1 code implementation • 30 Apr 2024 • Amarjeet Kumar, Hongxu Jiang, Muhammad Imran, Cyndi Valdes, Gabriela Leon, Dahyun Kang, Parvathi Nataraj, Yuyin Zhou, Michael D. Weiss, Wei Shao
This module uses the cross-slice attention mechanism to effectively capture 3D spatial information by learning long-range dependencies between the center slice (for segmentation) and its neighboring slices.
1 code implementation • 24 Apr 2024 • Vishal Balaji Sivaraman, Muhammad Imran, Qingyue Wei, Preethika Muralidharan, Michelle R. Tamplin, Isabella M . Grumbach, Randy H. Kardon, Jui-Kai Wang, Yuyin Zhou, Wei Shao
The model's effectiveness was demonstrated across three retinal image datasets: color fundus images, fluorescein angiography images, and laser speckle flowgraphy images.
no code implementations • 18 Apr 2024 • Abdul Wahab Ziaullah, Ferda Ofli, Muhammad Imran
Critical Infrastructure Facilities (CIFs), such as healthcare and transportation facilities, are vital for the functioning of a community, especially during large-scale emergencies.
no code implementations • 23 Jan 2024 • Muhammad Imran, Jonathan R Krebs, Veera Rajasekhar Reddy Gopu, Brian Fazzone, Vishal Balaji Sivaraman, Amarjeet Kumar, Chelsea Viscardi, Robert Evans Heithaus, Benjamin Shickel, Yuyin Zhou, Michol A Cooper, Wei Shao
Advancements in medical imaging and endovascular grafting have facilitated minimally invasive treatments for aortic diseases.
1 code implementation • 5 Jan 2024 • Zijun Long, Richard McCreadie, Muhammad Imran
We leverage the new Incidents1M crisis image dataset to develop a range of new transformer-based image classification models.
no code implementations • 28 Nov 2023 • James Rains, Anvar Tukmanov, Qammer Abbasi, Muhammad Imran
Can the smart radio environment paradigm measurably enhance the performance of contemporary urban macrocells?
no code implementations • 31 May 2023 • Muhammad Imran, Brianna Nguyen, Jake Pensa, Sara M. Falzarano, Anthony E. Sisk, Muxuan Liang, John Michael DiBianco, Li-Ming Su, Yuyin Zhou, Wayne G. Brisbane, Wei Shao
Our pipeline begins with the reconstruction of pseudo-whole-mount histopathology images and a 3-dimensional (3D) micro-US volume.
1 code implementation • 31 May 2023 • Hongxu Jiang, Muhammad Imran, Preethika Muralidharan, Anjali Patel, Jake Pensa, Muxuan Liang, Tarik Benidir, Joseph R. Grajo, Jason P. Joseph, Russell Terry, John Michael DiBianco, Li-Ming Su, Yuyin Zhou, Wayne G. Brisbane, Wei Shao
During the training process, MicroSegNet focuses more on regions that are hard to segment (hard regions), characterized by discrepancies between expert and non-expert annotations.
no code implementations • 15 Mar 2023 • Yao Ge, Chong Tang, Haobo Li, Zikang Zhang, Wenda Li, Kevin Chetty, Daniele Faccio, Qammer H. Abbasi, Muhammad Imran
The dataset has been validated and has potential for the research of lip reading and multimodal speech recognition.
no code implementations • 4 Mar 2023 • Irfan Ullah, Sharifullah Khan, Muhammad Imran, Young-Koo Lee
Many people turn to social media during disasters for requesting help and/or providing relief to others.
no code implementations • 8 Feb 2023 • Thai-Hoang Nguyen, Muhammad Imran, Jaehyuk Choi, Joon-Sung Yang
A stuck-at cell can be read but not reprogrammed, thus, stuck-at faults in NVMs may or may not result in errors depending on the data to be stored.
1 code implementation • 8 Nov 2022 • Nando Metzger, John E. Vargas-Muñoz, Rodrigo C. Daudt, Benjamin Kellenberger, Thao Ton-That Whelan, Ferda Ofli, Muhammad Imran, Konrad Schindler, Devis Tuia
Fine-grained population maps are needed in several domains, like urban planning, environmental monitoring, public health, and humanitarian operations.
no code implementations • 7 Nov 2022 • Fevziye Irem Eyiokur, Alperen Kantarcı, Mustafa Ekrem Erakin, Naser Damer, Ferda Ofli, Muhammad Imran, Janez Križaj, Albert Ali Salah, Alexander Waibel, Vitomir Štruc, Hazim Kemal Ekenel
The emergence of COVID-19 has had a global and profound impact, not only on society as a whole, but also on the lives of individuals.
