Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Patro, Arun"'
Autor:
Sathyanarayana, Girish, Patro, Arun
In this paper, we describe a novel solution to compute optimal warehouse allocations for fashion inventory. Procured inventory must be optimally allocated to warehouses in proportion to the regional demand around the warehouse. This will ensure that
Externí odkaz:
http://arxiv.org/abs/2007.05081
Publikováno v:
In Journal of Alloys and Compounds 15 October 2023 960
Autor:
Ravi, Abhinav, Patro, Arun, Garg, Vikram, Rajagopal, Anoop Kolar, Rajan, Aruna, Banerjee, Rajdeep Hazra
$ $"Fast Fashion" spearheads the biggest disruption in fashion that enabled to engineer resilient supply chains to quickly respond to changing fashion trends. The conventional design process in commercial manufacturing is often fed through "trends" o
Externí odkaz:
http://arxiv.org/abs/1906.12159
Autor:
Murugaiyan, Premkumar, Mitra, Amitava, Patro, Arun Kumar, Roy, Rajat K., Churyukanova, M., Kaloshkin, S., Shuvaeva, E., Panda, Ashis K.
Publikováno v:
In Journal of Magnetism and Magnetic Materials 15 December 2019 492
Autor:
CHATTERJI, AARON1 ronnie@duke.edu, PATRO, ARUN1
Publikováno v:
Academy of Management Perspectives. Nov2014, Vol. 28 Issue 4, p395-408. 14p.
Publikováno v:
Asian Case Research Journal; Dec2013, Vol. 17 Issue 2, p267-287, 21p
Publikováno v:
Indian Journal of Endocrinology & Metabolism. 2017 Supplement, Vol. 21, pS65-S71. 7p.
Publikováno v:
Indian Journal of Endocrinology & Metabolism. Oct2017, Vol. 21, pS59-S71. 13p.
Autor:
Jolapara, Milan, Kesavadas, Chandrasekharan, Radhakrishnan, V. V., Saini, Jitender, Patro, Satya Narayan, Gupta, Arun Kumar, Kapilamoorthy, Tirur Raman, Bodhey, Narendra
Publikováno v:
Neuroradiology; Feb2009, Vol. 51 Issue 2, p123-129, 7p, 3 Color Photographs, 1 Chart
Autor:
Gustavo Carneiro, Shaodi You
This LNCS workshop proceedings, ACCV 2018, contains carefully reviewed and selected papers from 11 workshops, each having different types or programs: Scene Understanding and Modelling (SUMO) Challenge, Learning and Inference Methods for High Perform