Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Bhaskar Dhariyal"'
Autor:
Maria Frizzarin, Giulio Visentin, Alessandro Ferragina, Elena Hayes, Antonio Bevilacqua, Bhaskar Dhariyal, Katarina Domijan, Hussain Khan, Georgiana Ifrim, Thach Le Nguyen, Joe Meagher, Laura Menchetti, Ashish Singh, Suzy Whoriskey, Robert Williamson, Martina Zappaterra, Alessandro Casa
In April 2022, the Vistamilk SFI Research Centre organized the second edition of the "International Workshop on Spectroscopy and Chemometrics - Applications in Food and Agriculture". Within this event, a data challenge was organized among participant
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a73b3c6b1552a51e3cec651bf90785fe
Publikováno v:
ICDM (Workshops)
The UEA Multivariate Time Series Classification (MTSC) archive released in 2018 provides an opportunity to evaluate many existing time series classifiers on the MTSC task. Nevertheless, although many new TSC approaches were proposed recently, a compr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6166a3ea8327a878670a42d2895019b7
https://doi.org/10.1109/icdmw51313.2020.00042
https://doi.org/10.1109/icdmw51313.2020.00042
Autor:
Marco Stefanucci, Uche Mbaka, Antonio Bevilacqua, Katarina Domijan, Alessandro Casa, Thach Le Nguyen, Georgiana Ifrim, Giovanna Ranzato, Elena Hayes, Bhaskar Dhariyal, Maria Frizzarin, Federico Ferraccioli, Ashish K. Singh, Agnieszka Konkolewska
Publikováno v:
Chemometrics and Intelligent Laboratory Systems
A chemometric data analysis challenge has been arranged during the first edition of the "International Workshop on Spectroscopy and Chemometrics", organized by the Vistamilk SFI Research Centre and held online in April 2021. The aim of the competitio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::50cb384dce6eb9308ba7d00eed1a80a7
https://doi.org/10.1016/j.chemolab.2021.104442
https://doi.org/10.1016/j.chemolab.2021.104442
Autor:
Vadlamani Ravi, Bhaskar Dhariyal
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9789811524745
In this study, we propose three novel hybrid deep learning architectures for sentiment classification. We hybridized convolution neural network (CNN) with two evolutionary neural networks, viz. fuzzy logic-driven self-tuned particle swarm optimizatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::72416fc09b003f791ed1be59eba0bddd
https://doi.org/10.1007/978-981-15-2475-2_1
https://doi.org/10.1007/978-981-15-2475-2_1
Publikováno v:
SSCI
In this study, we proposed two ensembled Convolutional Neural Network architectures viz. (CNNcuPSONN) and CNN-PNN, where cuPSONN is a CUDA enabled particle swarm optimization optimized neural network and PNN is the probabilistic neural network. We co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3a9bff105ea0060c2602a94c2e827800
https://doi.org/10.1109/ssci.2018.8628833
https://doi.org/10.1109/ssci.2018.8628833
Publikováno v:
Harmony Search and Nature Inspired Optimization Algorithms ISBN: 9789811307607
Random Projection has been used in many applications for dimensionality reduction. In this paper, a variant to the iterative random projection K-means algorithm to cluster high-dimensional data has been proposed and validated experimentally. Iterativ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::059132522c8512efd080941fe4497a2e
https://doi.org/10.1007/978-981-13-0761-4_14
https://doi.org/10.1007/978-981-13-0761-4_14