Noureldien Hussein

PhD Candidate in Computer Vision at the University of Amsterdam
Google Scholar, LinkedIn, GitHub, GoodReads, Blog
Email: nhussein AT uva.nl



Looking for Research Internship in Computer Vision (Video Analytics) for Summer 2019     Resume 

Fourth-year PhD candidate at Quva Lab, Informatics Institute (IvI), the University of Amsterdam (UvA). I am supervised by Professor Arnold Smeulders and co-supervised by Assistant Professor Efstratios Gavves.

My research interests are in computer vision using methods of machine learning and deep learning. I conduct(ed) research on action recognition, zero-shot event detection and graph-based video storytelling. I would like to help in advancing methods for understanding human activities in videos at industrial scale.

I started the PhD studies in January 2016. I obtained MSc Artificial Intelligence from the School of Electronics and Computer Science at the University of Southampton in 2015 and BSc Computer and System Engineering from the Faculty of Engineering, Ain Shams University in 2012.

Publications


Timeception for Complex Action Recognition • arXiv/1812.01289 (2018)
Noureldien Hussein, Efstratios Gavves, Arnold W. M. Smeulders

A novel temporal layer for 3D CNNs with multi-scale temporal convolutions and much reduced computation. The result is a CNN for modeling minute-long complex actions, 8 times longer than best related method.


Unified Embedding and Metric Learning for Zero-Exemplar Event Detection • CVPR (2017)
Noureldien Hussein, Efstratios Gavves, Arnold W. M. Smeulders

A manifold is learned using contrastive loss, in which there is a joint embedding of videos of human events and their related articles. The result is end-to-end model with best results on TRECVID MED dataset.


University of Amsterdam and Renmin University at TRECVID 2016: Searching Video, Detecting Events and Describing Video • TRECVID Workshop (2016)
Cees G. M. Snoek, Jianfeng Dong, Xirong Li, Xiaoxu Wang, Qijie Wei, Weiyu Lan, Efstratios Gavves, Noureldien Hussein, Dennis C. Koelma, Arnold W. M. Smeulders

Summary for our method used in the annual competition for zero-shot event recognition TRECVID MED 2016.

Teaching & Supervision


Thesis Supervision

Multi-Modal Detection for Boats using Vision and Radar  • MSc Artifical Intelligence (2019)
Juan Buhagiar, Noureldien Hussein, Efstratios Gavves

The goal of this on-going research is to detect the surrounding boats using multi-modal sensori data from cameras and radars. This will help achieve the over-arching goal of autonomus water taxi.


Improving Word Embeddings for Zero-Shot Event Localisation by Combining Relational Knowledge with Distributional Semantics • MSc Artifical Intelligence (2018)
Joop L. Pascha, Efstratios Gavves, Noureldien Hussein

Using knownlege graphs as a priori for labels associated with event images or videos. Hence, improving the accuracy of zero-shot detection.


Real-Time Composing of Restaurant Label Classifiers Utilizing Semantic Word Similarity • BSc Artifical Intelligence (2017)
Tony Nguyen, Noureldien Hussein, Efstratios Gavves

An method to predict missing labels of restaurant images using semantic word similarities. The method makes use of dataset of Kaggle competition: "Yelp Restaurant Photo Classification".


Teaching Assistance

  • Autonomous Mobile Robots - BSc Computer Science / Artificial Intelligence, 2018
  • Information Visualization - BSc Computer Science, 2017
  • Autonomous Mobile Robots - BSc Computer Science / Artificial Intelligence, 2016

Contact


Email: nhussein AT uva.nl
Office: +31-(0)20-525-8627
Website: https://staff.fnwi.uva.nl/n.m.e.hussein/

Address

Quva Lab, Room C3.250a
Informatics Institute, University of Amsterdam
Science Park 904, 1098 XH Amsterdam, The Netherlands