8 citations · 8 across the 3 of their papers we have counts for
4 papers
Offline Handwritten Amharic Character Recognition Using Few-shot Learning
Mesay Samuel, Lars Schmidt-Thieme, DP Sharma +2
Few-shot learning is an important, but challenging problem of machine learning aimed at learning from only fewer labeled training examples. It has become an active area of research…
Improving Amharic Handwritten Word Recognition Using Auxiliary Task
Mesay Samuel Gondere, Lars Schmidt-Thieme, Durga Prasad Sharma +1
Amharic is one of the official languages of the Federal Democratic Republic of Ethiopia. It is one of the languages that use an Ethiopic script which is derived from Gee'z, ancient…
Multi-script Handwritten Digit Recognition Using Multi-task Learning
Mesay Samuel Gondere, Lars Schmidt-Thieme, Durga Prasad Sharma +1
Handwritten digit recognition is one of the extensively studied area in machine learning. Apart from the wider research on handwritten digit recognition on MNIST dataset, there are…
Handwritten Amharic Character Recognition Using a Convolutional Neural Network
Mesay Samuel Gondere, Lars Schmidt-Thieme, Abiot Sinamo Boltena +1
Amharic is the official language of the Federal Democratic Republic of Ethiopia. There are lots of historic Amharic and Ethiopic handwritten documents addressing various relevant i…