In recent years, deep learning has evolved as a rapidly growing and stimulating field of
machine learning and has redefined state-of-the-art performances in a variety of …

Semantic labelling of remote sensing images, technically termed as remote sensing scene
classification, plays significant role in understanding huge volume of complex remote …

Social media is Internet‐based by design, allowing people to share content quickly via
electronic means. People can openly express their thoughts on social media sites such as …

Multivariate time series classification is a machine learning task with increasing importance
due to the proliferation of information sources in different domains (economy, health, energy …

In this paper, we propose MUSE-RNN, a multilayer self-evolving recurrent neural network
model for real-time classification of streaming data. Unlike the existing approaches, MUSE …

Health issues of individuals has to be observed and diagnosed carefully as well as at the
early stages and treatment has to be given using suitable medicines. Many health disorders …

The timely and accurate prediction of remote sensing data is of utmost importance especially
in a situation where the predicted data is utilized to provide insights into emerging issues …

Aerial scene classification using convolutional neural network (CNN) has gained substantial
research interest during last few years. The performance of these deep models is found to …

With the increasing demand of product supply, manufacturers are in urgent need of online
tool condition monitoring (TCM) without compromising with the maintenance cost in terms of …

Catastrophic forgetting of previously acquired knowledge is a major setback suffered by the
neural networks (NNs) when these are trained on tasks in sequential fashion. The NN …