Khan, Adil
Neurological conditions often manifest as gait disorders, frequently linked to spasticity. Botulinum Toxin Type A (BTX-A) injectionscommonly treat spasticity-related gait issues. Achieving optimal treatment outcomes with a favourable benefit-risk ratio remains crucial. Kinematic improvements obtained by this treatment are sometimes very efficient, ...
Soh, Mathurin Nguetoum Likeufack, Anderson
In this paper, we propose a hybrid approach for solving the symmetric traveling salesman problem. The proposed approach combines the ant colony algorithm (ACO) with neural networks based on the attention mechanism. The idea is to use the predictive capacity of neural networks to guide the behaviour of ants in choosing the next cities to visit and t...
Arezki, Bouzid Feng, Fangchen Mokraoui, Anissa
In this paper, we present a novel transformer-based architecture for end-to-end image compression. Our architecture incorporates blocks that effectively capture local dependencies between tokens, eliminating the need for positional encoding by integrating convolutional operations within the multi-head attention mechanism. We demonstrate through exp...
Lagzouli, Amine Pivonka, Peter Cooper, David M.L. Sansalone, Vittorio Othmani, Alice
The precise segmentation of cortical and trabecular bone compartments in high-resolution micro-computed tomography (μCT) scans is crucial for evaluating bone structure and understanding how different medical treatments and mechanical loadings affect bone morphology, offering valuable insights into osteoporosis. In this work, we propose a novel hybr...
Abdilrahim, Ahmad Mokhtar, Alsiraira
This study explores how attention mechanisms impact representation distributions within neural networks, focusing on catastrophic forgetting and robustness to input noise. We compare Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU), their attention-enhanced counterparts (RNNA, LSTMA, GRUA), and the Transfor...
Omar, Alfakir
Ambient temperature poses a significant challenge to the performance of mobile phones, impacting their internal thermal flow and increasing the likelihood of overheating, leading to a compromised user experience. The knowledge about the ambient temperature in mobile phones is crucial as it assists engineers in correlating external factors with inte...
Stival, Leandro da Torres, Ricardo Silva Pedrini, Helio
Video colorization is a challenging task, demanding deep learning models to employ diverse abstractions for a comprehensive grasp of the task, ultimately yielding high-quality results. Currently, in example-based colorization approaches, the use of attention processes and convolutional layers has proven to be the most effective method to produce go...
Doorshi, Raoof
Odometry estimation plays a key role in facilitating autonomous navigation systems. While significant consideration has been devoted to research on monocular odometry estimation, sensor fusion techniques for Stereo Visual Odometry (SVO) have been relatively neglected due to their demanding computational requirements, posing practical challenges. Ho...
Slimani, Karim Tamadazte, Brahim Achard, Catherine
This paper introduces a new method for 3D points cloud registration based on deep learning. The architecture is composed of three distinct blocs: (i) an encoder with a convolutional graph-based descriptor that encodes the immediate neighborhood of each point and an attention mechanism that encodes the variations of the surface normals. Such descrip...
Mili, Manel Kerkeni, Asma
Advancements in deep learning algorithms for medical imaging, combined with the integration of cyberworlds, have shown great promise in providing precise diagnostic results. One area of interest is the application of these advancements in enhancing personalized treatment of gliomas, a particularly challenging type of brain tumor, by providing more ...