(a-topleft) The original image in RGN color space, (b-topright) the hard segmentation output of the GFkuts algorithm after 5 iterations, (c-bottomleft) the soft segmentation result... by Julian D. Colorado (9461385)

Pre-processing of raw images for pose estimation using physical model-trained convolutional neural network model. by Aniket Ravan (3174171)

Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging by D. Andrew Brown (6584837)

Table_1_Fusion of fruit image processing and deep learning: a study on identification of citrus ripeness based on R-LBP algorithm and YOLO-CIT model.docx by Chenglin Wang (430151)

“…Instead of traditional convolution, Ghostconv is utilized by the neck network of the YOLO-CIT model. The fruit segment of citrus in the original citrus images processed by the R-LBP algorithm is combined with the background segment of the citrus images after grayscale processing to construct synthetic images, which are subsequently added to the training dataset. …”

ROC curves of our out-of-class algorithm (blue) and a threshold decision boundary (red) representing the true positive rates (TPR) compared to the false positive rates (FPR) for te... by G. Christopher Marais (21492084)

Experimental setup and trajectory estimation methodology. by Nouman Javed (16624785)

Data_Sheet_1_Information-theoretic analysis of Hierarchical Temporal Memory-Spatial Pooler algorithm with a new upper bound for the standard information bottleneck method.pdf by Shiva Sanati (16035875)

DataSheet_1_Preoperatively Estimating the Malignant Potential of Mediastinal Lymph Nodes: A Pilot Study Toward Establishing a Robust Radiomics Model Based on Contrast-Enhanced CT I... by Mengshi Dong (5181833)

“…Purpose<p>To establish and validate a radiomics model to estimate the malignancy of mediastinal lymph nodes (LNs) based on contrast-enhanced CT imaging.…”

Data_Sheet_2_Predicting Axial Length From Choroidal Thickness on Optical Coherence Tomography Images With Machine Learning Based Algorithms.docx by Hao-Chun Lu (12965318)

“…</p>Methods<p>The CT was estimated from 3 points of each image. We used five machine-learning base algorithms to construct the classifiers. …”

Data_Sheet_1_Predicting Axial Length From Choroidal Thickness on Optical Coherence Tomography Images With Machine Learning Based Algorithms.docx by Hao-Chun Lu (12965318)

“…</p>Methods<p>The CT was estimated from 3 points of each image. We used five machine-learning base algorithms to construct the classifiers. …”

Image_2_A Diagnostic Model for Kawasaki Disease Based on Immune Cell Characterization From Blood Samples.TIF by Shangming Du (9950501)

Image_4_A Diagnostic Model for Kawasaki Disease Based on Immune Cell Characterization From Blood Samples.TIF by Shangming Du (9950501)

Image_1_A Diagnostic Model for Kawasaki Disease Based on Immune Cell Characterization From Blood Samples.TIF by Shangming Du (9950501)

Image_3_A Diagnostic Model for Kawasaki Disease Based on Immune Cell Characterization From Blood Samples.TIF by Shangming Du (9950501)

NuSeT efficiently addresses common segmentation challenges. by Linfeng Yang (516708)

Supplementary Material for: Automated Detection and Diameter Estimation for Mouse Mesenteric Artery Using Semantic Segmentation by Higaki A. (11035161)

“…In this study, we developed an automatic artery/vein differentiation and a size measurement system utilizing machine learning algorithms. <b><i>Methods and Results:</i></b> We used 654 independent mouse mesenteric artery images for model training. …”

3D Microvascular Image Data and Labels for Machine Learning by Natalie Holroyd (7099391)

“…<p dir="ltr">These images and associated binary labels were collected from collaborators across multiple universities to serve as a diverse representation of biomedical images of vessel structures, for use in the training and validation of machine learning tools for vessel segmentation. …”

Imaging of the zebrafish tectum. by Giovanni Diana (7610630)

“…(D) Raw fluorescence is described in terms of a Hidden Markov model (HMM) where periods of increased activity are indicated by a binary process ({<i>s</i>}) triggering the onset of calcium transients ({<i>c</i>}). …”

WEISS Catheter Segmentation in Fluoroscopy Dataset by Evangelos Mazomenos (6761597)

“…The output of the algorithm was manually checked and corrected to provide the final catheter segmentation.…”

Deep Discrete Encoders: Identifiable Deep Generative Models for Rich Data with Discrete Latent Layers by Seunghyun Lee (1372719)

“…Extensive simulation studies for high-dimensional data and deep architectures validate our theoretical results and demonstrate the excellent performance of our algorithms. We apply DDEs to three diverse real datasets with different data types to perform hierarchical topic modeling, image representation learning, and response time modeling in educational testing.…”