To design fast neural networks, many works have been focusing on reducing the number of
floating-point operations (FLOPs). We observe that such reduction in FLOPs, however, does …

Floor labels of crowdsourced RF signals are crucial for many smart-city applications, such
as multi-floor indoor localization, geofencing, and robot surveillance. To build a prediction …

Time series data, including univariate and multivariate ones, are characterized by unique
composition and complex multi-scale temporal variations. They often require special …

As convolution has empowered many smart applications, dynamic convolution further equips
it with the ability to adapt to diverse inputs. However, the static and dynamic convolutions …

In applications such as elderly care, dementia anti-wandering and pandemic control, it is
important to ensure that people are within a predefined area for their safety and well-being. We …

A user's movement path can be precisely and concisely described as a concatenation of
straight lines having the user's turns as their end points. Learning such a path description or …

Caenorhabditis elegans is a widely used model organism to study development, aging and
behavior. Many of these biological studies require staging a large number of worms to assay …

Containment is the first-priority measure in infection control to curb the spread of highly
infectious diseases such as COVID-19. Home quarantine is one such measure to keep people at …

We study the problem of floor identification for radiofrequency (RF) signal samples obtained
in a crowdsourced manner, where the signal samples are highly heterogeneous and most …

Proximity detection is to determine whether an IoT receiver is within a certain distance from
a signal transmitter. Due to its low cost and high popularity, Bluetooth low energy (BLE) has …