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This set contains 1450 fundus images with 899 glaucoma data and 551 normal data.
All text about patient information and the date that the associated images were collected are replaced by 0, which is black.
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The present database contains records of underwater sounds produced by dolphins of the species Tursiops Truncatos. The dolphins live in Dolphinarium Varna (Varna, Bulgaria) and are a family of five
individuals. The records was made in the autumn 2019 by the “SigNautic Lab” crew, using measurement equipment of the world’s leading suppliers Bruel&Kjaer and National Instruments. The database
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The data set are images taken from the Particle Image Velocimetry (PIV) method and the Planar Laser-Induced Fluorescence (PLIF) method. These methods set out the macro-scale experimental techniques that can enable fluid dynamic knowledge to inform molecular communication performance and design. Fluid dynamic experiments can capture latent features that allow the receiver to detect coherent signal structures and infer transmit parameters for optimal decoding.
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This dataset contains light-field microscopy images and converted sub-aperture images.
The folder with the name "Light-fieldMicroscopeData" contains raw light-field data. The file LFM_Calibrated_frame0-9.tif contains 9 frames of raw light-field microscopy images which has been calibrated. Each frame corresponds to a specific depth. The 9 frames cover a depth range from 0 um to 32 um with step size 4 um. Files with name LFM_Calibrated_frame?.png are the png version for each frame.
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The odometric model is simulated herein. We described the trajectory of such one odometric model, with the delta of the heading angle given as one parameter of the simulation. The iterations show that the trajectory is well in the continuity of the variations of the heading angle. Moreover the distance in X and in Y are shown for the vehicle to be driven in the trajectory of the odometric model.
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The dataset was built by capturing the static gestures of the American Sign Language (ASL) alphabet, from 8 people, except for the letters J and Z, since they are dynamic gestures. To capture the images, we used a Logitech Brio webcam, with a resolution of 1920 × 1080 pixels, in a university laboratory with artificial lighting. By extracting only the hand region, we defined an area of 400 × 400 pixels for the final image of our dataset.
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RECOVERY-FA19 dataset is established for development and evaluation of retinal vessel detection algorithms in fluorescein angiography (FA). RECOVERY-FA19 provides 8 high-resolution ultra-widefield FA images acquired using Optos California P200DTx camera and corresponding labeled binary vessel maps.
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