Artificial Intelligence

This is a CSI dataset towards 5G NR high-precision positioning,

which is fine-grainedgeneral-purpose and 3GPP R18 standards complied

 

 

The corresponding paper is published here (https://doi.org/10.1109/jsac.2022.3157397).

5G NR is normally considered to as a new paradigm change in integrated sensing and communication (ISAC).

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In large-scale multiobjective optimization, too many decision variables hinder the convergence search of evolutionary algorithms. Reducing the search range of the decision space will significantly alleviate this puzzle. With this in mind, this paper proposes a fuzzy decision variables framework for large-scale multiobjective optimization. The framework divides the entire evolutionary process into two main stages: fuzzy evolution and precise evolution.

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Leucorrhea microscopic data set is a set of leucorrhea microscopic images, which is used in object detection task. The datasets are collected from the Sixth People’s Hospital of Chengdu (Sichuan Province, China). The samples were went flow diluted, stirred and placed, and imaged with a microscopic imaging system. The clearest 3 images were collected for each view of each sample with Tenengrad definition algorithm. The dataset we collected includes 1552 groups of views with 4656 jpg images. The Resolution of images are 1200×1920.

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424 Views

The University of Turin (UniTO) released the open-access dataset Stoke collected for the homonymous Use Case 3 in the DeepHealth project (https://deephealth-project.eu/). UniToBrain is a dataset of Computed Tomography (CT) perfusion images (CTP).

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3486 Views

This dataset includes the 3-day record (December 6 to December 8, 2020) of a plantation in the city of Guayaquil - Ecuador. This dataset includes the recording of the following variables: Relative Humidity, Environment Temperature, Soil moisture, Light intensity, and Rain Occurrence. An arduino uno module was used to record data, connected to the following sensors:

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66743 Views

Most of existing audio fingerprinting systems have limitations to be used for high-specific audio retrieval at scale. In this work, we generate a low-dimensional representation from a short unit segment of audio, and couple this fingerprint with a fast maximum inner-product search. To this end, we present a contrastive learning framework that derives from the segment-level search objective. Each update in training uses a batch consisting of a set of pseudo labels, randomly selected original samples, and their augmented replicas.

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This data set contains 416 liver patient records and 167 non liver patient records collected from North East of Andhra Pradesh, India. The "Dataset" column is a class label used to divide groups into liver patient (liver disease) or not (no disease). This data set contains 441 male patient records and 142 female patient records. 

Any patient whose age exceeded 89 is listed as being of age "90".

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488 Views

The datasets are about two user studies for brushing points in the scatterplot.

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This dataset contains trained weights to use with Mask RCNN for the purpose of detecting barchan dunes on Earth and Mars

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The region-based segmentation approach has been a major research area for many medical image applications. A vision guided autonomous system has used region-based segmentation information to operate heavy machinery and locomotive machines intended for computer vision applications. The dataset contains raw images in .png format fro brain tumor in various portions of brain.The dataset can be used fro training and testing. Images are calssified into three main regions as frontal lobe(level -1, level-2), optus-lobe(level-1), medula_lobe(level-1,level-2,level-3).

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10376 Views

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