Cargando…
WE3DS: An RGB-D Image Dataset for Semantic Segmentation in Agriculture
Smart farming (SF) applications rely on robust and accurate computer vision systems. An important computer vision task in agriculture is semantic segmentation, which aims to classify each pixel of an image and can be used for selective weed removal. State-of-the-art implementations use convolutional...
Autores principales: | Kitzler, Florian, Barta, Norbert, Neugschwandtner, Reinhard W., Gronauer, Andreas, Motsch, Viktoria |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007111/ https://www.ncbi.nlm.nih.gov/pubmed/36904917 http://dx.doi.org/10.3390/s23052713 |
Ejemplares similares
-
Multi-scale fusion for RGB-D indoor semantic segmentation
por: Jiang, Shiyi, et al.
Publicado: (2022) -
RGB-D-Based Pose Estimation of Workpieces with Semantic Segmentation and Point Cloud Registration
por: Xu, Hui, et al.
Publicado: (2019) -
Fast Detection of Tomato Sucker Using Semantic Segmentation Neural Networks Based on RGB-D Images
por: Giang, Truong Thi Huong, et al.
Publicado: (2022) -
In Situ 3D Segmentation of Individual Plant Leaves Using a RGB-D Camera for Agricultural Automation
por: Xia, Chunlei, et al.
Publicado: (2015) -
Dataset for flood area recognition with semantic segmentation
por: Intizhami, Naili Suri, et al.
Publicado: (2023)