1 code implementation • 26 Sep 2023 • Mathilde Papillon, Mustafa Hajij, Helen Jenne, Johan Mathe, Audun Myers, Theodore Papamarkou, Tolga Birdal, Tamal Dey, Tim Doster, Tegan Emerson, Gurusankar Gopalakrishnan, Devendra Govil, Aldo Guzmán-Sáenz, Henry Kvinge, Neal Livesay, Soham Mukherjee, Shreyas N. Samaga, Karthikeyan Natesan Ramamurthy, Maneel Reddy Karri, Paul Rosen, Sophia Sanborn, Robin Walters, Jens Agerberg, Sadrodin Barikbin, Claudio Battiloro, Gleb Bazhenov, Guillermo Bernardez, Aiden Brent, Sergio Escalera, Simone Fiorellino, Dmitrii Gavrilev, Mohammed Hassanin, Paul Häusner, Odin Hoff Gardaa, Abdelwahed Khamis, Manuel Lecha, German Magai, Tatiana Malygina, Rubén Ballester, Kalyan Nadimpalli, Alexander Nikitin, Abraham Rabinowitz, Alessandro Salatiello, Simone Scardapane, Luca Scofano, Suraj Singh, Jens Sjölund, Pavel Snopov, Indro Spinelli, Lev Telyatnikov, Lucia Testa, Maosheng Yang, Yixiao Yue, Olga Zaghen, Ali Zia, Nina Miolane
This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning.
no code implementations • 16 Apr 2022 • Mohammed Hassanin, Saeed Anwar, Ibrahim Radwan, Fahad S Khan, Ajmal Mian
However, the literature lacks a comprehensive survey on attention techniques to guide researchers in employing attention in their deep models.
1 code implementation • 24 Mar 2022 • Mohammed Hassanin, Abdelwahed Khamiss, Mohammed Bennamoun, Farid Boussaid, Ibrahim Radwan
3D human pose estimation can be handled by encoding the geometric dependencies between the body parts and enforcing the kinematic constraints.
Ranked #29 on 3D Human Pose Estimation on Human3.6M
no code implementations • 23 Jul 2021 • Mohammed Hassanin, Ibrahim Radwan, Salman Khan, Murat Tahtali
Multi-label recognition is a fundamental, and yet is a challenging task in computer vision.
no code implementations • 8 Dec 2020 • Mohammed Hassanin, Ibrahim Radwan, Nour Moustafa, Murat Tahtali, Neeraj Kumar
In it, a Defensive Feature Layer (DFL) is integrated with a well-known DNN architecture which assists in neutralizing the effects of illegitimate perturbation samples in the feature space.
no code implementations • 8 Dec 2020 • Mohammed Hassanin, Nour Moustafa, Murat Tahtali
Several research studies have been conducted to address this issue and build more robust deep learning models.
no code implementations • 18 Jul 2018 • Mohammed Hassanin, Salman Khan, Murat Tahtali
Nowadays, robots are dominating the manufacturing, entertainment and healthcare industries.