The construction industry is experiencing remarkable growth in the data generation. Data
mining (DM) from considerable amount of data in the construction industry has emerged as …

Due to the pervasiveness of always connected devices, large amounts of heterogeneous
data are continuously being collected. Beyond the benefits that accrue for the users, there …

Deep models, eg, CNNs and Vision Transformers, have achieved impressive achievements
in many vision tasks in the closed world. However, novel classes emerge from time to time in …

Real-world applications require the classification model to adapt to new classes without
forgetting old ones. Correspondingly, Class-Incremental Learning (CIL) aims to train a …

The Internet of Things (IoT) is transforming major industries, including but not limited to
healthcare, agriculture, finance, energy, and transportation. IoT platforms are continually …

Facial recognition technologies are implemented in many areas, including but not limited to,
citizen surveillance, crime control, activity monitoring, and facial expression evaluation …

Edge computing and distributed machine learning have advanced to a level that can
revolutionize a particular organization. Distributed devices such as the Internet of Things …

Computing technologies pervade physical spaces and human lives, and produce a vast
amount of data that is available for analysis. However, there is a growing concern that …

The number of mobile devices, such as smartphones and smartwatches, is relentlessly
increasing, to almost 6.8 billion by 2022, and along with it, the amount of personal and …

This study investigates existing input privacy-preserving data mining (PPDM) methods and
privacy-preserving data stream mining methods (PPDSM), including their strengths and …