Artificial intelligence (AI) systems hold great promise as decision-support tools, but we must
be able to identify and understand their inevitable mistakes if they are to fulfill this potential …

Air temperature within the urban canopy layer is one of the most critical variables that impact
the environmental sustainability of cities. With advantages in computational speed, machine …

There is general consensus that it is important for artificial intelligence (AI) and machine
learning systems to be explainable and/or interpretable. However, there is no general …

In semiconductor manufacturing, the defect patterns of wafer maps provide crucial
information to identify the root causes of wafer defects. Recently, convolutional neural …

The efficacy of deep learning depends on large-scale data sets that have been carefully
curated with reliable data acquisition and annotation processes. However, acquiring such …

It is well believed that the higher uncertainty in a word of the caption, the more inter-
correlated context information is required to determine it. However, current image captioning …

We propose an approach to detect violence in CCTV feeds that is robust to new datasets
and situations. This approach breaks with the traditional assumption of having large …

Proactively caching content at the network edge is particularly effective in high-mobility
vehicular networks, where intermittent connection is the major challenge for seamless …

Though an accurate measurement of entropy, or more generally uncertainty, is critical to the
success of human–machine teams, the evaluation of the accuracy of such metrics as a …

Remaining useful life (RUL) prediction is crucial to supporting intelligent maintenance and
health management of safety–critical products. Although advanced data-driven approaches …