1 code implementation • 17 Nov 2023 • Kiran Kokilepersaud, Yash-yee Logan, Ryan Benkert, Chen Zhou, Mohit Prabhushankar, Ghassan AlRegib, Enrique Corona, Kunjan Singh, Mostafa Parchami
In this paper, we introduce the FOCAL (Ford-OLIVES Collaboration on Active Learning) dataset which enables the study of the impact of annotation-cost within a video active learning setting.
no code implementations • 30 Jul 2021 • Mostafa Parchami, Saif Iftekar Sayed
In this paper, we proposed a novel and unified deep learning-based approach that can learn how to track features reliably as well as learn how to detect such reliable features for tracking purposes.
no code implementations • 3 Mar 2021 • Bruno Costa, Enrique Corona, Mostafa Parchami, Gint Puskorius, Dimitar Filev
This paper presents a novel approach of representing dynamic visual scenes with static maps generated from video/image streams.
no code implementations • 27 Feb 2018 • Saman Bashbaghi, Eric Granger, Robert Sabourin, Mostafa Parchami
In video-based FR systems, facial models of target individuals are designed a priori during enrollment using a limited number of reference still images or video data.
no code implementations • 3 Mar 2017 • Mohammadhani Fouladgar, Mostafa Parchami, Ramez Elmasri, Amir Ghaderi
However, centralized systems are not scalable and fail provide real-time feedback to the system whereas in a decentralized scheme, each node is responsible to predict its own short-term congestion based on the local current measurements in neighboring nodes.