Journal ArticleDOI
Predicting cell phone adoption metrics using machine learning and satellite imagery
TLDR
A machine learning method is presented that uses publicly available satellite imagery to predict telecoms demand metrics, including cell phone adoption and spending on mobile services, and applies the method to Malawi and Ethiopia and consistently outperforms baseline models which use population density or nightlight luminosity.About:
This article is published in Telematics and Informatics.The article was published on 2021-09-01. It has received 10 citations till now. The article focuses on the topics: Digital divide & Phone.read more
Citations
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Journal ArticleDOI
Personalized federated learning framework for network traffic anomaly detection
TL;DR: Wang et al. as mentioned in this paper proposed a personalized federated anomaly detection framework for network traffic anomaly detection, in which data are aggregated under the premise of privacy protection and relatively personalized models are constructed by fine-tuning.
Journal ArticleDOI
Supportive 5G Infrastructure Policies are Essential for Universal 6G: Assessment Using an Open-Source Techno-Economic Simulation Model Utilizing Remote Sensing
Edward J. Oughton,Ashutosh Jha +1 more
TL;DR: In this paper, the authors present a quantitative assessment of the impact of current 5G policies on universal broadband coverage, drawing conclusions over how decisions made now affect future evolution to 6G.
Journal ArticleDOI
Policy choices can help keep 4G and 5G universal broadband affordable
TL;DR: In this article , the authors assess universal broadband viability in the developing world, quantifying the relationship between demand-side revenue and supply-side cost, and develop a comprehensive scenario-based simulation model to evaluate the global cost-effectiveness of different 4G and 5G infrastructure strategies.
Journal ArticleDOI
Policy options for broadband infrastructure strategies: A simulation model for affordable universal broadband in Africa
TL;DR: In this article , the authors demonstrate an innovative method that addresses data and model uncertainty by developing open-source software to explore affordable universal broadband strategies, using a scenario-based hypothetical mobile operator.
References
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Proceedings Article
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan,Andrew Zisserman +1 more
TL;DR: In this paper, the authors investigated the effect of the convolutional network depth on its accuracy in the large-scale image recognition setting and showed that a significant improvement on the prior-art configurations can be achieved by pushing the depth to 16-19 layers.
Journal ArticleDOI
A Survey on Transfer Learning
Sinno Jialin Pan,Qiang Yang +1 more
TL;DR: The relationship between transfer learning and other related machine learning techniques such as domain adaptation, multitask learning and sample selection bias, as well as covariate shift are discussed.
Posted Content
Measuring Economic Growth from Outer Space
TL;DR: A statistical framework is developed that uses satellite data on lights growth to augment existing income growth measures, under the assumption that measurement error in using observed light as an indicator of income is uncorrelated with measurementerror in national income accounts.
Journal ArticleDOI
Measuring Economic Growth from Outer Space
TL;DR: In this paper, satellite data on lights at night is used to augment existing income growth measures, under the assumption that measurement errors in using observed light as an indicator of income is uncorrelated with measurement error in national income accounts.
Journal ArticleDOI
Combining satellite imagery and machine learning to predict poverty
Neal Jean,Marshall Burke,Marshall Burke,Michael Xie,W. Matthew Davis,David B. Lobell,Stefano Ermon +6 more
TL;DR: This work shows how a convolutional neural network can be trained to identify image features that can explain up to 75% of the variation in local-level economic outcomes, and could transform efforts to track and target poverty in developing countries.
Related Papers (5)
Predicting cell phone adoption metrics using satellite imagery.
Edward J. Oughton,Jatin Mathur +1 more