the cold-water coral Lophelia pertusa in three carbonate mound provinces in Irish waters. Specifically, the study evaluates (1) the capacity of newly developed high-resolution (250 m grid cell size) hydrodynamic variables to explain local scale cold-water coral distribution patterns, (2) the potential value of species occurrence proportion data to maintain semi-quantitative information of coral prevalence (i.e. coverage) and sampling effort per grid cell within the response variable, and (3) mixed effect modelling to deal with spatially grouped transect data. The study shows that predictive models using vertical and horizontal flow parameters perform significantly better than models based on terrain parameters only. Semi-quantitative proportion data may decrease model uncertainty and increase model reliability, and provide a fruitful avenue of research for analysing large quantities of video data in a detailed yet time-efficient manner. The study concludes with an outlook of how species distribution models could improve our understanding of vulnerable marine ecosystem functioning and processes in the deep sea. 相似文献
13.
Foresti G.L. Murino V. Regazzoni C.S. Trucco A. 《Oceanic Engineering, IEEE Journal of》1997,22(1):57-65
This paper describes a voting-based approach for the fast automatic recognition of man-made objects and related attitude estimation in underwater acoustic images generated by forward-looking sonars or acoustic cameras. In general, the continuous analysis of sequences of images is a very heavy task for human operators and this is due to the poor quality of acoustic images. Hence, algorithms able to recognize an object on the basis of a priori knowledge of the model and to estimate its attitude with reference to a global coordinate system are very useful to facilitate underwater operations like object manipulation or vehicle navigation. The proposed method is capable of recognizing objects and estimating their two-dimensional attitude by using information coming from boundary segments and their angular relations. It is based on a simple voting approach directly applied to the edge discontinuities of underwater acoustic images, whose quality is usually affected by some undesired effects such as object blurring, speckle noise, and geometrical distortions degrading the edge detection. The voting approach is robust, with respect to these effects, so that good results are obtained even with images of very poor quality. The sequences of simulated and real acoustic images are presented in order to test the validity of the proposed method in terms of average estimation error and computational load 相似文献
14.
为解决侧扫声纳(SSS)图像沉船检测中样本不足、代表性弱等带来的检测精度低的问题,提出了一种联合YOLOv4和迁移学习的SSS图像沉船检测方法。首先,基于SSS成像机理实现了SSS沉船图像样本扩增,解决样本少而无法开展沉船检测模型构建的难题;然后,利用迁移学习,将公共数据集上学习到的权重和沉船通用性特征引入YOLOv4网络,构建高性能沉船检测模型。试验表明,构建的沉船检测模型取得了85.5%的类平均精度(mAP),将传统方法的检测精度提升了7.7%,在少样本情况下实现了沉船的高精度检测。 相似文献
15.
实现高精度的定位导航是深海采矿车完成海底工作任务的基础条件。在采矿车行进过程中,声呐设备生成的图像信息能够反映海底场景的变化,从而体现采矿车本身的运动,由此建立了一种声呐图像里程计,并将其与轮式里程计和USBL测量数据相结合提出了一种深海采矿车组合定位导航算法。首先对多波束前视声呐图像进行预处理,然后使用Canny算法进行特征检测并对特征点云进行配准,再结合声呐成像原理构建了声呐图像里程计运动模型,最后通过轮式里程计运动模型推导预测方程、声呐图像里程计运动模型和USBL测量数据推导更新方程,利用EKF（extended Kalman filter）算法实现基于多传感器融合的定位与姿态估计。海试数据验证了该组合定位算法能实现轮式里程计、声呐里程计和超短基线在速度、位置、艏向角估计、定位速率的精度互补,具有一定的有效性和精确性,该算法为深海采矿车的定位与导航算法研发提供了参考。 相似文献
16.
Teresa Maggio Sabrina Lo Brutto Rita Cannas Anna Maria Deiana & Marco Arculeo 《Marine Ecology》2009,30(3):354-365
The deep-sea habitat, from 200 to 2000 m depth, has long been thought as an ecosystem where biotic and abiotic factors vary very little and consequently species are not disturbed by processes and phenomena which could promote fast evolutionary mechanisms. Unfortunately, biological information relating to deep water is limited, especially regarding the population genetics of species inhabiting the Mediterranean Sea, and general patterns cannot be inferred. In this study we report data on the population genetic structure of Aristeus antennatus , a deep-sea decapod crustacean species which has been widely studied due to its important economic value. We surveyed and examined the variation in a 369-bp fragment of the mtDNA control region from individuals caught by Spanish and Italian trawlers in eight localities. High levels of mitochondrial control region haplotypic diversity (ranging from 0.884 to 0.989) were observed. AMOVA showed a high level of genetic variation, more within than between populations, and a low but significant ΦST value was recovered. Minimum spanning network did not separate any haplotype group and haplotype distribution does not mirror the geographic origin of the samples. The absence of population substructuring was also observed with a principal coordinates analysis, which uses an individual-by-individual comparison. These results revealed extensive gene flow among populations. Information on demographic history based on mismatch analysis revealed an unstable population, showing an alternate pattern of growth and decline. Our results indicated that in the western and central Mediterranean basins A. antennatus is a large panmictic population with a fluctuating abundance. The absence of deep-sea barriers and adult migration may prevent the structuring of the species into genetically differentiated populations. 相似文献
17.
The contents of oxyanionic elements (V, Se and Mo) and cationic transition metals (Mn, Fe, Co, Ni, Cu and Zn) in sediments from near-shore to deep-sea environments were measured to clarify factors regulating the distribution of these elements in marine sediments. For cationic transition metals of which contents increase from near-shore to deep-sea environments, the chemical composition of pelagic clays is modeled by a mixture of aluminosilicates having the chemical composition of average shale and Fe–Mn oxides having the chemical composition of associated manganese nodules. The content of V is fairly constant in sediments from near-shore to deep-sea areas. The mixture model of average shale and manganese nodules holds also for V, although most of the V is located in the aluminosilicate lattices. The content of Se in the near-shore sediments is higher and that in the deep-sea sediments is lower than that in average shale. The high content in the near-shore sediments is interpreted as the addition of biogenic materials to aluminosilicates with average shale composition and the low content in deep-sea sediments is explained by oxidative release of Se from aluminosilicates. The content of Mo in sediments increases from near-shore to deep-sea environments. The general distribution of Mo in marine sediments is expressed by the mixture model. An anomalously high content of Mo in a near-shore sediment is attributed to adsorption of molybdate on manganese oxides. 相似文献
18.
近年来,海战场成为现代战争的主要作战区域之一,舰船目标逐渐成为海上重点监测对象,能否快速准确地识别海战场舰船目标的战术意图,给指挥员的决策提供必要的支持,这关系到一场海上战役的成败.随着合成孔径雷达(synthetic aperture radar,SAR)成像技术的不断发展,大量SAR图像可用于舰船目标检测与识别.利用SAR图像进行舰船目标检测与识别,已经成为重要的海洋应用之一.针对传统SAR图像舰船检测方法准确率较低的问题,本文在YOLOv3的基础上,结合感受野(receptive field block,RFB)模块,提出一种增强型的SAR舰船检测方法.该方法在最近公开的SAR图像舰船检测数据集上平均准确率值达到了91.50％,与原YOLOv3相比提高了0.92％.实验结果充分表明本文提出的算法在SAR舰船的检测中具有较好的检测效果. 相似文献