Ayaz, FurkanAri, AliHanbay, Davut2024-08-042024-08-042017978-1-5386-1880-6https://hdl.handle.net/11616/981002017 International Artificial Intelligence and Data Processing Symposium (IDAP) -- SEP 16-17, 2017 -- Malatya, TURKEYPlant recognition from their leaves has become a popular area in the machine learning and image processing. In this study 7 different types of apricot trees were determined and classified by using their leaves. At first leaves images were preprocessed. After than each image was scanned by 5x5 overlapping filter and median values of each filter process were recorded to represent the leaves. After than filtered each image was scanned by 2x2 overlapping filter and maximum values of each shifting step was recorded. The dimension of each image reduced to it half. Histogram of these uniform patterns were evaluated. These features were applied as input to the Artificial Neural Network (ANN) and 7 types of apricot were classified with the accuracy is 98.6 %.trinfo:eu-repo/semantics/closedAccessLeaf RecognitionUniform PatternsArtificial Neural NetworkConference Object2-s2.0-85039923391N/AWOS:000426868700080N/A