Tariq Habib Afridi

• Ph.D. Candidate
• PhD Student at Kyung Hee University

Deep supervised learning models require high volume of labeled data to attain sufficiently good results. Although, the practice of gathering and annotating such big data is costly and laborious. Recently, the application of self supervised learning (SSL) in vision tasks has gained significant attention. The intuition behind SSL is to exploit the sy...

The flexible paradigm of the Resource Description Framework (RDF) has accelerated the rate at which raw data is published on the web. Therefore, the volume of generated RDF data has increased impressively in the last decade, which promotes the use of compression to manage and reduce the size of RDF datasets. Furthermore, researchers have recently...

Deep learning has recently been shown to be effective in uncovering hidden patterns in non-Euclidean space, where data is represented as graphs with complex object relationships and interdependencies. Because of the implicit data dependence in the big graphs with millions of nodes and billions of edges, it is hard for industrial communities to expl...

Memes are graphics and text overlapped so that together they present concepts that become dubious if one of them is absent. It is spread mostly on social media platforms, in the form of jokes, sarcasm, motivating, etc. After the success of BERT in Natural Language Processing (NLP), researchers inclined to Visual-Linguistic (VL) multimodal problems...

On the rise of distributed computing technologies, video big data analytics in the cloud have attracted researchers and practitioners’ attention. The current technology and market trends demand an efficient framework for video big data analytics. However, the current work is too limited to provide an architecture on video big data analytics in the...

Feature indexing for video retrieval poses a significant hurdle for indexing due to three significant challenges. First, there are different types of features in varying nature, such as deep Convolutional Neural Network (CNN) features, handcrafted features, recognized text from the videos, and audio features, etc. Secondly, feature matching for tho...

On the rise of distributed computing technologies, video big data analytics in the cloud have attracted researchers and practitioners' attention. The current technology and market trends demand an efficient framework for video big data analytics. However, the current work is too limited to provide an architecture on video big data analytics in the...

Memes are graphics and text overlapped so that together they present concepts that become dubious if one of them is absent. It is spread mostly on social media platforms, in the form of jokes, sarcasm, motivating, etc. After the success of BERT in Natural Language Processing (NLP), researchers inclined to Visual-Linguistic (VL) multimodal problems...

One of the significant challenges with the Content-based Video Retrieval (CBVR) system is a spatiotemporal semantic gap, which has been addressed by the semantic methods. However, semantic solutions only accept SPARQL queries. The question is how to bridge the gap between both worlds? To address this issue, in this paper, we propose a hybrid layere...

Mitochondria are all-important organelles of eukaryotic cells since they are involved in processes associated with cellular mortality and human diseases. Therefore, trustworthy techniques are highly required for the identification of new mitochondrial proteins. We propose Mito-GSAAC system for prediction of mitochondrial proteins. The aim of this w...