21 citations · 24 across the 6 of their papers we have counts for
6 papers
Autoencoder based Hybrid Multi-Task Predictor Network for Daily Open-High-Low-Close Prices Prediction of Indian Stocks
Debasrita Chakraborty, Susmita Ghosh, Ashish Ghosh
Stock prices are highly volatile and sudden changes in trends are often very problematic for traditional forecasting models to handle. The standard Long Short Term Memory (LSTM) ne…
Improving the Robustness of Federated Learning for Severely Imbalanced Datasets
Debasrita Chakraborty, Ashish Ghosh
With the ever increasing data deluge and the success of deep neural networks, the research of distributed deep learning has become pronounced. Two common approaches to achieve this…
Improved Multi-label Classification with Frequent Label-set Mining and Association
Anwesha Law, Ashish Ghosh
Multi-label (ML) data deals with multiple classes associated with individual samples at the same time. This leads to the co-occurrence of several classes repeatedly, which indicate…
Unsupervised Change Detection in Hyperspectral Images using Feature Fusion Deep Convolutional Autoencoders
Debasrita Chakraborty, Ashish Ghosh
Binary change detection in bi-temporal co-registered hyperspectral images is a challenging task due to a large number of spectral bands present in the data. Researchers, therefore,…
Transfer-Recursive-Ensemble Learning for Multi-Day COVID-19 Prediction in India using Recurrent Neural Networks
Debasrita Chakraborty, Debayan Goswami, Susmita Ghosh +2
The current COVID-19 pandemic has put a huge challenge on the Indian health infrastructure. With more and more people getting affected during the second wave, the hospitals were ov…
Integration of Autoencoder and Functional Link Artificial Neural Network for Multi-label Classification
Anwesha Law, Ashish Ghosh
Multi-label (ML) classification is an actively researched topic currently, which deals with convoluted and overlapping boundaries that arise due to several labels being active for…