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)

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)

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

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)

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)

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

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)

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)

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

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. …”

Super.Complex identifies likely protein complexes within a PPI network using a distributed supervised AutoML method. by Meghana Venkata Palukuri (11890672)

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. …”

Data_Sheet_1_DINTD: Detection and Inference of Tandem Duplications From Short Sequencing Reads.docx by Jinxin Dong (9229511)

“…The major principle of the proposed method is that it first extracts read depth and mapping quality signals, then uses the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm to find the possible TD regions. …”

Table 1_Non-obtrusive monitoring of obstructive sleep apnea syndrome based on ballistocardiography: a preliminary study.docx by Biyong Zhang (20906192)

“…Applying fast change-point detection to first isolate apnea-suspected episodes would allow for processing only those suspected episodes for further feature extraction and OSAS severity classification. …”

Flowchart of software workflow. by Gavrielle R. Untracht (11820311)