Spelling suggestions: "subject:"[een] CHANGE DETECTION"" "subject:"[enn] CHANGE DETECTION""
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Perceptual Grouping by Closure in Visual Working MemoryNeira, Sofia 01 January 2016 (has links)
Research on visual working memory (VWM) suggests a capacity limit of three to four objects (Luck & Vogel, 1997), but recent studies on the fidelity of VWM capacity for objects indicates that informational bandwidth, which can vary with factors like complexity and amenability to perceptual grouping, can interact with this capacity (Brady, Konkle & Alvarez, 2011). For example, individual features can be grouped into objects for an added benefit in VWM capacity (Xu, 2002). Along these lines, the Gestalt principles of proximity and connectedness have been shown to benefit VWM, although they do not influence capacity equally (Xu 2006; Woodman, Vecera & Luck, 2003). Closure, which has not been investigated for its influence in VWM capacity, is similar to connectedness and proximity as it promotes the perception of a coherent object without physical connections. In the current experiment, we evaluated whether closure produces similar or greater VWM capacity advantages compared to proximity by having participants engage in a change detection task. Four L-shaped features were grouped in tilted clusters to either form an object (closure condition) or not (no-object condition), with a set size of two (8 L features), four (16 L features), or six clusters (24 L features). Following a brief mask (1000 ms), the orientation of one cluster was changed (tilted 25 or -25 degrees) on half the trials. Our results indicate that there was no difference in accuracy or reaction time for the perceptual grouping conditions of closure/no-object, although we did find a main effect for set size and change conditions. Overall, it seems that grouping by closure provides no further advantages to VWM capacity than proximity; however, more experiments need to be conducted to solidify the findings of the current experiment.
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Estimation of Soil Moisture Using Active Microwave Remote SensingRamnath, Vinod 02 August 2003 (has links)
The method for developing a soil moisture inversion algorithm using Radar data can be approached in two ways: the multiple-incident angle approach and the change detection method. This thesis discusses how these two methods can be used to predict surface soil moisture. In the multiple incident angle approach, surface roughness can be mapped, if multiple incident angle viewing is possible and if the surface roughness is assumed constant during data acquisitions. A backpropagation neural network (NN) is trained with the data set generated by the Integral Equation Method (IEM) model. The training data set includes possible combinations of backscatter obtained as a result of variation in dielectric constant within the period of data acquisitions. The inputs to the network are backscatter acquired at different incident angles. The outputs are correlation length and root mean square height (rms). Once the roughness is mapped using these outputs, dielectric constant can be determined. Three different data sets, (backscatter acquired from multiplerequencies, multiple-polarizations, and multiple-incident angles) are used to train the NN. The performance of the NN trained by the different data sets is compared. The next approach is the application of the change detection concept. In this approach, the relative change in dielectric constant over two different periods is determined from Radarsat data using a simplified algorithm. The vegetation backscatter contribution can be removed with the aid of multi-spectral data provided by Landsat. A method is proposed that minimizes the effect of incident angle on Radar backscatter by normalizing the acquired SAR images to a reference angle. A quantitative comparison of some of the existing soil moisture estimation algorithms is also made
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Morphology-Based Identification of Surface Features to Support Landslide Hazard Detection Using Airborne LiDAR DataMora, Omar Ernesto 29 May 2015 (has links)
No description available.
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Cortical Representation of Frequency Changes in Cochlear Implant UsersLiang, Chun, Ph.D. 12 December 2017 (has links)
No description available.
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Conservation Matters: Applied Geography for Habitat Assessments to Maintain and Restore BiodiversityJacobs, Teri A. 12 December 2017 (has links)
No description available.
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Characterizing Remote Sensing Data Compression Distortion for Improved Automated Exploitation PerformanceMcGuinness, Christopher 31 May 2018 (has links)
No description available.
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Land Cover Change Across an Urban-Rural Transect in Southern Ohio, 1988-2008Walsh, Steven 18 August 2009 (has links)
No description available.
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Multi-Ratio Fusion Change Detection Framework with Adaptive Statistical ThresholdingHytla, Patrick C. 18 May 2016 (has links)
No description available.
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Automatic Building Change Detection Through Linear Feature Fusion and Difference of Gaussian ClassificationPrince, Daniel Paul January 2016 (has links)
No description available.
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A model-based approach to hyperspectral change detectionMeola, Joseph 15 December 2011 (has links)
No description available.
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