Prasun Chakrabarti

TL;DR: A cascaded ensembled network that uses an integration of ConvNet and handcrafted features based multi-layer perceptron is proposed in this work and it is demonstrated that accuracy of ensembleled deep learning model is improved to 98.3% from 85.3%.

TL;DR: In this paper, the results have been computed based on (i) full features, (ii) correlation-based feature selection, (iii) Wrapper method feature selection and (iv) Least absolute shrinkage and selection operator regression, (v) synthetic minority over-sampling technique with least absolute shrinkages and operator regression selected features, and (vi) Synthetic minority over sampling technique with full features.

TL;DR: In this paper, two approaches are used to implement classification models, i.e. 3-layer CNN and RNN-LSTM, and SVM (Sigmoid, Polynomial & Gaussian Kernel).

TL;DR: An adaptive neuro-fuzzy inference system (ANFIS) maximum power point tracking (MPPT) controller for grid-connected doubly fed induction generator (DFIG)-based wind energy conversion systems (WECS) aims at extracting maximum power from the wind by tracking the maximum power peak regardless of wind speed.

TL;DR: This article indicated that the J48 decision tree classifier is the appropriate machine learning-based classifier for optimum breast cancer prognosis.