Recently, many efforts have been concentrated on land use land cover (LULC) classification
due to rapid urbanization, environmental pollution, agriculture drought, frequent floods, and …

As the prevalence of social media on the Internet, opinion mining has become an essential
approach to analyzing so many data. Various applications appear in a wide range of …

Semi-supervised learning (SSL) improves model generalization by leveraging massive
unlabeled data to augment limited labeled samples. However, currently, popular SSL …

Recent years have witnessed the success of deep learning methods in human activity
recognition (HAR). The longstanding shortage of labeled activity data inherently calls for a …

Machine learning systems deployed in the wild are often trained on a source distribution but
deployed on a different target distribution. Unlabeled data can be a powerful point of …

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions,
sentiments, evaluations, attitudes, and emotions from written language. It is one of the most …

Since the booming development of e-commerce in the last decade, the researchers have
begun to pay more attention to extract the valuable information from consumers comments …

Document-level sentiment classification aims to automate the task of classifying a textual
review, which is given on a single topic, as expressing a positive or negative sentiment. In …

Sentiment analysis is the computational study of people's opinions, sentiments, emotions,
moods, and attitudes. This fascinating problem offers numerous research challenges, but …

Sentiment Analysis is the most prominent branch of natural language processing. It deals
with the text classification in order to determine the intention of the author of the text. The …