Cui, Chen Chen, Jian
Published in
Journal of Physics: Conference Series
Considering the difficulty to built mechanisms models for complex industrial processes, this paper proposes a data-driven modelling method. This method includes a process for processing real industrial data and an improved deep learning algorithm. The data processing flow completes the basic preparation work for the raw data, and the improved algor...
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 Ml 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...
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...
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...
