Grantha Palm Leaf Dataset Consistute of Grantha characters extracted from palm leaf images. Grantha characters are characters used in the southern part of India to write the Sanskrit language. Sanskrit has been the official language in Ancient India. Many valuable cultural and literary works of ancient India exist in the form of palm-leaf documents. These palm leaf images are collected from the Oriental Research Institute under the University of Kerala. Grantha dataset constitutes of 3900 character images of 39 classes of Grantha characters. These characters are manually extracted into 39 classes. These folders can be used for testing the efficiency of character recognition algorithms
Dzongkha, the national language of Bhutan, has limited resources available for Natural Language Proc...
Tamil characters are of historical significance. The shapes of the character and its writing continu...
Analysis of ancient Khmer documents can be quite challenging due to the elaborated shape of Khmer ha...
Grantha Palm Leaf Dataset Consistute of Grantha characters extracted from palm leaf images. Grantha ...
Grantha Palm leaf images are palm leaf images collected from the Oriental Research Institute at the ...
This dataset consists of manually segmented grantha characters from palmleaflets.Grantha characters ...
This dataset consists of manually segmented grantha characters from palmleaflets.Grantha characters ...
Abstract — This paper presents a novel approach to recognize Grantha, an ancient script in South Ind...
Cite this dataset as: Ferdous J., Karmaker S., Rabby A.K.M.S.A., Hossain S. (2021) MatriVasha: A Mul...
This dataset, BanglaLekha-Isolated, is a collection of Bangla handwritten isolated character samples...
A benchmark dataset is always required for any classification or recognition system. To the best of ...
A benchmark dataset is always required for any classification or recognition system. To the best of ...
This dataset is an extensive collection of approximately 80,000 Bangla character images meticulously...
The dataset titled "Dataset of Handwritten Chakma Alphabet" contains 33 different Chakma h...
Research in character recognition is very popular for various application potentials in banks, post ...
Dzongkha, the national language of Bhutan, has limited resources available for Natural Language Proc...
Tamil characters are of historical significance. The shapes of the character and its writing continu...
Analysis of ancient Khmer documents can be quite challenging due to the elaborated shape of Khmer ha...
Grantha Palm Leaf Dataset Consistute of Grantha characters extracted from palm leaf images. Grantha ...
Grantha Palm leaf images are palm leaf images collected from the Oriental Research Institute at the ...
This dataset consists of manually segmented grantha characters from palmleaflets.Grantha characters ...
This dataset consists of manually segmented grantha characters from palmleaflets.Grantha characters ...
Abstract — This paper presents a novel approach to recognize Grantha, an ancient script in South Ind...
Cite this dataset as: Ferdous J., Karmaker S., Rabby A.K.M.S.A., Hossain S. (2021) MatriVasha: A Mul...
This dataset, BanglaLekha-Isolated, is a collection of Bangla handwritten isolated character samples...
A benchmark dataset is always required for any classification or recognition system. To the best of ...
A benchmark dataset is always required for any classification or recognition system. To the best of ...
This dataset is an extensive collection of approximately 80,000 Bangla character images meticulously...
The dataset titled "Dataset of Handwritten Chakma Alphabet" contains 33 different Chakma h...
Research in character recognition is very popular for various application potentials in banks, post ...
Dzongkha, the national language of Bhutan, has limited resources available for Natural Language Proc...
Tamil characters are of historical significance. The shapes of the character and its writing continu...
Analysis of ancient Khmer documents can be quite challenging due to the elaborated shape of Khmer ha...