The Nomenclature of Territorial Units for Statistics (NUTS) is a hierarchical classification of statistical regions and subdivides the EU economic territory into regions of four different levels (NUTS 0, 1, 2 and 3, moving respectively from larger to smaller territorial units). NUTS 1 is the most aggregated level. An additional Country level (NUTS 0) is also available for countries where the the nation at statistical level does not coincide with the administrative boundaries. For example Mt Athos in Greece and Mellum and Minsener Ogg in Germany. The NUTS classification has been officially established through Regulation (EC) No 2016/2066 of the European Parliament and of the Council and its amendments. A non-official NUTS-like classification has been defined for the EFTA countries and candidate countries. An introduction to the NUTS classification is available here: http://ec.europa.eu/eurostat/web/nuts/overview. The datasets are based on: EuroBoundaryMap (EBM) from EuroGeographics (scale of 1:100.000), Global Administrative Unit Layer (GAUL) country data from UN/FAO, data from the National Statistical Institute of Turkey (TurkStat) (might vary for different years). The different scale levels were derived by generalisation of the 100K scale. The public datasets are available under the Download link indicated below. Available scales are: 100k, 1M, 3M, 10M, 20M, 60M. Date of the NUTS regions are currently available for the years 2003, 2006, 2010, 2013, 2016 and 2021. The full datasets are available via the EC restricted download link. Here six scale ranges (100K, 1M, 3M, 10M and 20M, 60M) are available. Coverage is the economic territory of the EU, EFTA countries and candidate countries as in the respective year.

The Nomenclature of Territorial Units for Statistics (NUTS) were drawn up by Eurostat in order to define territorial units for the production of comparable regional statistics across the European Union. The NUTS classification has been used in EU legislation since 1988, but it was only in 2003 that the EU Member States, the European Parliament and the Commission established the NUTS regions within a legal framework (Regulation (EC) No 1059/2003). For the purpose of comparability, NUTS classifications remain stable for at least three years, as specified by the regulation. However, if national interests require a change in the regional breakdown of a country, the country concerned may notify the European Commission, who will then carry out the required amendments at the end of a period of stability, according to the rules of the NUTS regulation. Changes made under the 2014 Local Government Act prompted a revision to the Irish NUTS 2 and NUTS 3 Regions. The NUTS 3 boundaries were amended on 21st of November 2016 and have been given legal status under the Commission Regulation (Regulation (EC) No 2066/2016). The main changes at NUTS 3 level are the transfer of South Tipperary from the South-East into the Mid-West NUTS 3 region and the movement of Louth from the Border to the Mid-East NUTS 3 Region. The NUTS 3 boundaries are available as generalised (20/50/100m) and ungeneralised. The NUTS coding scheme and naming structure were decided by Eurostat.The new NUTS 2 and NUTS 3 structure and classification are displayed in a table on the CSO website https://www.cso.ie/en/methods/revnuts23/

Nuts Classification

## Overview

Nuts Classification is a dataset for classification tasks - it contains Nuts annotations for 600 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).

dataset of 10 types of tree nuts. 1163train, 50 test,50 validation files 224 X 224 X 3 jpg format. Also includes a tensorflow trained model nuts)100.0.hs that achieved an F1 score of 100%. A csv file tree nuts.csv is also provided

This dataset represents the regions for levels 1, 2 and 3 of the Nomenclature of Territorial Units for Statistics (NUTS) for 2016. The NUTS nomenclature is a hierarchical classification of statistical regions and subdivides the EU economic territory into regions of four different levels (NUTS , 1, 2 and 3, moving respectively from larger to smaller territorial units). NUTS 1 is the most aggregated level. An additional Country level (NUTS 0) is also available for countries where the the nation at statistical level does not coincide with the administrative boundaries. For example Mt Athos in Greece and Mellum and Minsener Ogg in Germany. The NUTS classification has been officially established through Regulation (EC) No 2016/2066 of the European Parliament and of the Council and its amendments. A non-official NUTS-like classification has been defined for the EFTA countries and candidate countries. An introduction to the NUTS classification is available here: http://ec.europa.eu/eurostat/web/nuts/overview. This dataset has been created mainly from the EuroBoundary Map v 12 (Eurogeographics) and geographic information from TurkStat for Turkey. The public dataset is available under the Download link indicated below. Available scales are 1M, 3M, 10M, 20M, 60M). The full dataset is available via the EC restricted download link under GISCO.NUTS_2016. Here six scale ranges (100K, 1M, 3M, 10M and 20M, 60M) are available. Coverage is the economic territory of the EU, EFTA countries and candidate countries as in 2013.

