Chanuki Illushka Seresinhe
Chanuki Illushka Seresinhe
Warwick Business School, University of Warwick
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Cited by
Cited by
Quantifying the impact of scenic environments on health
CI Seresinhe, T Preis, HS Moat
Scientific reports 5 (1), 1-9, 2015
Using deep learning to quantify the beauty of outdoor places
CI Seresinhe, T Preis, HS Moat
Royal Society open science 4 (7), 170170, 2017
Happiness is greater in more scenic locations
CI Seresinhe, T Preis, G MacKerron, HS Moat
Scientific Reports 9 (1), 1-11, 2019
Historical analysis of national subjective wellbeing using millions of digitized books
TT Hills, E Proto, D Sgroi, CI Seresinhe
Nature human behaviour 3 (12), 1271-1275, 2019
Street-Frontage-Net: urban image classification using deep convolutional neural networks
S Law, CI Seresinhe, Y Shen, M Gutierrez-Roig
International Journal of Geographical Information Science 34 (4), 681-707, 2020
Quantifying scenic areas using crowdsourced data
CI Seresinhe, HS Moat, T Preis
Environment and Planning B: Urban Analytics and City Science 45 (3), 567-582, 2018
Quantifying the link between art and property prices in urban neighbourhoods
CI Seresinhe, T Preis, HS Moat
Royal Society Open Science 3 (4), 160146, 2016
An application of convolutional neural network in street image classification: The case study of London
S Law, Y Shen, C Seresinhe
Proceedings of the 1st Workshop on Artificial Intelligence and Deep Learning …, 2017
Of Streets and Squares, Which public places do people want to be in and why
M Iovene, N Boys-Smith, CI Seresinhe
Create Streets and Cadogan: London, UK, 2019
From landscapes to cityscapes: quantifying the connection between scenic beauty and human wellbeing
CI Seresinhe
University of Warwick, 2018
Using Deep Learning to Quantify the Beauty of Outdoor Places Supplementary Material
CI Seresinhe, T Preis, HS Moat
Might beautiful places have a quantifiable impact on our wellbeing?
CI Seresinhe
Quantifying the Link Between Art and Property Prices in Urban Neighbourhoods Supplementary Material
CI Seresinhe, T Preis, HS Moat
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