B
Baikunth Nath
Researcher at University of Melbourne
Publications - 30
Citations - 1130
Baikunth Nath is an academic researcher from University of Melbourne. The author has contributed to research in topics: Hidden Markov model & Feature vector. The author has an hindex of 14, co-authored 30 publications receiving 1025 citations.
Papers
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Journal ArticleDOI
A fusion model of HMM, ANN and GA for stock market forecasting
TL;DR: A fusion model by combining the Hidden Markov Model (HMM), Artificial Neural Networks (ANN) and Genetic Algorithms (GA) to forecast financial market behaviour is proposed and implemented.
Proceedings ArticleDOI
Stock market forecasting using hidden Markov model: a new approach
Md. Rafiul Hassan,Baikunth Nath +1 more
TL;DR: HMM offers a new paradigm for stock market forecasting, an area that has been of much research interest lately, and is presented for forecasting stock price for interrelated markets.
Journal ArticleDOI
Layered Approach Using Conditional Random Fields for Intrusion Detection
TL;DR: It is demonstrated that high attack detection accuracy can be achieved by using Conditional Random Fields and high efficiency by implementing the Layered Approach and the proposed system is robust and is able to handle noisy data without compromising performance.
Proceedings ArticleDOI
Automatic Detection of Vascular Bifurcations and Crossovers from Color Retinal Fundus Images
TL;DR: This paper proposes an efficient method to detect vascular bifurcation and crossover points based on the vessel geometrical features by segmenting the blood vessels from the color retinal RGB image, and applying the morphological thinning operation to find the vessel centerline.
Proceedings ArticleDOI
Blood Vessel Segmentation from Color Retinal Images using Unsupervised Texture Classification
TL;DR: A new method of texture based vessel segmentation using Gaussian and L*a*b* perceptually uniform color spaces with original RGB for texture feature extraction on retinal images and achieving 84.37% sensitivity and 99.61% specificity.