1 code implementation • 2 Nov 2022 • Alperen Kantarcı, Ferda Ofli, Muhammad Imran, Hazim Kemal Ekenel
In this work, we present a novel face mask detection dataset that contains images posted on Twitter during the pandemic from around the world.
no code implementations • 14 Feb 2022 • Ferda Ofli, Umair Qazi, Muhammad Imran, Julien Roch, Catherine Pennington, Vanessa Banks, Remy Bossu
This paper presents an online system that leverages social media data in real time to identify landslide-related information automatically using state-of-the-art artificial intelligence techniques.
1 code implementation • 11 Jan 2022 • Ethan Weber, Dim P. Papadopoulos, Agata Lapedriza, Ferda Ofli, Muhammad Imran, Antonio Torralba
In this work, we present the Incidents1M Dataset, a large-scale multi-label dataset which contains 977, 088 images, with 43 incident and 49 place categories.
1 code implementation • 16 Nov 2021 • Şeymanur Aktı, Ferda Ofli, Muhammad Imran, Hazim Kemal Ekenel
We also propose a new dataset, named Social Media Fight Images (SMFI), comprising real-world images of fight actions.
1 code implementation • 4 Oct 2021 • Muhammad Imran, Umair Qazi, Ferda Ofli
The widespread usage of social networks during mass convergence events, such as health emergencies and disease outbreaks, provides instant access to citizen-generated data that carry rich information about public opinions, sentiments, urgent needs, and situational reports.
no code implementations • 3 Oct 2021 • Ferda Ofli, Muhammad Imran, Umair Qazi, Julien Roch, Catherine Pennington, Vanessa J. Banks, Remy Bossu
Lack of global data inventories obstructs scientific modeling of and response to landslide hazards which are oftentimes deadly and costly.
1 code implementation • 29 Aug 2021 • Firoj Alam, Tanvirul Alam, Md. Arid Hasan, Abul Hasnat, Muhammad Imran, Ferda Ofli
This is the first dataset of its kind: social media images, disaster response, and multi-task learning research.
no code implementations • 29 Jul 2021 • Benjamin Kellenberger, John E. Vargas-Muñoz, Devis Tuia, Rodrigo C. Daudt, Konrad Schindler, Thao T-T Whelan, Brenda Ayo, Ferda Ofli, Muhammad Imran
Building functions shall be retrieved by parsing social media data like for instance tweets, as well as ground-based imagery, to automatically identify different buildings functions and retrieve further information such as the number of building stories.
no code implementations • 9 Apr 2021 • Firoj Alam, Tanvirul Alam, Muhammad Imran, Ferda Ofli
Images shared on social media help crisis managers gain situational awareness and assess incurred damages, among other response tasks.
no code implementations • 7 Apr 2021 • Firoj Alam, Umair Qazi, Muhammad Imran, Ferda Ofli
Social networks are widely used for information consumption and dissemination, especially during time-critical events such as natural disasters.
no code implementations • 29 Jan 2021 • Zhiwei Guo, Keping Yu, Tan Guo, Ali Kashif Bashir, Muhammad Imran, Mohsen Guizani
With the prevalence of Internet of Things (IoT)-based social media applications, the distance among people has been greatly shortened.
no code implementations • COLING 2020 • Reem Suwaileh, Muhammad Imran, Tamer Elsayed, Hassan Sajjad
For example, results show that, for training a location mention recognition model, Twitter-based data is preferred over general-purpose data; and crisis-related data is preferred over general-purpose Twitter data.
no code implementations • 17 Nov 2020 • Firoj Alam, Ferda Ofli, Muhammad Imran, Tanvirul Alam, Umair Qazi
In this study, we propose new datasets for disaster type detection, and informativeness classification, and damage severity assessment.
1 code implementation • CONLL 2020 • Romain Couillet, Yagmur Gizem Cinar, Eric Gaussier, Muhammad Imran
This article establishes that, unlike the legacy tf*idf representation, recent natural language representations (word embedding vectors) tend to exhibit a so-called \textit{concentration of measure phenomenon}, in the sense that, as the representation size $p$ and database size $n$ are both large, their behavior is similar to that of large dimensional Gaussian random vectors.
1 code implementation • ECCV 2020 • Ethan Weber, Nuria Marzo, Dim P. Papadopoulos, Aritro Biswas, Agata Lapedriza, Ferda Ofli, Muhammad Imran, Antonio Torralba
While most studies on social media are limited to text, images offer more information for understanding disaster and incident scenes.
no code implementations • 9 Jul 2020 • Noman Haider, Muhammad Zeeshan Baig, Muhammad Imran
Recent technological and architectural advancements in 5G networks have proven their worth as the deployment has started over the world.
