Machine Learning
This data set contains nifty 50 companies and all their details of Open, Volume, Close, Adj Close, and name of the company.
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This dataset consists of 1878 labeled images of flowers from blackberry trees from the specie Rubus L. subgenus Rubus Watson. These are white flowers with five petals that blossom in the spring through summer. The images were collected using an Intel RealSense D435i camera inside a greenhouse.
This images were inicially collected to support a robotic autonomous pollination project.
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This dataset was prepared to aid in the creation of a machine learning algorithm that would classify the white blood cells in thin blood smears of juvenile Visayan warty pigs. The creation of this dataset was deemed imperative because of the limited availability of blood smear images collected from the critically endangered species on the internet. The dataset contains 3,457 images of various types of white blood cells (JPEG) with accompanying cell type labels (XLSX).
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The data are made of nine sets of measurements of four chipless RFID tags. The first two are made of 2600 measurements made at 160 centimeters (distance between the tag and the antenna) without (first) and with (second) initial background subtraction. The third set is made of 5600 measurements made in the range of 50 – 140 centimeters. The next six sets are measurements made to test models trained with the third set. All the measurements are made in the monostatic configuration.
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This repository contains the data related to the paper “CNN-Based Image Reconstruction Method for Ultrafast Ultrasound Imaging” (10.1109/TUFFC.2021.3131383). It contains multiple datasets used for training and testing, as well as the trained models and results (predictions and metrics). In particular, it contains a large-scale simulated training dataset composed of 31000 images for the three different imaging configuration considered (i.e., low quality, high quality, and ultrahigh quality).
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EEG consists of collecting information from brain activity in the form of electrical voltage. Epileptic Seizure prediction and detection is a major sought after research nowadays. This dataset contains data from 11 patients of whom seizures are observed in EEG for 2 patients.
The total duration of seizures is 170 seconds. The number of channels is 16 and data is collected at 256Hz sampling rate.
The final dataset files in .csv format contain 87040 rows x 17 columns,
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A Dynamic Multi-Objective Evolutionary Algorithm
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This dataset is related to dog activity and is sensor data.
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