This dataset contains the Nomenclature of territorial units for statistics Units (NUTS) defined and updated in 2021 from Eurostat. More details at https://ec.europa.eu/eurostat/web/nuts/background

The 'GISCO NUTS 2021' data set represents the NUTS 2021 regulation and statistical regions by means of multipart polygon, polyline and point topology. The NUTS geographical information is completed by attribute tables and a set of cartographic help lines to better visualize multipart polygonal regions.

The NUTS nomenclature is a hierarchical classification of statistical regions defined by Eurostat. The NUTS classification subdivides the EU economic territory into 3 statistical levels. The NUTS 2021 classification has been established through the Commission Delegated Regulation 2019/1755, which entered into force on 8th August 2019 and applies from 1st January 2021. A non official NUTS-like classification has been defined for the EFTA countries and the candidate countries.

At present, six scale ranges (100K, 1M, 3M, 10M and 20M, 60M) are maintained in the GISCO geodatabase. The polygon and boundary classes delineate the regions, while the points provide an anchor for each region. Associated tables contain basic information such as the name of the region. The public data set will be available at 1M, 3M, 10M, 20M, 60M, while the full data set at 100K is restricted.

The data set covers EU Member States, EFTA countries, EU candidate countries and the UK. Following the departure of the UK from the European Union, the UK is no longer flagged as an EU Member State but retains its place in the NUTS and statistical regions data set.

This metadata only refers to the full NUTS2021 dataset (polygons) at 100k (NUTS_RG_100K_2021), which is derived from the EuroBoundary Map 2020 (EBM2020) from Eurogeographics as well as GISCO NUTS 2016 (from Türkiye). With the dataset it is also provided the table NUTS_AT_2021.dbf and an excel file NUTS2016-NUTS2021.xlsx with the list of changes between 2016 and 2021.

IMPORTANT NOTE: Additional information, including the conditions of use and acknowledgement notice is included in the document provided with the dataset "GISCO NUTS 2021 Additional Information.pdf". Public access to this data set is restricted due to intellectual property rights. It shall only be used internally by the EEA, its ETCs and subcontractors working on behalf of the EEA. This metadata has been slightly adapted from the original metadata information provided by Eurostat (European Commission) and is to be used only for internal EEA purposes.

An introduction to the NUTS classification is available here: http://ec.europa.eu/eurostat/web/nuts/overview.

NUTS2 boundaries generalised to 20m.The Nomenclature of Territorial Units for Statistics (NUTS) were drawn up by Eurostat in order to define territorial units for the production of regional statistics across the European Union. The NUTS classification has been used in EU legislation since 1988, but it was only in 2003 that the EU Member States, the European Parliament and the Commission established the NUTS regions within a legal framework (Regulation (EC) No 1059/2003).The Irish NUTS 3 regions comprise the eight Regional Authorities established under the Local Government Act, 1991 (Regional Authorities) (Establishment) Order, 1993 which came into operation on January 1st 1994. The NUTS 2 regions, which were proposed by Government and agreed to by Eurostat in 1999, are groupings of the Regional Authorities.This dataset is provided by Tailte Éireann .hidden { display: none }

NUTS3 boundaries ungeneralised. The Nomenclature of Territorial Units for Statistics (NUTS) were drawn up by Eurostat in order to define territorial units for the production of regional statistics across the European Union. The NUTS classification has been used in EU legislation since 1988, but it was only in 2003 that the EU Member States, the European Parliament and the Commission established the NUTS regions within a legal framework (Regulation (EC) No 1059/2003). The Irish NUTS 3 regions comprise the eight Regional Authorities established under the Local Government Act, 1991 (Regional Authorities) (Establishment) Order, 1993 which came into operation on January 1st 1994. The NUTS 2 regions, which were proposed by Government and agreed to by Eurostat in 1999, are groupings of the Regional Authorities.This dataset is provided by Tailte Éireann

The Tree Nuts Image Classification Dataset includes over 1,300 high-quality RGB images of 10 different tree nut types, including almonds, walnuts, pecans, and hazelnuts. Designed for computer vision and machine learning tasks, it helps improve classification accuracy and quality control in the nut industry.

The Nomenclature of Territorial Units for Statistics (NUTS) was established by Eurostat to provide a single uniform breakdown of territorial units for the production of regional statistics for the European Union.

