Asynchronous Veterinary Telemedicine     

《Veterinary Clinics of North America: Small Animal Practice》2022,52(5):1135-1140

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宁夏中部生态移民区土地利用时空变化分析     

路彩玲  朱志玲  王重玲 《西部林业科学》2015,(1):58-63

通过解译宁夏中部红寺堡区1989年、1999年、2006年、2012年TM遥感影像,获取该区域生态移民前后4期土地利用数据,对1989~2012年以来土地利用变化情况进行了分析。结果表明,各个时间段的土地利用变化差异性显著。1989~1999年,由于大规模的土地开荒和红寺堡灌区的建设,耕地面积持续增加,同时该区域开始有了水浇地,而林草面积相应减少;1999~2006年,由于退耕还林还草政策的实施,耕地中的旱地被逐渐退耕为草地或发展为水浇地,林草面积开始由减少转为增加,区域土地利用开始合理化;2006~2012年,随着生态移民工程和生态建设工程的成熟发展,林草覆盖面积进一步增加,水浇地面积继续稳步增加,而未利用地和旱地面积持续下降。研究结果为区域土地资源的合理利用及生态移民工程的进一步顺利开展提供可靠依据。  相似文献   

《唐物语》对朱买臣故事的摄取与创新     

王川 《安徽农业大学学报》2016,(3):108-112

《唐物语》第十九段对《汉书·朱买臣传》中朱买臣故事进行改编，因受众群体、文化差异、民族向性的不同，在改编过程中必然产生对母国文化信息的过滤与人物形象变异。以朱买臣故事东渐日本为线索，运用比较文学流传学与变异学，探究该文学作品对朱买臣故事的摄取与创新、朱买臣故事日本化的实现条件等，以期增进文学文化交流中的互读互解，避免因文学流变中信息过滤增删、形象失落变形而产生的民族心理与意识形态的误读。  相似文献   

基于卷积神经网络马铃薯叶片病害识别和病斑检测*     

王林柏  张博  姚竟发  杨志辉  张君  范晓飞 《中国农机化学报》2021,42(11):122

针对自然环境下马铃薯叶片病害识别率低和晚疫病斑定位难的问题,基于大田环境中采集的马铃薯叶片图像,首先对马铃薯叶片病害进行识别,对比AlexNet、VGG16、InceptionV3、ResNet50、MobileNet五种神经网络模型,结果表明InceptionV3模型的识别效果准确率最高,可达98.00%。其次对马铃薯叶片的晚疫病斑进行检测,提出一种改进型的CenterNet-SPP模型,该模型通过特征提取网络获取对象的中心点,再通过中心点回归获得中心点偏移量、目标大小等图像信息,训练后的模型在验证集下的mAP可达90.03%,以F₁为评价值分析对比其它目标检测模型,CenterNet-SPP模型的效果最好,准确率为94.93%,召回率为90.34%,F₁值为92.58%,平均检测一张图像耗时0.10 s。为自然环境下马铃薯叶片病害识别和检测提供较为全面的深度学习算法和模型研究基础。  相似文献   

分块子空间追踪算法     

庄燕滨  王化程 《湖南农业大学学报(自然科学版)》2015,(4):64-68

压缩传感理论是一种充分利用信号稀疏性或者可压缩性的全新信号采样理论。该理论表明，通过采集少量的信号测量值就能够实现可稀疏信号的精确重构。本文在研究现有经典重构算法的基础上，提出结合图像分块思想和回溯思想的分块子空间追踪算法（Block Subspace Pursuit, B_SP）用于压缩传感信号的重构。该算法以块结构获取图像，利用回溯过程实现支撑集的自适应筛选，最终实现图像信号的精确重构。实验结果表明，在相同测试条件下，该算法的重构效果无论从主观视觉上还是客观数据上都有不同程度的提高。  相似文献   

Changes in Physical Properties of Soils with Land Use Time in the Brazilian Savanna Environment     

Kleber Trabaquini  Antnio Roberto Formaggio  Lênio Soares Galvo 《Land Degradation \u0026amp; Development》2015,26(4):397-408

Soils from central Brazil have been intensively used over the last decades because of the rapid conversion of savannas ( Cerrado ) into corn/soybean fields. The objective of this work is to study modifications in the physical properties of soils in the Rio Verde watershed, as a function of the land use time for agriculture, determined from classification of Landsat satellite images between 1980 and 2010. Soil samples were collected at surface (0–20 cm) and subsurface (20–40 cm) horizons for the different classes of land use time (<10, 10–20, 20–30, and >30 years). The following physical properties were measured: bulk density (BD), air permeability (K_a), penetration resistance (PR), microporosity (MI), macroporosity (MA), and total porosity (TP). Results showed a strong expansion with time of agriculture that occupied 35·3% (1980), 37·4% (1990), 51·3% (2000), and 60·9% (2010) of the watershed area. When properties were compared with those from the reference areas (preserved soils under native vegetation), significant differences were observed for all the physical attributes of soils for a land use time higher than 20 years. Overall, BD and PR increased with land use time, and the opposite was verified for K_a, MA, and TP. Some physical properties presented values (e.g., 1·54 g cm⁻³ for BD and 0.06 cm³ cm⁻³ for MA) close to the critical ones reported to affect crop development, but they were not still impacting on local soybean yield. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

