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This is the dataset related to the article "Machine-learning-based Colorimetric Sensor on Smarthone for Salivary Uric Acid Detection". The dataset contains two types of images. The first type is the full-sized image captured by the sensor, which is used to evaluate the performance of the ROI detection. The second type is the reaction area from artificial saliva and clinical samples, which is used to train and test machine-learning models.
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An understanding of local walking context plays an important role in the analysis of gait in humans and in the high level control systems of robotic prostheses. Laboratory analysis on its own can constrain the ability of researchers to properly assess clinical gait in patients and robotic prostheses to function well in many contexts, therefore study in diverse walking environments is warranted. A ground-truth understanding of the walking terrain is traditionally identified from simple visual data.
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"LaneVisionIITR: A Comprehensive High-Resolution Dataset for Lane Detection recorded at IIT Roorkee ", which is a newly built high-resolution dataset for developing Lane detection dataset for advanced driver assistance systems.
This folder consists of three files for each image:
1. The image captured in .jpg format.
2. Annotations (.json) having left and center line coordinates represented as “L” and “C” respectively.
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429 Views
This dataset is a collection of images and their respective labels containing examples of multiple Brazilian coins, the primary purpose is to support the development of Computer Vision techniques for automatic detection of such objects, i.e., localization and classification tasks.
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1369 Views
Water meter dataset. Contains 1244 water meter images. Assembled using a crowdsourcing platform Yandex.Toloka.
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4154 Views
A spectrally encapsulated orthogonal frequency division multiplexing (SE-OFDM) precoding scheme for short packet transmission that is able to suppress the out-of-band emission (OoBE) while maintaining the advantage of thecyclic prefix (CP)-OFDM is proposed. The SE-OFDM symbol consists of a prefix, an information (I)-symboland a suffix that are generated by head, center and tail matrices, respectively.
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219 Views