The confidence curve of a binary image. by Dingming Yang (8505990)

The confidence change of the binary image after iteration. by Dingming Yang (8505990)

Test results of different models on TinyPerson. by Ju Liang (4277062)

“…These characteristics impose high demands on detection algorithms in terms of fine-grained feature extraction, cross-scale fusion capability, and occlusion resistance.The YOLOv11s model has significant limitations in practical applications: its feature extraction module has a single semantic representation, the traditional feature pyramid network has limited capability to detect multi-scale targets, and it lacks an effective feature compensation mechanism when targets are occluded.To address these issues, we propose a UAV aerial small target detection algorithm named UAS-YOLO (Universal Inverted Bottleneck with Adaptive BiFPN and Separated and Enhancement Attention module YOLO), which incorporates three key optimizations. …”

Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale. by Tehnan I. A. Mohamed (16846175)

Visual comparison of TinyPerson. by Ju Liang (4277062)

“…These characteristics impose high demands on detection algorithms in terms of fine-grained feature extraction, cross-scale fusion capability, and occlusion resistance.The YOLOv11s model has significant limitations in practical applications: its feature extraction module has a single semantic representation, the traditional feature pyramid network has limited capability to detect multi-scale targets, and it lacks an effective feature compensation mechanism when targets are occluded.To address these issues, we propose a UAV aerial small target detection algorithm named UAS-YOLO (Universal Inverted Bottleneck with Adaptive BiFPN and Separated and Enhancement Attention module YOLO), which incorporates three key optimizations. …”

Differences between models of different scales. by Daoze Tang (20454615)

“…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …”

A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

“…Pixel paths were classified using a z-score brightness threshold of 1.21, optimized for noise reduction and accuracy. The A* algorithm then evaluated connectivity by minimizing Euclidean distance and heuristic cost between cells. …”

ROC curve for binary classification. by Nicodemus Songose Awarayi (18414494)

“…The study introduced a scheme for enhancing images to improve the quality of the datasets. Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”

Confusion matrix for binary classification. by Nicodemus Songose Awarayi (18414494)

“…The study introduced a scheme for enhancing images to improve the quality of the datasets. Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”

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

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

“…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …”

Dataset 2: Zip file containing the Tables of the presented method and results by Suchismita Behera (22027316)

Image1_Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.JPEG by Wisnu Ananta Kusuma (9276182)

Image2_Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.JPEG by Wisnu Ananta Kusuma (9276182)

Image4_Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.jpg by Wisnu Ananta Kusuma (9276182)

Image5_Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.jpg by Wisnu Ananta Kusuma (9276182)

Image3_Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.JPEG by Wisnu Ananta Kusuma (9276182)

LC-FPN structure. by Daoze Tang (20454615)

“…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …”

Labeling information of the VisDrone dataset. by Daoze Tang (20454615)

“…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …”

LFERELAN structure. by Daoze Tang (20454615)

“…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …”