Zobrazeno 1 - 10
of 162
pro vyhledávání: '"Cheikh, Faouzi Alaya"'
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
Multi-label learning is a rapidly growing research area that aims to predict multiple labels from a single input data point. In the era of big data, tasks involving multi-label classification (MLC) or ranking present significant and intricate challen
Externí odkaz:
http://arxiv.org/abs/2401.16549
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:
d’Albenzio, Gabriella, Kamkova, Yuliia, Naseem, Rabia, Ullah, Mohib, Colonnese, Stefania, Cheikh, Faouzi Alaya, Kumar, Rahul Prasanna
Publikováno v:
In Computers in Biology and Medicine September 2024 179
Autor:
Munsif, Muhammad, Sajjad, Muhammad, Ullah, Mohib, Tarekegn, Adane Nega, Cheikh, Faouzi Alaya, Tsakanikas, Panagiotis, Muhammad, Khan
Publikováno v:
In Computers in Biology and Medicine September 2024 179
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
Autor:
Ullah, Mohib, Mahmud, Maqsood, Ullah, Habib, Ahmad, Kashif, Imran, Ali Shariq, Cheikh, Faouzi Alaya
For multi-target tracking, target representation plays a crucial rule in performance. State-of-the-art approaches rely on the deep learning-based visual representation that gives an optimal performance at the cost of high computational complexity. In
Externí odkaz:
http://arxiv.org/abs/2006.06134
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
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