Kidney Segmentation with LinkNetB7 by Cihan Akyel

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Employee Motivation Strategies and Sales Performance: A Case Study of Hawk’s Eye Lodge Bunyonyi. by Kihembo, Linnet

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Ethnobotany, floristic and phytochemical studies of medicinal plants used to treat uterine fibroids in Mbarara City, Uganda by Calton Nantinda, Esther Lynnet Kisakye, David Musana, Isaac Ssessanga, Ukashar Ssenabulya, Timothy Omara, Ivan Kahwa, Florence Nalimu

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Evaluation of Siemens Healthineers’ StrokeSegApp for automated diffusion and perfusion lesion segmentation in patients with ischemic stroke by Lynnet-Samuel J. Teichmann, Ahmed A. Khalil, Kersten Villringer, Jochen B. Fiebach, Stefan Huwer, Eli Gibson, Ivana Galinovic

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Patterns of self-harm presentations at a Tertiary Urban Hospital in Kenya: A retrospective 5-year study (2018-2022). by Willie Njoroge, Catherine Gitau, Everline Onchari, Linnet Ongeri, Linda Khakali, Murad Khan, Zul Merali, Lukoye Atwoli, Jasmit Shah

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Blood Vessel Segmentation and Classification of Diabetic Retinopathy with Machine Learning-Based Ensemble Model by Cihan Akyel, Bünyamin Ciylan

“…In this study, the noise of blood vessels in fundus images was eliminated using the LinkNet-RCB7 model, and diabetic retinopathy was categorized into five classes using a machine learning-based ensemble model. …”
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Attention-Based Convolutional Neural Network for Pavement Crack Detection by Haifeng Wan, Lei Gao, Manman Su, Qirun Sun, Lei Huang

“…The experiment results demonstrated that, compared with other popular models (ENet, ExFuse, FCN, LinkNet, SegNet, and UNet), for the public dataset, CrackResAttentionNet with BCE loss function and PRelu activation function achieved the best performance in terms of precision (89.40), mean IoU (71.51), recall (81.09), and F1 (85.04). …”
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RS-Lane: A Robust Lane Detection Method Based on ResNeSt and Self-Attention Distillation for Challenging Traffic Situations by Ronghui Zhang, Yueying Wu, Wanting Gou, Junzhou Chen

“…This method is based on LaneNet and uses Split Attention proposed by ResNeSt to improve the feature representation on slender and sparse annotations like lane markings. …”
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