most citedA One class Classifier based Framework using SVDD : Application to an Imbalanced Geological Dataset

5 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2023

Communication Trade-offs in Federated Learning of Spiking Neural Networks

Soumi Chaki, David Weinberg, Ayca Özcelikkale

Spiking Neural Networks (SNNs) are biologically inspired alternatives to conventional Artificial Neural Networks (ANNs). Despite promising preliminary results, the trade-offs in th…

cs.LG20165 cited

A One class Classifier based Framework using SVDD : Application to an Imbalanced Geological Dataset

Soumi Chaki, Akhilesh Kumar Verma, Aurobinda Routray +2

Evaluation of hydrocarbon reservoir requires classification of petrophysical properties from available dataset. However, characterization of reservoir attributes is difficult due t…

cs.LG20161 cited

A Novel Framework based on SVDD to Classify Water Saturation from Seismic Attributes

Soumi Chaki, Akhilesh Kumar Verma, Aurobinda Routray +2

Water saturation is an important property in reservoir engineering domain. Thus, satisfactory classification of water saturation from seismic attributes is beneficial for reservoir…

cs.LG2016

A novel multiclassSVM based framework to classify lithology from well logs: a real-world application

Soumi Chaki, Aurobinda Routray, William K. Mohanty +1

Support vector machines (SVMs) have been recognized as a potential tool for supervised classification analyses in different domains of research. In essence, SVM is a binary classif…

cs.LG2016

Development of a hybrid learning system based on SVM, ANFIS and domain knowledge: DKFIS

Soumi Chaki, Aurobinda Routray, William K. Mohanty +1

This paper presents the development of a hybrid learning system based on Support Vector Machines (SVM), Adaptive Neuro-Fuzzy Inference System (ANFIS) and domain knowledge to solve…