Lithium-ion batteries play a pivotal role in a wide range of applications, from electronic
devices to large-scale electrified transportation systems and grid-scale energy storage …

Deep semi-supervised learning is a fast-growing field with a range of practical applications.
This paper provides a comprehensive survey on both fundamentals and recent advances in …

Integrating artificial intelligence with food category recognition has been a field of interest for
research for the past few decades. It is potentially one of the next steps in revolutionizing …

Semi-supervised learning is the branch of machine learning concerned with using labelled
as well as unlabelled data to perform certain learning tasks. Conceptually situated between …

Multimodal biomedical data fusion plays a pivotal role in distilling comprehensible and
actionable insights by seamlessly integrating disparate biomedical data from multiple …

Along with the advancement of several emerging computing paradigms and technologies,
such as cloud computing, mobile computing, artificial intelligence, and big data, Internet of …

Supervised learning techniques construct predictive models by learning from a large
number of training examples, where each training example has a label indicating its ground …

Current deep-learning models are mostly built upon neural networks, ie multiple layers of
parameterized differentiable non-linear modules that can be trained by backpropagation. In …

Deep neural networks (DNNs) have witnessed great successes in semantic segmentation,
which requires a large number of labeled data for training. We present a novel learning …

The world we see is ever-changing and it always changes with people, things, and the
environment. Domain is referred to as the state of the world at a certain moment. A research …