Stage-Wise Categorization and Prediction of Diabetic Retinopathy Using Ensemble Learning and 2D-CNN

Diabetic Eye Disease(DED)is a fundamental cause of blindness in human beings in the medical world.Different techniques are proposed to forecast and examine the stages in Prognostication of Diabetic Retinopathy(DR).The Machine Learning(ML)and the Deep Learning(DL)algorithms are the predomi-nant techniques to project and explore the images of DR.Even though some solu-tions were adapted to challenge the cause of DR disease,still there should be an efficient and accurate DR prediction to be adapted to refine its performance.In this work,a hybrid technique was proposed for classification and prediction of DR.The proposed hybrid technique consists of Ensemble Learning(EL),2 Dimensional-Conventional Neural Network(2D-CNN),Transfer Learning(TL)and Correlation method.Initially,the Stochastic Gradient Boosting(SGB)EL method was used to predict the DR.Secondly,the boosting based EL method was used to predict the DR of images.Thirdly 2D-CNN was applied to categorize the various stages of DR images.Finally,the TL was adopted to transfer the clas-sification prediction to training datasets.When this TL was applied,a new predic-tion feature was increased.From the experiment,the proposed technique has achieved 97.8%of accuracy in prophecies of DR images and 98%accuracy in grading of images.The experiment was also extended to measure the sensitivity(99.6%)and specificity(97.3%)metrics.The predicted accuracy rate was com-pared with existing methods.

Efficient Realization of Vinculum Vedic BCD Multipliers for High Speed Applications

Decimal multipliers play an important role in our day to day life for commercial, financial and tax applications. Every processor multiplier acts as the basic building block which decides the performance of processor. Time and again research is going on to design high-performance, low-latency BCD multiplier architectures. This paper proposes a new approach to BCD multiplication using vinculum number system. The key feature of the proposed architecture uses entirely a new one digit ROM based BCD multiplier that uses vinculum numbers as operands. Using this one digit BCD multiplier, an N digit BCD multiplier is built by using the vedic vertical cross wire method (Urdhav Triyagbhyam). We have also used our proposed multi operand VBCD Adder (Vinculum BCD Adder) [my paper 26] to add the partial products. In this paper, we show that this approach is a promising alternative to conventional BCD multiplication or other decimal multiplication methods that use alternative decimal representations like 5211, 4221, Xs3 etc.