As the globally increasing population drives rapid urbanization in various parts of the world,
there is a great need to deliberate on the future of the cities worth living. In particular, as …

Time Series Classification and Extrinsic Regression are important and challenging machine
learning tasks. Deep learning has revolutionized natural language processing and computer …

The increasing need for economic, safe, and sustainable smart manufacturing combined
with novel technological enablers has paved the way for artificial intelligence (AI) and big …

Time series data usually contains local and global patterns. Most of the existing feature
networks focus on local features rather than the relationships among them. The latter is also …

Time-Series Mining (TSM) is an important research area since it shows great potential in
practical applications. Deep learning models that rely on massive labeled data have been …

Abstract The Electricity Supply Chain is a system of enabling procedures to optimize
processes ranging from production to transportation and consumption of electricity. The …

Deep Learning (DL) is vulnerable to out-of-distribution and adversarial examples resulting in
incorrect outputs. To make DL more robust, several posthoc (or runtime) anomaly detection …

Breast cancer is the second deadliest disease amongst women worldwide. Breast
histopathology image analysis is one of the most powerful ways used for the detection of …

With the ever increase in social media usage, it has become necessary to combat the
spread of false information and decrease the reliance of information retrieval from such …

In recent years, there has been a rapidly expanding focus on explaining the predictions
made by black-box AI systems that handle image and tabular data. However, considerably …