This dataset represents the regions for levels 1, 2 and 3 of the Nomenclature of Territorial Units for Statistics (NUTS) for 2016. The NUTS nomenclature is a hierarchical classification of statistical regions and subdivides the EU economic territory into regions of four different levels (NUTS , 1, 2 and 3, moving respectively from larger to smaller territorial units). NUTS 1 is the most aggregated level. An additional Country level (NUTS 0) is also available for countries where the the nation at statistical level does not coincide with the administrative boundaries. For example Mt Athos in Greece and Mellum and Minsener Ogg in Germany. The NUTS classification has been officially established through Regulation (EC) No 2016/2066 of the European Parliament and of the Council and its amendments. A non-official NUTS-like classification has been defined for the EFTA countries and candidate countries. An introduction to the NUTS classification is available here: http://ec.europa.eu/eurostat/web/nuts/overview. This dataset has been created mainly from the EuroBoundary Map v 12 (Eurogeographics) and geographic information from TurkStat for Türkiye. The public dataset is available at 1M, 3M, 10M, 20M, 60M, while the full dataset at 100K is restricted. Coverage is the economic territory of the EU, EFTA countries and candidate countries as in 2016. This metadata only refers to a pre-release version of the full nuts 2016 dataset at 100k (it does not contain Albanian boundaries) and shall only be used internally by the EEA following the conditions stated in the document "GISCO-LicenseconditionsforEGdatasets.pdf" provided with the dataset. This metadata has been slightly adapted from the original metadata file provided by Eurostat (European Commission) and is to be used only for internal EEA purposes. For reference, the original metadata file provided by ESTAT (NUTS_2016.xml) is also available for download together with the dataset. The public datasets, at smaller scales, are available on http://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units/nuts#nuts16.

The NUTS classification (Nomenclature of Territorial Units for Statistics) is a hierarchical system for dividing the economic territory of the European Union for the following purposes: - The collection, development and harmonisation of European regional statistics. - Socio-economic analysis of the regions. NUTS 1: main socio-economic regions NUTS 2: basic regions for the implementation of regional policies NUTS 3: small regions for specific diagnoses.

Structural business statistics (SBS) describe the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors).
The EU Member States transmit SBS annually to the European Commission (Eurostat) based on European legislation.
SBS covers all activities of the business economy with the exception of agricultural activities, public administration and largely non-market services such as education and health. The data is provided by all EU Member States, Iceland, Norway and Switzerland, some candidate and potential candidate countries.
Most data is collected by National Statistical Institutes (NSIs) through statistical surveys, business registers or various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K).
Member States apply various statistical methods - such as grossing up, model based estimation or different forms of imputation - according to the data source to ensure the quality of SBS produced.

Main characteristics (variables) of the SBS data category:

• "Business Demographic" variables (e.g. Number of active enterprises)
• "Output related" variables (e.g. Net turnover, Value added)
• "Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Purchases of goods and services); capital input (e.g. Gross investments)

All SBS characteristics are published on Eurostat’s website in tables. An example of the existent tables is presented below:

• Annual enterprise statistics broken down by size classes: SBS data is published by country and employment size class (0-9; 10-19; 20-49; 50-249; 250 persons employed or more), again broken down by detailed economic activity, group level (3-digits). Additional size classes 0-1 and 2-9 persons employed are available for NACE Rev 2 Sections F to J, L to N and P to R and divisions S95 and S96 only for variables "Number of active enterprises" and "Number of employees and self-employed persons". For trade (NACE Rev 2 Section G) a supplementary breakdown by size class of turnover is available.
• Annual enterprise statistics: SBS data is published by country and detailed economic activity (NACE Rev 2) class level (4-digits) and special aggregates.
• Annual/bi-annual business services statistics: "Net turnover by product" and "Net turnover by residence of client" are published by country and detailed down to NACE Rev 2 group level (3-digits). The statistics on “Net turnover by product” permit analysis of products' relative importance in the turnover, consistency of product level statistics and product specialisation. On the other hand, information on “Turnover by residence of client” enable analysis of the type and location of clients and client specialisation.
• Annual regional statistics: Three characteristics are published by NUTS-2 country regions and detailed on NACE Rev 2 division level (2-digits).

Starting from the reference year 2023, voluntary data in new size classes called Small-Mid Caps (i.e. 250-499 and 500 and more persons employed) of selected SBS variables are transmitted by Member States and published together with legal size classes in a new Eurostat table.

More information on the contents of different tables and the detail level and breakdowns required starting with the reference year 2021, is defined in Commission Regulation 2019/2152 (‘EBS Regulation’) and Regulation (EU) 2020/1197 (‘EBS General Implementing Act’) concerning European Business Statistics.

Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available in the Annexes.

