Effect of image resolution on the performance of the binary classifier algorithm in predicting occurrence of a bird target(s) on an individual image using the validation imagery se... by Tsung-Wei Ke (18297551)

The classification algorithm flow chart for binary classification among NC, EMCI, LMCI and AD groups. by Qian Zhang (49333)

Effect of training regions on the performance of the Mask R-CNN detection algorithm based on the refined annotation bounding boxes. by Tsung-Wei Ke (18297551)

Performance of the baseline SVM and Mask R-CNN detection algorithms based on the original, manually-derived annotated bounding boxes. by Tsung-Wei Ke (18297551)

Effect of image resolution on the performance of the Mask R-CNN algorithm in detecting individual bird instances as applied to the validation imagery set. by Tsung-Wei Ke (18297551)

Performance of the Mask R-CNN detection algorithm based on the original, manually-derived, annotation bounding boxes, and the refined annotation bounding boxes. by Tsung-Wei Ke (18297551)

Detection performances and validation losses. by Hailang Li (12557543)

Key steps in neurodegeneration detection algorithm. by Andrew S. Clark (16510496)

“…<p><b>A.</b> Dendrite detection steps. The original image is first contrast adjusted and binarized to detect the location of the cell body (Scale bar = 25 μm). …”

For each classification algorithm, the classification accuracies for binary subject groups NC versus EMCI, NC versus LEMC, EMCI versus LEMC, EMCI versus AD, LMCI versus AD, AD vers... by Qian Zhang (49333)

Examples of input (first column) and areas between ILM and RPE layers of ground truth (second column) and U-Net (third columns) and U-Net++ (fourth column) of four OCT cases. by Rinrada Tanthanathewin (18611171)

The main workflow of the proposed algorithm. by Xin Li (51274)

Signal detection algorithm adapted from [1] yields exponential distributions and unrealistic mean durations of percepts. by Quynh-Anh Nguyen (847240)

“…(Bottom) Trial-by-trial applications of the signal detection algorithm from [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1008152#pcbi.1008152.ref001" target="_blank">1</a>] with A: <i>C</i>_<i>th</i> = 4.01 and B: <i>C</i>_<i>th</i> = 4.21 yield exponentially distributed subsequent percept durations for <i>I</i> (blue) and <i>S</i> (red). …”

Samples of the rail defect dataset with 8 categories. by Hailang Li (12557543)

Effect of different randomization constraints on pattern detection. by Zachary P. Neal (9946331)

Region-specific variable importance. by Katherine E. Overly (10789206)

“…Using occurrence data and terrain attributes derived from bathymetric datasets at different resolutions, we developed species distribution models unique to each sampling region (west, northeast, and southeast Puerto Rico) using seven different algorithms. Then, we developed ESDM models to analyze fish distribution using the highest-performing algorithms for each region. …”

Detection and Analysis of Nodule in Mammographic images using false positive reduction Detection Technique by Dr.E.N. Ganesh (12315038)

“…The second</p> <p>approach is based on an extension of his PCA approach using the recently proposed 2DPCA</p> <p>algorithm. Finally, a third approach is based on local binary patterns (LBPs) to represent texture</p> <p>information while preserving the spatial structure of the mass. …”

Recognition of each neuron’s digital identity. by Yuxiang Wu (748543)

MRCNN+Watershed workflow. by Anuradha Kar (12418362)

Flow diagram of the automatic animal detection and background reconstruction. by David Tadres (9120564)

“…(K) Using the local threshold, each new image is binarized and then subtracted from the first image as shown in panel (J, bottom). If the identical blob that was detected in panel J (bottom) is found in any of the new subtracted binary images (cyan arrow), the animal is considered as having left its original position, and the algorithm continues. …”

Nonparametric Distribution Regression and Change Point Detection in High-Dimensions by Shivam Kumar (17808571)

“…This dissertation investigates two high-dimensional problems—change-point analysis in functional linear regression and nonparametric density estimation using modern generative models. First, we introduce the Functional Regression Binary Segmentation (FRBS) algorithm for change-point detection in the slope function when predictors are functions and responses are scalars. …”