44 citations · 125 across the 6 of their papers we have counts for
6 papers
Deep learning-based approach for tomato classification in complex scenes
Mikael A. Mousse, Bethel C. A. R. K. Atohoun, Cina Motamed
Tracking ripening tomatoes is time consuming and labor intensive. Artificial intelligence technologies combined with those of computer vision can help users optimize the process of…
TopicBERT: A Transformer transfer learning based memory-graph approach for multimodal streaming social media topic detection
Meysam Asgari-Chenaghlu, Mohammad-Reza Feizi-Derakhshi, Leili farzinvash +2
Real time nature of social networks with bursty short messages and their respective large data scale spread among vast variety of topics are research interest of many researchers.…
BERTERS: Multimodal Representation Learning for Expert Recommendation System with Transformer
N. Nikzad-Khasmakhi, M. A. Balafar, M. Reza Feizi-Derakhshi +1
The objective of an expert recommendation system is to trace a set of candidates' expertise and preferences, recognize their expertise patterns, and identify experts. In this paper…
ExEm: Expert Embedding using dominating set theory with deep learning approaches
N. Nikzad-Khasmakhi, M. A. Balafar, M. Reza Feizi-Derakhshi +1
A collaborative network is a social network that is comprised of experts who cooperate with each other to fulfill a special goal. Analyzing this network yields meaningful informati…
A multimodal deep learning approach for named entity recognition from social media
Meysam Asgari-Chenaghlu, M. Reza Feizi-Derakhshi, Leili Farzinvash +2
Named Entity Recognition (NER) from social media posts is a challenging task. User generated content that forms the nature of social media, is noisy and contains grammatical and li…
Foreground-Background Segmentation Based on Codebook and Edge Detector
Mikaël A. Mousse, Eugène C. Ezin, Cina Motamed
Background modeling techniques are used for moving object detection in video. Many algorithms exist in the field of object detection with different purposes. In this paper, we prop…