POLLEN24_SP_Dataset
[EN] A comprehensive dataset of pollen images has been constructed. This Ground Truth termed POLLEN24_SP, comprised 32.285 pollen/particle images (captured by an expert using optical microscopy) and covers the 24 most prevalent types of pollen grains found in Spanish honeys. Twelve different pre-exi...
| Autores: | , , , |
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| Tipo de recurso: | conjunto de datos |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/221455 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/221455 |
| Access Level: | acceso abierto |
| Palabra clave: | Monofloral honey classification Pollen Classification Pollen dataset Labelling and annotating application HoneyApp Convolutional neural networks (CNN) |
| Sumario: | [EN] A comprehensive dataset of pollen images has been constructed. This Ground Truth termed POLLEN24_SP, comprised 32.285 pollen/particle images (captured by an expert using optical microscopy) and covers the 24 most prevalent types of pollen grains found in Spanish honeys. Twelve different pre-existing Convolutional Neural Networks (CNN) were evaluated in order to discern the relative frequencies of different pollen types, including our new proposals PolleNetV2 and PollenNetV2.mobile. |
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