Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Identification of script from document images is an active area of research under document image processing for a multilingual/ multiscript country like India.  the real life problem of printed script identification from official Indian document images is considered and performances of different ll-known classifiers are evaluated. Two important evaluating parameters, namely, AAR (average accuracy rate) and MBT (model building time), are computed for this performance analysis. Experiment was carried out on 459 printed document images with 5-fold cross-validation. Simple Logistic model shows highest AAR of 98.9% among all. BayesNet and Random Forest model have average accuracy rate of 96.7% and 98.2% correspondingly with lost MBT of 0.09 s.
['Sk Md Obaidullah', 'Anamika Mondal', 'Nibaran Das', 'Kaushik Roy']
I am writing a research paper on a idea Script identification from printed indian document images and performance evaluation using different classifiers
[{"from": "human", "value": "I am writing a research paper on a idea Script identification from printed indian document images and performance evaluation using different classifiers"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Identification of script from document images is an active area of research under document image processing for a multilingual/ multiscript country like India.  the real life problem of printed script identification from official Indian document images is considered and performances of different ll-known classifiers are evaluated. Two important evaluating parameters, namely, AAR (average accuracy rate) and MBT (model building time), are computed for this performance analysis. Experiment was carried out on 459 printed document images with 5-fold cross-validation. Simple Logistic model shows highest AAR of 98.9% among all. BayesNet and Random Forest model have average accuracy rate of 96.7% and 98.2% correspondingly with lost MBT of 0.09 s."}]