Artificial Intelligence
This dataset was collected in our lab using Kinect to emphasize three points: (1) Larger number of human activities. (2) Each subject performed all actions in a continuous manner with no breaks or pauses. Therefore, the start and end positions of body for the same actions are different. (3) Each subject performed the same actions four times while imaged from four different views: front view, left and right side views, and top view.
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The femur dataset is our internal dataset, which
was collected from the clinical data of the Affiliated Hospital
of Capital Medical University, including 41 knee joint CT
scans, with a total of 7121 axial enhanced knee joint clinical
CT images. The dataset is shown in Fig. 5, which can be
downloaded in our github.
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Reference Evapotranspiration (ETo) is the basic element of smart irrigation water management for sustainable developments in agriculture. Penman-Monteith (FAO-56 PM) is the standard method of ETo. The FAO-56 PM is complex in nature due to the requirements of many climatic conditions. Many existing machine learning-based solutions for simplification of ETo are limited to a specific area and not in accordance with the standard method FAO-56 PM.
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SWAN is a large-scale outdoor point cloud semantic segmentation, instance segmentation and object detection dataset. The dataset is targeted explicitly at the challenging urban environment, which aligns well with the needs of the intelligent transportation systems. The data is collected in the Central Business District (CBD) of Perth city in Australia, covering nearly 150km. It additionally used specialized equipment (portable trolley) to capture scenes of no-through roads and narrow streets.
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SWAN is a Large-Scale Outdoor Point Cloud semantic segmentation dataset . The dataset is targeted explicitly at the challenging urban environment, which aligns well with the needs of the intelligent transportation systems. The data is collected in the Central Business District (CBD) of Perth city in Australia, covering nearly 150km. It additionally used specialized equipment (portable trolley) to capture scenes of no-through roads and narrow streets.
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We pre-processed and built posts and comments posted during 2010-2016 on the subreddit r/depression.
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69 whole slide images for early gastric cancer diagnosis, evaluating the proposed variational energy network (VENet).
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The self-collected 30000 pathological images for gland segmentation, including training images and annotations.
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Grasp intention recognition is a vital problem for controlling assistive robots to help the elderly and infirm people restore arm and hand function. This dataset contains gaze data and scene image data of healthy individuals and hemiplegic patients while performing different grasping tasks. It can be used for gaze-based grasp intention recognition studies.
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Layout planning is centrally important in the field of architecture and urban design. Among the various basic units carrying urban functions, residential community plays a vital part for supporting human life. Therefore, the layout planning of residential community has always been of concern, and has attracted particular attention since the advent of deep learning that facilitates the automated layout generation and spatial pattern recognition.
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