Zobrazeno 1 - 10
of 248
pro vyhledávání: '"Beghdadi, Azeddine"'
Scene understanding plays an important role in several high-level computer vision applications, such as autonomous vehicles, intelligent video surveillance, or robotics. However, too few solutions have been proposed for indoor/outdoor scene classific
Externí odkaz:
http://arxiv.org/abs/2407.14658
The recent development of deep learning methods applied to vision has enabled their increasing integration into real-world applications to perform complex Computer Vision (CV) tasks. However, image acquisition conditions have a major impact on the pe
Externí odkaz:
http://arxiv.org/abs/2311.06976
Autor:
Khan, Zohaib Amjad, Beghdadi, Azeddine, Kaaniche, Mounir, Cheikh, Faouzi Alaya, Gharbi, Osama
Video quality assessment is a challenging problem having a critical significance in the context of medical imaging. For instance, in laparoscopic surgery, the acquired video data suffers from different kinds of distortion that not only hinder surgery
Externí odkaz:
http://arxiv.org/abs/2202.04517
Laparoscopic images and videos are often affected by different types of distortion like noise, smoke, blur and nonuniform illumination. Automatic detection of these distortions, followed generally by application of appropriate image quality enhanceme
Externí odkaz:
http://arxiv.org/abs/2106.06784
Publikováno v:
In Signal Processing: Image Communication February 2024 121
Autor:
Wang, Congcong, Zhao, Meng, Zhou, Chengguang, Dong, Nanqing, Khan, Zohaib Amjad, Zhao, Xintong, Alaya Cheikh, Faouzi, Beghdadi, Azeddine, Chen, Shengyong
Publikováno v:
In Computers in Biology and Medicine January 2024 168
Road signs detection and recognition in natural scenes is one of the most important tasksin the design of Intelligent Transport Systems (ITS). However, illumination changes remain a major problem. In this paper, an efficient ap-proach of road signs s
Externí odkaz:
http://arxiv.org/abs/2010.13844
Autor:
Khan, Zohaib Amjad, Beghdadi, Azeddine, Cheikh, Faouzi Alaya, Kaaniche, Mounir, Pelanis, Egidijus, Palomar, Rafael, Fretland, Åsmund Avdem, Edwin, Bjørn, Elle, Ole Jakob
Publikováno v:
Proc. SPIE 11316, Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment, 113160P (2020)
Laparoscopic videos can be affected by different distortions which may impact the performance of surgery and introduce surgical errors. In this work, we propose a framework for automatically detecting and identifying such distortions and their severi
Externí odkaz:
http://arxiv.org/abs/2003.12679
Human actions in videos are 3D signals. However, there are a few methods available for multiple human action recognition. For long videos, it's difficult to search within a video for a specific action and/or person. For that, this paper proposes a ne
Externí odkaz:
http://arxiv.org/abs/1907.11272
The object sizes in images are diverse, therefore, capturing multiple scale context information is essential for semantic segmentation. Existing context aggregation methods such as pyramid pooling module (PPM) and atrous spatial pyramid pooling (ASPP
Externí odkaz:
http://arxiv.org/abs/1907.06082