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pro vyhledávání: '"Kyrkou, Christos"'
Autor:
Kyrkou, Christos
High-efficiency deep learning (DL) models are necessary not only to facilitate their use in devices with limited resources but also to improve resources required for training. Convolutional neural networks (ConvNets) typically exert severe demands on
Externí odkaz:
http://arxiv.org/abs/2407.14831
The Forward-Forward (FF) Algorithm has been recently proposed to alleviate the issues of backpropagation (BP) commonly used to train deep neural networks. However, its current formulation exhibits limitations such as the generation of negative data,
Externí odkaz:
http://arxiv.org/abs/2312.12668
Autonomous vehicles increasingly rely on cameras to provide the input for perception and scene understanding and the ability of these models to classify their environment and objects, under adverse conditions and image noise is crucial. When the inpu
Externí odkaz:
http://arxiv.org/abs/2111.03480
Autor:
Kyrkou, Christos
The need for automated real-time visual systems in applications such as smart camera surveillance, smart environments, and drones necessitates the improvement of methods for visual active monitoring and control. Traditionally, the active monitoring t
Externí odkaz:
http://arxiv.org/abs/2107.13233
Autor:
Ignatov, Andrey, Malivenko, Grigory, Timofte, Radu, Chen, Sheng, Xia, Xin, Liu, Zhaoyan, Zhang, Yuwei, Zhu, Feng, Li, Jiashi, Xiao, Xuefeng, Tian, Yuan, Wu, Xinglong, Kyrkou, Christos, Chen, Yixin, Zhang, Zexin, Peng, Yunbo, Lin, Yue, Dutta, Saikat, Das, Sourya Dipta, Shah, Nisarg A., Kumar, Himanshu, Ge, Chao, Wu, Pei-Lin, Du, Jin-Hua, Batutin, Andrew, Federico, Juan Pablo, Lyda, Konrad, Khojoyan, Levon, Thanki, Abhishek, Paul, Sayak, Siddiqui, Shahid
Camera scene detection is among the most popular computer vision problem on smartphones. While many custom solutions were developed for this task by phone vendors, none of the designed models were available publicly up until now. To address this prob
Externí odkaz:
http://arxiv.org/abs/2105.08819
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing ( Volume: 13), Page(s): 1687 - 1699, 2020
Deep learning-based algorithms can provide state-of-the-art accuracy for remote sensing technologies such as unmanned aerial vehicles (UAVs)/drones, potentially enhancing their remote sensing capabilities for many emergency response and disaster mana
Externí odkaz:
http://arxiv.org/abs/2104.14006
Autor:
Shafique, Muhammad, Naseer, Mahum, Theocharides, Theocharis, Kyrkou, Christos, Mutlu, Onur, Orosa, Lois, Choi, Jungwook
Publikováno v:
IEEE Design and Test (Volume: 37, Issue: 2, April 2020): 30-57
Machine Learning (ML) techniques have been rapidly adopted by smart Cyber-Physical Systems (CPS) and Internet-of-Things (IoT) due to their powerful decision-making capabilities. However, they are vulnerable to various security and reliability threats
Externí odkaz:
http://arxiv.org/abs/2101.02559
Autor:
Kyrkou, Christos
The increasing need for automated visual monitoring and control for applications such as smart camera surveillance, traffic monitoring, and intelligent environments, necessitates the improvement of methods for visual active monitoring. Traditionally,
Externí odkaz:
http://arxiv.org/abs/2012.06428
Autor:
Kyrkou, Christos
Deep Learning-based object detectors can enhance the capabilities of smart camera systems in a wide spectrum of machine vision applications including video surveillance, autonomous driving, robots and drones, smart factory, and health monitoring. Ped
Externí odkaz:
http://arxiv.org/abs/2007.13404
Publikováno v:
In Proceedings of the 13th International Conference on Distributed Smart Cameras (ICDSC 2019)
Visual intelligence at the edge is becoming a growing necessity for low latency applications and situations where real-time decision is vital. Object detection, the first step in visual data analytics, has enjoyed significant improvements in terms of
Externí odkaz:
http://arxiv.org/abs/1911.06091