Datasets:

yuqingXing
/

leave_data

@@ -9,34 +9,32 @@ size_categories:
 - 1M<n<10M
 ---
 Description:
-One-hundred plant species leaves dataset
 The dataset is derived from this paper: Charles Mallah, James Cope, James Orwell. Plant Leaf Classification Using Probabilistic Integration of Shape, Texture and Margin Features. Signal Processing, Pattern Recognition and Applications, in press. 2013.
 Sources:
-(a) Original owners of colour Leaves Samples:
  James Cope, Thibaut Beghin, Paolo Remagnino, Sarah Barman.
  The colour images are not included.
  The Leaves were collected in the Royal Botanic Gardens, Kew, UK.
  email: james.cope@kingston.ac.uk
-(b) This dataset consists of work carried out by James Cope, Charles Mallah, and James Orwell.
  Donor of the database:
   Charles Mallah, charles.mallah@kingston.ac.uk; James Cope, james.cope@kingston.ac.uk.
- Dataset Information:
  The original data directory contains the binary images (masks) of the leaf samples (colour images not included). There are three features for each image: Shape, Margin and Texture. For each feature, a 64 element vector is given per leaf sample. These vectors are taken as a contiguous descriptor (for shape) or histograms (for texture and margin). So, there are three different files, one for each feature problem:
 ‘data_Sha_64.txt’ -> prediction based on shape
 ‘data_Tex_64.txt’ -> prediction based on texture
 ‘data_Mar_64.txt’ -> prediction based on margin
-Each row has a 64-element feature vector followed by the Class label. There is a total of 1600 samples with 16 samples per leaf class (100 classes), and no missing values.
 References:

 - 1M<n<10M
 ---
 Description:
+ One-hundred plant species leaves dataset
 The dataset is derived from this paper: Charles Mallah, James Cope, James Orwell. Plant Leaf Classification Using Probabilistic Integration of Shape, Texture and Margin Features. Signal Processing, Pattern Recognition and Applications, in press. 2013.
 Sources:
+ (a) Original owners of colour Leaves Samples:
  James Cope, Thibaut Beghin, Paolo Remagnino, Sarah Barman.
  The colour images are not included.
  The Leaves were collected in the Royal Botanic Gardens, Kew, UK.
  email: james.cope@kingston.ac.uk
+ (b) This dataset consists of work carried out by James Cope, Charles Mallah, and James Orwell.
  Donor of the database:
   Charles Mallah, charles.mallah@kingston.ac.uk; James Cope, james.cope@kingston.ac.uk.
+Dataset Information:
  The original data directory contains the binary images (masks) of the leaf samples (colour images not included). There are three features for each image: Shape, Margin and Texture. For each feature, a 64 element vector is given per leaf sample. These vectors are taken as a contiguous descriptor (for shape) or histograms (for texture and margin). So, there are three different files, one for each feature problem:
 ‘data_Sha_64.txt’ -> prediction based on shape
 ‘data_Tex_64.txt’ -> prediction based on texture
 ‘data_Mar_64.txt’ -> prediction based on margin
+ Each row has a 64-element feature vector followed by the Class label. There is a total of 1600 samples with 16 samples per leaf class (100 classes), and no missing values.
 References: