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Datasets

19,997 machine learning datasets

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19,997 dataset results

Retinal Disease Classification

Description:

0 papers0 benchmarks

Potato Plant Diseases Data

Description:

0 papers0 benchmarksImages

Sokoto Coventry Fingerprint Dataset (SOCOFing)

Description:

0 papers0 benchmarks

Landslide-dam-dataset-for-LDBF

A landslide dataset for LDBF predictions.

0 papers0 benchmarks

CornHub (Instance-Segmentation Dataset of Corn Cobs)

๐ŸŒฝ CornHub: Instance-Segmentation Dataset of Corn Cobs Version: 1.0.0 Date: 2025-05-18 License: CC BY 4.0 Author: Sebastian Borukaล‚o

0 papers0 benchmarks

Reviews data from trustpilot

This dataset contains a curated sample of 20,000 English-language user reviews sourced exclusively from Trustpilot.com. It is a representative subset of our larger collection containing over 1 million Trustpilot reviews across various industries and companies.

0 papers0 benchmarks

Shanghai2020 (Shanghai-2020 Dataset)

It is released by the Shanghai Central Meteorological Observatory (SCMO) in 2020, records serval years of historical precipitation events in the Yangtze River delta area. The dataset contains a total of 43000 samples of precipitation events, of which 40000 samples for training and 3000 samples for testing. Each sample consists of 20 consecutive radar echo frames and lasts for 3 hours, where the first 10 frames are with intervals of 6 minutes and the last 10 frames are with intervals of 12 minutes. The echo frame has 460 * 460 resolution and covers 460km * 398km region. We additionally split out 3000 samples from the training set and use them for validation.

0 papers0 benchmarksImages, Videos

Grouper

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0 papers0 benchmarks

LLSD (Low-illumination steel dataset)

A dataset of low-illumination steel for industrial applications

0 papers0 benchmarks

NTU VIRAL (NTU VIRAL: A Visual-Inertial-Ranging-Lidar Dataset, From an Aerial Vehicle Viewpoint)

In recent years, autonomous robots have become ubiquitous in research and daily life. Among many factors, public datasets play an important role in the progress of this field, as they waive the tall order of initial investment in hardware and manpower. However, for research on autonomous aerial systems, there appears to be a relative lack of public datasets on par with those used for autonomous driving and ground robots. Thus, to fill in this gap, we conduct a data collection exercise on an aerial platform equipped with an extensive and unique set of sensors: two 3D lidars, two hardware-synchronized global-shutter cameras, multiple Inertial Measurement Units (IMUs), and especially, multiple Ultra-wideband (UWB) ranging units. The comprehensive sensor suite resembles that of an autonomous driving car, but features distinct and challenging characteristics of aerial operations. We record multiple datasets in several challenging indoor and outdoor conditions. Calibration results and ground

0 papers0 benchmarks

Lego Road image for Drone

Description:

0 papers0 benchmarks

NIAB teff phenotyping platform

Description:

0 papers0 benchmarks

datasets

download: https://zenodo.org/records/15515662?token=eyJhbGciOiJIUzUxMiJ9.eyJpZCI6IjRjOThmMzRmLTJiMzYtNDFiOC1hMzAxLTI5NGE2YTNjM2M3ZCIsImRhdGEiOnt9LCJyYW5kb20iOiIxYTJjNTBiYzAzMmJmMGFlNjU2NTlkZjdhMmZlOTVkMiJ9.8XZaxBtcoxLDJcgSdNK20aQwoF1T0VElDpaOxg1tVioUzjk1CPP_SNmIhLnj0aiagpZ4qTu5EMPHaj_MZ66t4w

0 papers0 benchmarks

datasetsOfmetric

download: https://zenodo.org/records/15515662?token=eyJhbGciOiJIUzUxMiJ9.eyJpZCI6IjRjOThmMzRmLTJiMzYtNDFiOC1hMzAxLTI5NGE2YTNjM2M3ZCIsImRhdGEiOnt9LCJyYW5kb20iOiIxYTJjNTBiYzAzMmJmMGFlNjU2NTlkZjdhMmZlOTVkMiJ9.8XZaxBtcoxLDJcgSdNK20aQwoF1T0VElDpaOxg1tVioUzjk1CPP_SNmIhLnj0aiagpZ4qTu5EMPHaj_MZ66t4w

0 papers0 benchmarks

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่‚‹้ชจ

0 papers0 benchmarks

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0 papers0 benchmarks

Burmese Handwritten Digit Dataset (BHDD)

The Burmese Handwritten Digit Dataset (BHDD) is a dataset project specifically created for recognizing handwritten Burmese digits. It is a Burmese version of MNIST dataset with a training set of 60,000 examples, and a test set of 27,561 examples.

0 papers0 benchmarksImages

SICS-155 (Phase Recognition in Small Incision Cataract Surgery Videos)

Cataract is the leading cause of blindness worldwide, most affecting life in low- and middle-income countries (LMICs). The mainly used, most appropriate, and most cost-effective cataract surgical technique for LMICs is small incision cataract surgery (SICS). While algorithms have been developed for automated video analysis of surgical performance parameters for the cataract surgical technique predominantly used in high-income settings, so far there were no datasets nor algorithms for SICS available. This MICCAI challenge introduces the first SICS video dataset and offers teams the opportunity to evaluate the effectiveness of their phase recognition algorithms. The dataset of 155 patients was recruited at Sankara Eye Hospital in India.

0 papers0 benchmarksMedical, Videos

Digital Screen | Television Dataset

Description:

0 papers0 benchmarks

Carioca 1

Carioca 1 dataset consists of 200 audios having frequency of 44 KHz

0 papers0 benchmarks
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