machine learning

Deep Neural Networks and Transfer Learning for Food Crop Identification in UAV Images

Accurate projections of seasonal agricultural output are essential for improving food security. However, the collection of agricultural information through seasonal agricultural surveys is often not timely enough to inform public and private …

Identification of Bicycling Periods Using the MicroPEM Personal Exposure Monitor

Exposure assessment studies are the primary means for understanding links between exposure to chemical and physical agents and adverse health effects. Recently, researchers have proposed using wearable monitors during exposure assessment studies to …

Estimated Ages of JUUL Twitter Followers

JUUL is the most popular electronic nicotine delivery system (ENDS) in the United States. JUUL’s discreet design, availability in flavors such as mango, and use of nicotine salt solutions that deliver a high dose of nicotine with minimal harshness …

SMART: An Open Source Data Labeling Platform for Supervised Learning

SMART is an open source web application designed to help data scientists and research teams efficiently build labeled training data sets for supervised machine learning tasks. SMART provides users with an intuitive interface for creating labeled data …

SMART

SMART is an open source application designed to help teams efficiently build labeled training datasets for supervised machine learning tasks.

Toward Model-Generated Household Listing in Low- and Middle-Income Countries Using Deep Learning

While governments, researchers, and NGOs are exploring ways to leverage big data sources for sustainable development, household surveys are still a critical source of information for dozens of the 232 indicators for the Sustainable Development Goals …

Assessing Target Audiences of Digital Public Health Campaigns: A Computational Approach

As a larger proportion of society participates in social media, public health organizations are increasingly using digital campaigns to engage and educate their target audiences. Computational methods such as social network analysis and machine …

Residential scene classification for gridded population sampling in developing countries using deep convolutional neural networks on satellite imagery

Conducting surveys in low- and middle-income countries is often challenging because many areas lack a complete sampling frame, have outdated census information, or have limited data available for designing and selecting a representative sample. …

Classification of Twitter users who tweet about e-cigarettes

Despite concerns about their health risks, e‑cigarettes have gained popularity in recent years. Concurrent with the recent increase in e‑cigarette use, social media sites such as Twitter have become a common platform for sharing information about …

Predicting age groups of Twitter users based on language and metadata features

Health organizations are increasingly using social media, such as Twitter, to disseminate health messages to target audiences. Determining the extent to which the target audience (e.g., age groups) was reached is critical to evaluating the impact of …