This file provides the correspondence table between EUROSTAT NUTS3 classification and the adapted regional classification used by the RISIS-KNOWMAK project. This regional classification fits the structure of knowledge production in Europe and addresses some knowm problems of the NUTS3 classification, such as the treatment of large agglomerations, while remaining fully compatible with the EUROSTAT NUTS regional classification. This compatibility allows combining all KNOWMAK data with regional statistics (at NUTS3 level, 2021 edition) from EUROSTAT.

More precisely, the classification includes EUROSTAT metropolitan regions (based on the aggregation of NUTS3-level regions) and NUTS2 regions for the remaining areas; further, a few additional centers for knowledge production, like Oxford and Leuven, have been singled out at NUTS3 level. The resulting classification is therefore more fine-grained than NUTS2 in the areas with sizeable knowledge production, but at the same time recognizes the central role of metropolitan areas in knowledge production. While remaining compatible with NUTS, the classification allows addressing two well-known shortcomings: a) the fact that some large cities are split between NUTS regions (London) and b) the fact that NUTS3 classification in some countries includes many very small regions, as in the case of Germany

The Nomenclature of Territorial Units for Statistics (NUTS) were drawn up by Eurostat in order to define territorial units for the production of regional statistics across the European Union. The NUTS classification has been used in EU legislation since 1988, but it was only in 2003 that the EU Member States, the European Parliament and the Commission established the NUTS regions within a legal framework (Regulation (EC) No 1059/2003).

The Irish NUTS 3 regions comprise the eight Regional Authorities established under the Local Government Act, 1991 (Regional Authorities) (Establishment) Order, 1993 which came into operation on January 1st 1994. The NUTS 2 regions, which were proposed by Government and agreed to by Eurostat in 1999, are groupings of the Regional Authorities.

GeoJSON data on the NUTS (Nomenclature of territorial units for statistics) and Statistical regions of the EU.

As explained here, the NUTS are a hierarchical system divided into 3 levels: NUTS 1: major socio-economic regions NUTS 2: basic regions for the application of regional policies NUTS 3: small regions for specific diagnoses

The NUTS legislation is periodically amended; this version is from 2021.

NUTS3 boundaries ungeneralised. The Nomenclature of Territorial Units for Statistics (NUTS) were drawn up by Eurostat in order to define territorial units for the production of regional statistics across the European Union. The NUTS classification has been used in EU legislation since 1988, but it was only in 2003 that the EU Member States, the European Parliament and the Commission established the NUTS regions within a legal framework (Regulation (EC) No 1059/2003). The Irish NUTS 3 regions comprise the eight Regional Authorities established under the Local Government Act, 1991 (Regional Authorities) (Establishment) Order, 1993 which came into operation on January 1st 1994. The NUTS 2 regions, which were proposed by Government and agreed to by Eurostat in 1999, are groupings of the Regional Authorities.This dataset is provided by Tailte Éireann

Background: Nuts are nutrient-dense foods that contribute to healthier eating. Food image datasets enable artificial intelligence (AI) powered diet-tracking apps to help people monitor daily eating patterns.

Aim: This study aimed to create an image dataset of commonly consumed nut types and use it to build an AI computer vision model to automate nut type classification tasks.

Methods: iPhone 11 was used to take photos of 11 nut types—almond, brazil nut, cashew, chestnut, hazelnut, macadamia, peanut, pecan, pine nut, pistachio, and walnut. The dataset contains 2,200 images, 200 per nut type. The dataset was randomly split into the training (60% or 1,320 images), validation (20% or 440 images), and test sets (20% or 440 images). A neural network model was constructed and trained using transfer learning and other computer vision techniques—data augmentation, mixup, normalization, label smoothing, and learning rate optimization.

Results: The trained neural network model correctly predicted 338 out of 440 images (40 per nut type) in the validation set, achieving 99.55% accuracy. Moreover, the model classified the 440 images in the test set with 100% accuracy.

Conclusion: This study built a nut image dataset and used it to train a neural network model to classify images by nut type. The model achieved near-perfect accuracy on the validation and test sets, demonstrating the feasibility of automating nut type classification using smartphone photos. Being made open-source, the dataset and model can assist the development of diet-tracking apps that facilitate users’ adoption and adherence to a healthy diet.

Please cite the following peer-reviewed publication if you use this dataset: An R, Perez-Cruet J, Wang J. We got nuts! Use deep neural networks to classify images of common edible nuts. 2022. Nutrition and Health. In press.

Labeled Nuts images suitable for training and evaluating computer vision and deep learning models.