Quantitative accuracy assessment of contextually filtered classified images

2001 ◽  
Vol 22 (16) ◽  
pp. 3203-3222 ◽  
Author(s):  
P. M. Zukowskyj ◽  
M. A. Bussell ◽  
C. Power ◽  
R. M. Teeuw
Keyword(s):  
Accuracy Assessment ◽  
Quantitative Accuracy

scholarly journals Quantitative accuracy assessment of the revised sparse Gash model using distinct time-step climatic parameters

2021 ◽  
Author(s):  
Yiran Li ◽  
Chuanjie Zhang ◽  
Yong Niu
Keyword(s):  
Accuracy Assessment ◽  
Growing Season ◽  
Northern China ◽  
Climatic Parameters ◽  
Time Step ◽  
Platycladus Orientalis ◽  
Climate Parameters ◽  
Quantitative Accuracy ◽  
Modeling Accuracy ◽  
Event Basis

Abstract Rainfall interception (I) can considerably influence the transport process of water. The revised sparse Gash model (RSGM) is a tool for determining the I, which assumes that the two climate parameters in the model are equal for all storms. However, few studies have provided additional cases to reexamine the correctness of this assumption and investigated the response of I of single storms to the time-step variability in climatic parameters. Hence, running the RSGM separately on an event basis during the growing season in 2017 and using three time-step climatic parameters (storm-based, monthly, and fixed) to estimate I for the forest stands of Pinus tabuliformis, Platycladus orientalis, and Acer truncatum in Northern China. In summary, the modeling accuracy of both cumulative I and individual I was enhanced by increasing the time step of the climatic parameters in this study. These positively support the assumption in the RSGM. These results suggest that it is more appropriate to run the RSGM using fixed climate parameters to estimate I for these tree species during the growing season in northern China. Additionally, the assumption in the RSGM should be appealed to be further confirmed across the widest possible range of species, regions, and time scales.

scholarly journals Quantitative accuracy assessment and optimization of SPECT geometrical calibration

2010 ◽  
Vol 15 (1) ◽  
pp. 96-101 ◽  
Author(s):  
Tianyu Ma ◽  
Yinbin Miao ◽  
Rutao Yao ◽  
Tiantian Dai ◽  
Xiao Deng
Keyword(s):  
Accuracy Assessment ◽  
Quantitative Accuracy

Quantitative accuracy of serotonergic neurotrans-mission imaging with high-resolution 123I SPECT

2004 ◽  
Vol 43 (06) ◽  
pp. 185-189 ◽  
Author(s):  
J. T. Kuikka
Keyword(s):  
High Resolution ◽  
Scatter Correction ◽  
Region Of Interest ◽  
Binding Potential ◽  
Partial Volume ◽  
Therapeutic Drugs ◽  
Quantitative Accuracy ◽  
Critical Error ◽  
Statistical Noise

Summary Aim: Serotonin transporter (SERT) imaging can be used to study the role of regional abnormalities of neurotransmitter release in various mental disorders and to study the mechanism of action of therapeutic drugs or drugs’ abuse. We examine the quantitative accuracy and reproducibility that can be achieved with high-resolution SPECT of serotonergic neurotransmission. Method: Binding potential (BP) of 123I labeled tracer specific for midbrain SERT was assessed in 20 healthy persons. The effects of scatter, attenuation, partial volume, mis-registration and statistical noise were estimated using phantom and human studies. Results: Without any correction, BP was underestimated by 73%. The partial volume error was the major component in this underestimation whereas the most critical error for the reproducibility was misplacement of region of interest (ROI). Conclusion: The proper ROI registration, the use of the multiple head gamma camera with transmission based scatter correction introduce more relevant results. However, due to the small dimensions of the midbrain SERT structures and poor spatial resolution of SPECT, the improvement without the partial volume correction is not great enough to restore the estimate of BP to that of the true one.

Rapid mapping accuracy assessment using low-cost UAV and open-source Structure from Motion

2020 ◽  
Vol 52 ◽  
pp. 55-61
Author(s):  
Ettore Potente ◽  
Cosimo Cagnazzo ◽  
Alessandro Deodati ◽  
Giuseppe Mastronuzzi
Keyword(s):  
Open Source ◽  
Structure From Motion ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Mapping Accuracy ◽  
Rapid Mapping ◽  
Source Structure

Speakers construct reference based on listeners’ expected visual search

2020 ◽  
Author(s):  
Julian Jara-Ettinger ◽  
Paula Rubio-Fernandez
Keyword(s):  
Visual Search ◽  
Computational Model ◽  
Referential Communication ◽  
Human Communication ◽  
Quantitative Accuracy ◽  
Utterance Length ◽  
Acceptability Judgments

A foundational assumption of human communication is that speakers ought to say as much as necessary, but no more. How speakers determine what is necessary in a given context, however, is unclear. In studies of referential communication, this expectation is often formalized as the idea that speakers should construct reference by selecting the shortest, sufficiently informative, description. Here we propose that reference production is, instead, a process whereby speakers adopt listeners’ perspectives to facilitate their visual search, without concern for utterance length. We show that a computational model of our proposal predicts graded acceptability judgments with quantitative accuracy, systematically outperforming brevity models. Our model also explains crosslinguistic differences in speakers’ propensity to over-specify in different visual contexts. Our findings suggest that reference production is best understood as driven by a cooperative goal to help the listener understand the intended message, rather than by an egocentric effort to minimize utterance length.

scholarly journals Assessing Riyadh’s Urban Change Utilizing High-Resolution Imagery

Land ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 193
Author(s):  
Ali Alghamdi ◽  
Anthony R. Cummings
Keyword(s):  
Maximum Likelihood ◽  
High Resolution ◽  
Accuracy Assessment ◽  
Middle Eastern ◽  
Object Oriented ◽  
Training Data ◽  
High Resolution Imagery ◽  
Significant Research ◽  
Desert Areas ◽  
Spot 5

The implications of change on local processes have attracted significant research interest in recent times. In urban settings, green spaces and forests have attracted much attention. Here, we present an assessment of change within the predominantly desert Middle Eastern city of Riyadh, an understudied setting. We utilized high-resolution SPOT 5 data and two classification techniques—maximum likelihood classification and object-oriented classification—to study the changes in Riyadh between 2004 and 2014. Imagery classification was completed with training data obtained from the SPOT 5 dataset, and an accuracy assessment was completed through a combination of field surveys and an application developed in ESRI Survey 123 tool. The Survey 123 tool allowed residents of Riyadh to present their views on land cover for the 2004 and 2014 imagery. Our analysis showed that soil or ‘desert’ areas were converted to roads and buildings to accommodate for Riyadh’s rapidly growing population. The object-oriented classifier provided higher overall accuracy than the maximum likelihood classifier (74.71% and 73.79% vs. 92.36% and 90.77% for 2004 and 2014). Our work provides insights into the changes within a desert environment and establishes a foundation for understanding change in this understudied setting.

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