Abhiraj Mohan
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View article: OpenMonkeyChallenge: Dataset and Benchmark Challenges for Pose Estimation of Non-human Primates
OpenMonkeyChallenge: Dataset and Benchmark Challenges for Pose Estimation of Non-human Primates Open
View article: PARIS: Personalized Activity Recommendation for Improving Sleep Quality
PARIS: Personalized Activity Recommendation for Improving Sleep Quality Open
The quality of sleep has a deep impact on people's physical and mental health. People with insufficient sleep are more likely to report physical and mental distress, activity limitation, anxiety, and pain. Moreover, in the past few years, …
View article: OpenMonkeyChallenge: Dataset and Benchmark Challenges for Pose Tracking of Non-human Primates
OpenMonkeyChallenge: Dataset and Benchmark Challenges for Pose Tracking of Non-human Primates Open
The ability to automatically track non-human primates as they move through the world is important for several subfields in biology and biomedicine. Inspired by the recent success of computer vision models enabled by benchmark challenges (e…
View article: University Operations During a Pandemic: A Flexible Decision Analysis Toolkit
University Operations During a Pandemic: A Flexible Decision Analysis Toolkit Open
Modeling infection spread during pandemics is not new, with models using past data to tune simulation parameters for predictions. These help in understanding of the healthcare burden posed by a pandemic and responding accordingly. However,…
View article: Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting
Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting Open
Intelligent transportation systems are a key component in smart cities, and the estimation and prediction of the spatiotemporal traffic state is critical to capture the dynamics of traffic congestion, i.e., its generation, propagation and …
View article: Detecting behavior modes in user behavior patterns using time-series clustering methods
Detecting behavior modes in user behavior patterns using time-series clustering methods Open