Named entity recognition (NER) on noisy data, specifically user-generated content (e.g. on- line reviews, tweets) is a challenging task because of the presence of ill-formed text. In this regard, while studies on ...

In recent years, research made in person re-identification has gained quite a bit of significance due to the increasing demand from a broad range of application fields with security and surveillance topping the list. A ...

Since mobile devices are increasingly on hand today, users have become more heavily involved with their use in accessing the Internet. Today, most mobile devices use the Android operating system. On mobile devices, users' ...

Most pre-trained word embeddings are achieved from context-based learning algorithms trained over a large text corpus. This leads to learning similar vectors for words that share most of their contexts, while expressing ...

Detecting anomalies in surveillance videos is an important research problem in computer vision. In this thesis, we propose two deep network architectures for anomaly detection, Anomaly Detection Network (ADNet) and Anomaly ...

Automatic term extraction is an essential task in natural language processing. In this thesis, we work on terminology extraction for two purposes. The first aim is to measure inconsistency of scientific terminology for ...

Visual question answering (VQA) is one of the difficult tasks in multimodal machine reasoning. VQA requires machines to provide correct answers to questions about an image or a video. Here, the machine should perceive the ...

Integrating advanced AI-driven question answering (QA) systems into educational settings offers significant potential for enhancing learning experiences. This study focuses on developing and optimizing an educational QA ...

Recent video-text multimodel approaches provide good results on retrieval tasks. However, the performance of domain-specific cases might be decreased because of internal differences with generic data. Since deep learning ...

Analysis of histopathological images plays a crucial role in cancer detection and grading. Although well-trained pathologists can perform these tasks, the process is time-consuming and prone to errors. The advancement of ...