Abstract Vision-based Human Action Recognition (HAR) is a hot topic in computer vision.
Recently, deep-based HAR has shown promising results. HAR using a single data modality …

Mental health is a state of well-being where a person understands his/her potential,
participates in his or her community and is able to deal effectively with the challenges and …

The various variants of the classical least square regression (LSR) have been extensively
utilized in numerous applications. However, most previous linear regression methods only …

Breast cancer is the most commonly diagnosed cancer worldwide, and early detection is
essential for reducing mortality rates. Digital mammography is currently the best standard for …

Smart healthcare applications cannot be separated from healthcare data analysis and the
interactive interpretability between data and model. A human‐in‐the‐loop active learning …

Inferring human activities from the skeletons extracted from activity photos or videos is a
fundamental yet important issue in the research community of computer vision. Current …

An advancement in the paradigm of machine learning has been acclaimed by the arrival of
semi-supervised learning. In real life, it is challenging to get enough labeled samples. On …

Predicting a class or label of text-aided image has practical application in a range of
domains including social media, machine learning and medical domain. Usually, supervised …

Manual annotation of unlabeled data for model training is expensive and time-consuming,
especially for visual datasets requiring domain-specific experience for multi-labeling, such …

Skin lesion is one of the most commonly encountered illnesses that need to be detected and
treated at an early stage. Numerous Convolutional Neural Network (CNN) classifiers were …