1 code implementation • 22 May 2020 • Umair Qazi, Muhammad Imran, Ferda Ofli
The past several years have witnessed a huge surge in the use of social media platforms during mass convergence events such as health emergencies, natural or human-induced disasters.
1 code implementation • 14 Apr 2020 • Ferda Ofli, Firoj Alam, Muhammad Imran
Multimedia content in social media platforms provides significant information during disaster events.
Ranked #1 on Disaster Response on CrisisMMD
no code implementations • 14 Apr 2020 • Firoj Alam, Hassan Sajjad, Muhammad Imran, Ferda Ofli
Time-critical analysis of social media streams is important for humanitarian organizations for planing rapid response during disasters.
no code implementations • 14 Apr 2020 • Muhammad Imran, Firoj Alam, Umair Qazi, Steve Peterson, Ferda Ofli
Rapid damage assessment is one of the core tasks that response organizations perform at the onset of a disaster to understand the scale of damage to infrastructures such as roads, bridges, and buildings.
no code implementations • 1 Sep 2019 • Hong-Ning Dai, Hao Wang, Guangquan Xu, Jiafu Wan, Muhammad Imran
The recent advances in information and communication technology (ICT) have promoted the evolution of conventional computer-aided manufacturing industry to smart data-driven manufacturing.
no code implementations • 5 Aug 2019 • Muhammad Zubair Asghar, Fazli Subhan, Muhammad Imran, Fazal Masud Kundi, Shahboddin Shamshirband, Amir Mosavi, Peter Csiba, Annamaria R. Varkonyi-Koczy
Emotion detection from the text is an important and challenging problem in text analytics.
1 code implementation • journal 2019 • Naila Hayat, Muhammad Imran
A ghost-free multi-exposure image fusion technique using the dense SIFT descriptor and the guided filter is proposed in this paper.
1 code implementation • ACL 2018 • Firoj Alam, Shafiq Joty, Muhammad Imran
In such scenarios, a DNN model can leverage labeled and unlabeled data from a related domain, but it has to deal with the shift in data distributions between the source and the target domains.
no code implementations • 2 May 2018 • Firoj Alam, Shafiq Joty, Muhammad Imran
During time-critical situations such as natural disasters, rapid classification of data posted on social networks by affected people is useful for humanitarian organizations to gain situational awareness and to plan response efforts.
2 code implementations • 2 May 2018 • Firoj Alam, Ferda Ofli, Muhammad Imran
Despite extensive research that mainly focuses on textual content to extract useful information, limited work has focused on the use of imagery content or the combination of both content types.
Social and Information Networks Computers and Society
no code implementations • 9 Apr 2017 • Dat Tien Nguyen, Firoj Alam, Ferda Ofli, Muhammad Imran
The extensive use of social media platforms, especially during disasters, creates unique opportunities for humanitarian organizations to gain situational awareness and launch relief operations accordingly.
no code implementations • 6 Oct 2016 • Muhammad Imran, Sanjay Chawla, Carlos Castillo
An emerging challenge in the online classification of social media data streams is to keep the categories used for classification up-to-date.
no code implementations • 5 Oct 2016 • Koustav Rudra, Siddhartha Banerjee, Niloy Ganguly, Pawan Goyal, Muhammad Imran, Prasenjit Mitra
The use of microblogging platforms such as Twitter during crises has become widespread.
no code implementations • 4 Oct 2016 • Dat Tien Nguyen, Shafiq Joty, Muhammad Imran, Hassan Sajjad, Prasenjit Mitra
During natural or man-made disasters, humanitarian response organizations look for useful information to support their decision-making processes.
no code implementations • 12 Aug 2016 • Dat Tien Nguyen, Kamela Ali Al Mannai, Shafiq Joty, Hassan Sajjad, Muhammad Imran, Prasenjit Mitra
The current state-of-the-art classification methods require a significant amount of labeled data specific to a particular event for training plus a lot of feature engineering to achieve best results.
1 code implementation • LREC 2016 • Muhammad Imran, Prasenjit Mitra, Carlos Castillo
Microblogging platforms such as Twitter provide active communication channels during mass convergence and emergency events such as earthquakes, typhoons.
no code implementations • 17 Feb 2016 • Muhammad Imran, Prasenjit Mitra, Jaideep Srivastava
Scarcity of labeled data causes poor performance in machine training.
no code implementations • 21 Oct 2013 • Muhammad Imran, Ioanna Lykourentzou, Yannick Naudet, Carlos Castillo
A crowdsourced stream processing system (CSP) is a system that incorporates crowdsourced tasks in the processing of a data stream.