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Sayantan sengupta
Sayantan sengupta
Verified email at food.dtu.dk - Homepage
Title
Cited by
Cited by
Year
Active learning solution on distributed edge computing
J Qian, S Sengupta, LK Hansen
arXiv preprint arXiv:1906.10718, 2019
172019
Submerged aquatic vegetation: Overview of monitoring techniques used for the identification and determination of spatial distribution in European coastal waters
C Lønborg, A Thomasberger, PAU Stæhr, A Stockmarr, S Sengupta, ...
Integrated Environmental Assessment and Management 18 (4), 892-908, 2022
92022
Seagrassdetect: A novel method for the detection of seagrass from unlabelled underwater videos
S Sengupta, BK Ersbøll, A Stockmarr
Ecological Informatics 57, 101083, 2020
72020
Benefit and risk assessment of fish in the Norwegian diet
ALF VKM, P Berstad, B Bukhvalova, M Carlsen, L Dahl, A Goksøyr, ...
Scientific Opinion of the Scientific Steering Committee of the Norwegian …, 2022
62022
Benefit and risk assessment of fish in the Norwegian diet-Scientific Opinion of the Steering Committee of the Norwegian Scientific Committee for Food and Environment
LF Andersen, P Berstad, BA Bukhvalova, MH Carlsen, LJ Dahl, A Goksøyr, ...
22022
Bayesian Transfer Learning For Deep Networks
J Wohlert, AM Munk, S Sengupta, F Laumann
2*
Vitamin D Food Fortification Strategies on Population-Based Dietary Intake Data Using Mixed-Integer Programming
S Sengupta, T Christensen, G Ravn-Haren, R Andersen
Foods 12 (4), 698, 2023
12023
Nye overvågningsteknikker til marin vegetation
T Karen, T Aris, H Lars Boye, S Peter A, R Mikkel Lydholm, S Anders, ...
Vand og Jord 1 (28), 8-11, 2021
1*2021
Multi-hypothesis classifier
S Sengupta, S Sanyal
arXiv preprint arXiv:1908.07857, 2019
12019
Ålegræs detektion fra undervandsvideoer
A Stockmarr, S Sengupta
Vand og Jord 1 (28), 4-7, 2021
2021
Towards Automatic Monitoring and Mapping of Benthic Vegetation using Machine Learning
S Sengupta
Technical University of Denmark, 2021
2021
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Articles 1–11