no code implementations • 1 May 2024 • Saurabh Saini, Kapil Ahuja, Siddartha Chennareddy, Karthik Boddupalli
A competitive approach for type classification on the same dataset achieved 81%-91% performance.
no code implementations • 22 Dec 2023 • Mithun Singh, Kapil Ahuja, Milind B. Ratnaparkhe
Commonly, a natural exponential function is used for this purpose.
no code implementations • 23 Aug 2021 • Seemandhar Jain, Aditya A. Shastri, Kapil Ahuja, Yann Busnel, Navneet Pratap Singh
Due to the large sizes of data, clustering algorithm often take too much time.
no code implementations • 18 Sep 2020 • Aditya A. Shastri, Kapil Ahuja, Milind B. Ratnaparkhe, Yann Busnel
We experimentally show that we are up to 45% more accurate than HC in terms of clustering accuracy.
no code implementations • 30 Sep 2018 • Aditya A. Shastri, Kapil Ahuja, Milind B. Ratnaparkhe, Aditya Shah, Aishwary Gagrani, Anant Lal
We develop a Vector Quantized Spectral Clustering (VQSC) algorithm that is a combination of Spectral Clustering (SC) and Vector Quantization (VQ) sampling for grouping Soybean genomes.
1 code implementation • 21 May 2018 • Chandan Gautam, Ramesh Balaji, K Sudharsan, Aruna Tiwari, Kapil Ahuja
In this paper, we present a multiple kernel learning approach for the One-class Classification (OCC) task and employ it for anomaly detection.
no code implementations • 17 Jan 2017 • Chandan Gautam, Aruna Tiwari, Sundaram Suresh, Kapil Ahuja
This paper presents an online learning with regularized kernel based one-class extreme learning machine (ELM) classifier and is referred as online RK-OC-ELM.
no code implementations • 15 Jan 2017 • Aditya A. Shastri, Deepti Tamrakar, Kapil Ahuja
We apply our two new descriptors on all images of the IRMA database for density wise classification, and compare with the standard descriptors.