Object‐Based Mapping of Karst Rocky Desertification using a Support Vector Machine     

E.‐Q. Xu  H.‐Q. Zhang  M.‐X. Li 《Land Degradation \u0026amp; Development》2015,26(2):158-167

Accurate and cost‐effective mapping of karst rocky desertification (KRD) is still a challenge at the regional and national scale. Visual interpretation has been utilised in the majority of studies, while an automated method based on pixel data has been investigated repeatedly. An object‐based method coupling with support vector machine (SVM) was developed and tested using Enhanced Thematic Mapper Plus (ETM+) images from three selected counties (Liujiang, Changshun and Zhenyuan) with different karst landscapes in SW China. The method supports a strategy of defining a mapping unit. It combined ETM+ images and ancillary data including elevation, slope and Normalized Difference Vegetation Index images. A sequence of scale parameters estimation, image segmentation, training data sampling, SVM parameters tuning and object classification was performed to achieve the mapping. A quantitative and semi‐automated approach was used to estimate scale parameters for segmenting an object at an optimal scale. We calculated the sum of area‐weighted standard deviation (WS), rate of change for WS, local variance (LV) and rate of change for LV at each scale level, and the threshold of the aforementioned index that indicated the optimal segment level and merge level. The KRD classification results had overall accuracies of 85·50, 84·00 and 84·86 per cent for Liujiang, Changshun and Zhenyuan, respectively, and kappa coefficients are up to 0·8062, 0·7917 and 0·8083, respectively. This approach mapped six classes of KRD and offered a visually appealing presentation. Moreover, it proposed a conceptual and size‐variable object from the classification standard of KRD. The results demonstrate that the application of our method provides an efficient approach for the mapping of KRD. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

基于高斯自适应拟合的苹果目标分割方法研究     

张润浩  李军  任静  宋怀波 《农机化研究》2015,(6):13-17

苹果目标的准确识别是苹果机械化采摘需要解决的关键问题之一。为此,基于YUV颜色空间模型,提出了一种结合色差分量与高斯自适应拟合算法的苹果目标分割方法。该方法采用首先将苹果目标由RGB颜色空间转换至YUV颜色空间,并利用色差分量V建立果实与背景分割的高斯分布拟合模型,根据拟合结果自动获取分割阈值,以实现自然场景下苹果目标的准确分割。为了验证文中算法的有效性,利用多幅图像进行了试验并与Otsu自适应阈值分割算法进行了比较。试验结果表明,采用文中算法得到的苹果果实的平均检出率达87.08%,识别率领先Otsu算法9.91%。因此,对于着色度较为均匀的苹果目标,采用高斯自适应拟合方法可以有效提高其识别率。  相似文献   

INVITED REVIEW—IMAGE REGISTRATION IN VETERINARY RADIATION ONCOLOGY: INDICATIONS,IMPLICATIONS, AND FUTURE ADVANCES          下载免费PDF全文

Yang Feng  Jessica Lawrence  Kun Cheng  Dean Montgomery  Lisa Forrest  Duncan B. Mclaren  Stephen McLaughlin  David J. Argyle  William H. Nailon 《Veterinary radiology & ultrasound》2016,57(2):113-123

The field of veterinary radiation therapy (RT) has gained substantial momentum in recent decades with significant advances in conformal treatment planning, image‐guided radiation therapy (IGRT), and intensity‐modulated (IMRT) techniques. At the root of these advancements lie improvements in tumor imaging, image alignment (registration), target volume delineation, and identification of critical structures. Image registration has been widely used to combine information from multimodality images such as computerized tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) to improve the accuracy of radiation delivery and reliably identify tumor‐bearing areas. Many different techniques have been applied in image registration. This review provides an overview of medical image registration in RT and its applications in veterinary oncology. A summary of the most commonly used approaches in human and veterinary medicine is presented along with their current use in IGRT and adaptive radiation therapy (ART). It is important to realize that registration does not guarantee that target volumes, such as the gross tumor volume (GTV), are correctly identified on the image being registered, as limitations unique to registration algorithms exist. Research involving novel registration frameworks for automatic segmentation of tumor volumes is ongoing and comparative oncology programs offer a unique opportunity to test the efficacy of proposed algorithms.  相似文献   

基于"3S"技术的甘肃子午岭自然保护区土地利用变化研究   总被引：1，自引：0，他引：1  

焦明  张世强  刘勇  张培栋  张小文 《草业科学》2007,24(11):14-17

以甘肃省子午岭自然保护区为研究对象,运用"3S"技术,对研究区的地形图、不同时相的TM遥感影像进行数据预处理,并分类提取了研究区2个时段的土地利用信息.对分类信息进行统计分析后并与实地调查数据进行比较,结果表明,近20年来甘肃子午岭自然保护区的森林覆盖面积在稳步提高,乔木林面积明显增加.为甘肃子午岭自然保护区工程的建设提供了基础信息,为林区植物种群生长及分布调查研究提供了宏观数据,并且输出了研究区不同时相土地利用专题图.  相似文献