The illustration depicts our CQ-CNN architecture for binary image classification. by Mominul Islam (3513758)

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)

Detection result. by Hailang Li (12557543)

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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)

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

“…Using the structures obtained through binarizing these images, the algorithm detects which image contains the dendrites (Scale bar = 10 μm). …”

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)

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

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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)

Number of backbones ensembled and their detection precisions. by Hailang Li (12557543)

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<b>DDS3 - Dataset of mosaic sputum smear microscopy images for evaluation of bacillus detection algorithms</b> by Marly G F Costa (19812192)

“…This dataset was generated to enable the training, validation and testing of bacillus detection algorithms. There are 8,000 mosaic images with corresponding binary masks. 6,000 for training set, 1,000 for validation set and 1,000 for testing set. …”

Detection results of different methods over the rail defect datasets. by Hailang Li (12557543)

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Illustration of unprocessed-image analysis and cropped-image analysis by the algorithm. by Seung Seog Han (4782486)

Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by Hussein Ali Bardan (21976208)

“…The binary GWO algorithm identifies the most relevant features from </p><p dir="ltr">dermatological images, eliminating redundancy and reducing the computational burden. …”

Effectiveness of image augmentation operations. by Hailang Li (12557543)

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Urgent versus nonurgent binary classification performance. by Kyung Won Kwon (18150416)

Image augmentation methods within IAB. by Hailang Li (12557543)

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The impact of the combination of image augmentation and feature augmentation operations. by Hailang Li (12557543)

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Particle tracking validation of the S8 algorithm. by Jennifer M. Knighten (15453354)

Performance of the proposed method for binary classification of lung cancer. by Md. Sabbir Hossain (9958939)

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