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Journey9ni/VLM-3R-DATA dataset hosted on Hugging Face and contributed by the HF Datasets community
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The Alzheimer's Disease Multiclass Dataset contains approximately 44,000 MRI images categorized into four distinct classes based on the severity of Alzheimer's disease. This dataset is intended for use in machine learning model training and testing. All images are skull-stripped and clean of non-brain tissue.
Dataset Structure The dataset is organized into the following four directories, each representing a different class of disease severity: NonDemented: Contains 12,800 MRI images of subjects with no signs of dementia. VeryMildDemented: Contains 11,200 MRI images of subjects with very mild symptoms of dementia. MildDemented: Contains 10,000 MRI images of subjects with mild dementia. ModerateDemented: Contains 10,000 MRI images of subjects with moderate dementia.
Image Details Total Number of Images: 44,000 Image Format: MRI scans as .JPG files Image Usage: Suitable for training and testing machine learning models focused on classifying Alzheimer's disease stages.
Disease Severity Classification The dataset follows a severity ranking system for Alzheimer's disease: NonDemented: No dementia. Very Mild Demented: Early signs of dementia, very mild symptoms. Mild Demented: Clear signs of dementia, but still mild. Moderate Demented: More pronounced symptoms of dementia, moderate severity.
This dataset is an augmented and upsampled version of the dataset below: https://www.kaggle.com/datasets/uraninjo/augmented-alzheimer-mri-dataset-v2
This dataset was upsampled as the original dataset had a large class imbalance.
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Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This dataset was created by JAYAPRAKASHPONDY
Released under CC0: Public Domain
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TwitterWorldSense: Evaluating Real-world Omnimodal Understanding for Multimodal LLMs
Jack Hong1, Shilin Yan1†, Jiayin Cai1, Xiaolong Jiang1, Yao Hu1, Weidi Xie2‡
†Project Leader
‡Corresponding Author
1Xiaohongshu Inc. 2Shanghai Jiao Tong University [🏠 Project Page] [📖 arXiv Paper] [🤗 Dataset] [🏆 Leaderboard]
🔥 News
2025.02.07 🌟 We release WorldSense, the first benchmark for real-world omnimodal understanding of MLLMs.
👀 WorldSense Overview
we… See the full description on the dataset page: https://huggingface.co/datasets/honglyhly/WorldSense.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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## Overview
Jules Dataset is a dataset for instance segmentation tasks - it contains Pallet annotations for 2,140 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
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Twitterrufimelo/securecode-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community
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TwitterAttribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
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Gopalatius/bitcoin-historical-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community
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TwitterThe dataset represents a compilation of user interaction data generated by users who participated in the project's pilot activities in Patras, Greece. Data was generated by users in the SMARTBUY app and includes information about users, stores, product categories, professions, and events.
The dataset comprises the following data: - users: user account data for the Patras pilot users - occupation: all possible occupations that the pilot users could choose from - stores: stores which participated in the Patras pilot - sel_products_cat: products uploaded to the SMARTBUY platform by retailers - events: geo-stamped and time-stamped descriptions of a user interaction event (for instance, "user_id 67 rated product_id 722 with rating 4 at location x1 at datetime y1", or "user_id 91 denoted product_id 78 as favorite at location x2 at datetime y2") - event_types: all possible event types captured by the SMARTBUY platform ('Product searches', 'Product views', 'Featured product', 'Products near you views', 'Product photos browsed', 'Product ratings', 'Clicks on Read More button to read product reviews', 'Clicks on Open map button', 'Clicks on Send this info by email button', 'Products denoted as Favorite')
Privacy-sensitive information such as user names, retailer owner names and store names and keywords searched are anonymized.
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Context
The dataset tabulates the population of Rochester by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Rochester across both sexes and to determine which sex constitutes the majority.
Key observations
There is a slight majority of female population, with 51.82% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Rochester Population by Race & Ethnicity. You can refer the same here
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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## Overview
YoloV8Corrosion is a dataset for semantic segmentation tasks - it contains Corrosion annotations for 770 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
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Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This dataset was created by SeshuRaju 🧘♂️
Released under CC0: Public Domain
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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## Overview
Sketch Detection is a dataset for object detection tasks - it contains Sketch annotations for 1,499 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
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TwitterMIT Licensehttps://opensource.org/licenses/MIT
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This dataset was created by Soham Chakote
Released under MIT
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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## Overview
Reston Trimtrack is a dataset for instance segmentation tasks - it contains Objects annotations for 648 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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## Overview
Potato Plants Diseases is a dataset for object detection tasks - it contains Leaves annotations for 2,152 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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## Overview
Food Object Detection 6 is a dataset for object detection tasks - it contains Food annotations for 2,192 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
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Twitterhttps://crehq.com/data-license/https://crehq.com/data-license/
Mountain Heritage location dataset — 4 locations in 1 states. Part of CREHQ's multi-unit intelligence platform covering retail, restaurant, financial services, and healthcare brands. Licensed access via enterprise API or dataset purchase. Training on CREHQ data is not permitted.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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## Overview
Sorted Fire Smoke Data is a dataset for object detection tasks - it contains Fire annotations for 383 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
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Twitterhttps://www.gnu.org/licenses/old-licenses/gpl-2.0.en.htmlhttps://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html
The Construction Equipment dataset is a valuable resource designed for object detection tasks, which finds potential applications within the realms of the construction and surveillance industries. Comprising 318 images, this dataset encompasses a total of 3752 annotated objects, categorized into five distinct classes, such as crane, excavator, truck, tractor and other. This dataset serves as an essential tool for developing and testing object detection algorithms to enhance safety and efficiency within these industrial domains.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Added new dataset OpenDataLog. The dataset stores detailed information regarding issues with the open data portal, new or changes to datasets on the portal as well as other information related to the City's Open Data Portal
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TwitterApache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
Journey9ni/VLM-3R-DATA dataset hosted on Hugging Face and contributed by the HF Datasets community