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The Femoropopliteal Artery Stent Dataset is captured by Siemens digital radiography fluoroscopy system Luminos dRF Max. The dataset is from the First Affiliated Hospital of Fujian Medical University in Fuzhou City (Fujian Province, China). The X-ray fluoroscopic image data set of the femoropopliteal artery stent was obtained from different positions of the patient.
The provided dataset file contains the following directory structure when unzipped:
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This publication contains three new datasets for scene-level sketch semantic segmentation task, namely SKY-Scene, TUB-Scene, and Freehand-Scene. SKY-Scene and TUB-Scene are synthetic datasets, where the scene layout templates were extracted from dataset SketchyScene, and the object components were adopted from dataset Sketchy. They are composed to include more sketch-specific characteristics, e.g., sparsity, abstractness, and diversity, to truly evaluate segmentation performance. Freehand-Scene are fifty real human-drawn scene sketches for practical test.
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Fifty human-drawn scene sketches with semantic annotation.
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A synthetic scene-level sketch dataset for sketch semantic segmentation task. The scene layout templates were extracted from dataset SketchyScene, and the object components were adopted from dataset TU-Berlin.
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A synthetic scene-level sketch dataset for sketch semantic segmentation task. The scene layout templates were extracted from dataset SketchyScene, and the object components were adopted from dataset Sketchy.
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该舌头图像数据集包含 300 张舌头图像。数据集中所有图像均由我们的图像采集设备采集,图像尺寸为576*768。手动分割被用作基本事实。
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The Lung Image Database Consortium image collection (LIDC-IDRI) consists of diagnostic and lung cancer screening thoracic computed tomography (CT) scans with marked-up annotated lesions. It is a web-accessible international resource for development, training, and evaluation of computer-assisted diagnostic (CAD) methods for lung cancer detection and diagnosis.
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The dataset contains UAV imagery and fracture interpretation of rock outcrops acquired in Praia das Conchas, Cabo Frio, Rio de Janeiro, Brazil. Along with georeferenced .geotiff images, the dataset contains filtered 500 x 500 .png tiles containing only scenes with fracture data, along with .png binary masks for semantic segmentation and original georeferenced shapefile annotations. This data can be useful for segmentation and extraction of geological structures from UAV imagery, for evaluating computer vision methodologies or machine learning techniques.
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In this brief,
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