21 citations · 30 across the 10 of their papers we have counts for
4 papers · 1 filter
Multi-Fake Evolutionary Generative Adversarial Networks for Imbalance Hyperspectral Image Classification
Tanmoy Dam, Nidhi Swami, Sreenatha G. Anavatti +1
This paper presents a novel multi-fake evolutionary generative adversarial network(MFEGAN) for handling imbalance hyperspectral image classification. It is an end-to-end approach i…
Rainfall-runoff prediction using a Gustafson-Kessel clustering based Takagi-Sugeno Fuzzy model
Subhrasankha Dey, Tanmoy Dam
A rainfall-runoff model predicts surface runoff either using a physically-based approach or using a systems-based approach. Takagi-Sugeno (TS) Fuzzy models are systems-based approa…
Does Adversarial Oversampling Help us?
Tanmoy Dam, Md Meftahul Ferdaus, Sreenatha G. Anavatti +2
Traditional oversampling methods are generally employed to handle class imbalance in datasets. This oversampling approach is independent of the classifier; thus, it does not offer…
Improving ClusterGAN Using Self-Augmented Information Maximization of Disentangling Latent Spaces
Tanmoy Dam, Sreenatha G. Anavatti, Hussein A. Abbass
Since their introduction in the last few years, conditional generative models have seen remarkable achievements. However, they often need the use of large amounts of labelled infor…