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pro vyhledávání: '"Oussalah, Mourad"'
The surge of interest in data augmentation within the realm of NLP has been driven by the need to address challenges posed by hate speech domains, the dynamic nature of social media vocabulary, and the demands for large-scale neural networks requirin
Externí odkaz:
http://arxiv.org/abs/2404.00303
In today's age, social media reigns as the paramount communication platform, providing individuals with the avenue to express their conjectures, intellectual propositions, and reflections. Unfortunately, this freedom often comes with a downside as it
Externí odkaz:
http://arxiv.org/abs/2312.10528
Conventional feature extraction techniques in the face anti-spoofing domain either analyze the entire video sequence or focus on a specific segment to improve model performance. However, identifying the optimal frames that provide the most valuable i
Externí odkaz:
http://arxiv.org/abs/2309.04958
With the growing availability of databases for face presentation attack detection, researchers are increasingly focusing on video-based face anti-spoofing methods that involve hundreds to thousands of images for training the models. However, there is
Externí odkaz:
http://arxiv.org/abs/2308.12364
Face presentation attacks (PA), also known as spoofing attacks, pose a substantial threat to biometric systems that rely on facial recognition systems, such as access control systems, mobile payments, and identity verification systems. To mitigate th
Externí odkaz:
http://arxiv.org/abs/2307.02858
Face Presentation Attack Detection (PAD) plays a pivotal role in securing face recognition systems against spoofing attacks. Although great progress has been made in designing face PAD methods, developing a model that can generalize well to unseen te
Externí odkaz:
http://arxiv.org/abs/2301.02145
Autor:
Muhammad, Usman, Oussalah, Mourad
Without deploying face anti-spoofing countermeasures, face recognition systems can be spoofed by presenting a printed photo, a video, or a silicon mask of a genuine user. Thus, face presentation attack detection (PAD) plays a vital role in providing
Externí odkaz:
http://arxiv.org/abs/2208.13164
Autor:
Muhammad, Usman, Oussalah, Mourad
Face presentation attack detection (PAD) plays an important role in defending face recognition systems against presentation attacks. The success of PAD largely relies on supervised learning that requires a huge number of labeled data, which is especi
Externí odkaz:
http://arxiv.org/abs/2208.13070
Autor:
Panchanathan, Anandharuban, Ahrari, Amirhossein, Ghag, Kedar Surendranath, Mustafa, Syed, Haghighi, Ali Torabi, Kløve, Bjørn, Oussalah, Mourad
Publikováno v:
In Earth-Science Reviews November 2024 258