1 code implementation • 24 May 2023 • Błażej Leporowski, Arian Bakhtiarnia, Nicole Bonnici, Adrian Muscat, Luca Zanella, Yiming Wang, Alexandros Iosifidis
We introduce the first audio-visual dataset for traffic anomaly detection taken from real-world scenes, called MAVAD, with a diverse range of weather and illumination conditions.
no code implementations • 16 May 2023 • Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis
The increasing prevalence of gigapixel resolutions has presented new challenges for crowd counting.
no code implementations • 30 Jan 2023 • Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis
In this paper, we introduce PromptMix, a method for artificially boosting the size of existing datasets, that can be used to improve the performance of lightweight networks.
no code implementations • 15 Aug 2022 • Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis
JPEG image compression algorithm is a widely used technique for image size reduction in edge and cloud computing settings.
no code implementations • 26 Jul 2022 • Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis
Cameras in modern devices such as smartphones, satellites and medical equipment are capable of capturing very high resolution images and videos.
1 code implementation • 20 Jul 2022 • Arian Bakhtiarnia, Błażej Leporowski, Lukas Esterle, Alexandros Iosifidis
Images and video frames captured by cameras placed throughout smart cities are often transmitted over the network to a server to be processed by deep neural networks for various tasks.
no code implementations • 23 May 2022 • Arian Bakhtiarnia, Nemanja Milošević, Qi Zhang, Dragana Bajović, Alexandros Iosifidis
Split computing is a paradigm where a DNN is split into two sections; the first section is executed on the end device, and the output is transmitted to the edge server where the final section is executed.
1 code implementation • 17 Jan 2022 • Lukas Hedegaard, Arian Bakhtiarnia, Alexandros Iosifidis
Transformers in their common form are inherently limited to operate on whole token sequences rather than on one token at a time.
Ranked #4 on Online Action Detection on TVSeries
no code implementations • 29 Jun 2021 • Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis
In this work, we propose seven different architectures for early exit branches that can be used for dynamic inference in Vision Transformer backbones.
no code implementations • 19 May 2021 • Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis
Deploying deep learning models in time-critical applications with limited computational resources, for instance in edge computing systems and IoT networks, is a challenging task that often relies on dynamic inference methods such as early exiting.
no code implementations • 21 Apr 2021 • Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis
Deploying deep learning services for time-sensitive and resource-constrained settings such as IoT using edge computing systems is a challenging task that requires dynamic adjustment of inference time.