Brain Tumor Classification using Vision Transformer with Selective Cross-Attention Mechanism and Feature Calibration
MAL Khaniki, A Golkarieh, M Manthouri - arXiv preprint arXiv:2406.17670, 2024 - arxiv.org
Brain tumor classification is a challenging task in medical image analysis. In this paper, we
propose a novel approach to brain tumor classification using a vision transformer with a …
propose a novel approach to brain tumor classification using a vision transformer with a …
Twin Transformer using Gated Dynamic Learnable Attention mechanism for Fault Detection and Diagnosis in the Tennessee Eastman Process
MA Labbaf-Khaniki, M Manthouri - arXiv preprint arXiv:2403.10842, 2024 - arxiv.org
Fault detection and diagnosis (FDD) is a crucial task for ensuring the safety and efficiency of
industrial processes. We propose a novel FDD methodology for the Tennessee Eastman …
industrial processes. We propose a novel FDD methodology for the Tennessee Eastman …
Disentangled Representation Learning vs. Resnet 18 for White Matter Lesion Detection in Multiple Sclerosis: A Comparative Study Including PCAEClassifier …
H Ajami - 2024 - search.proquest.com
Multiple sclerosis is one of the critical autoimmune diseases that require early detection. The
central nervous system (CNS) is demyelinated by multiple sclerosis (MS), which causes …
central nervous system (CNS) is demyelinated by multiple sclerosis (MS), which causes …
Enhanced fault detection and cause identification using integrated attention mechanism
MAL Khaniki, A Golkarieh, H Nouri… - arXiv preprint arXiv …, 2024 - arxiv.org
This study introduces a novel methodology for fault detection and cause identification within
the Tennessee Eastman Process (TEP) by integrating a Bidirectional Long Short-Term …
the Tennessee Eastman Process (TEP) by integrating a Bidirectional Long Short-Term …
Hierarchical SegNet with Channel and Context Attention for Accurate Lung Segmentation in Chest X-ray Images
Lung segmentation in chest X-ray images is a critical task in medical image analysis,
enabling accurate diagnosis and treatment of various lung diseases. In this paper, we …
enabling accurate diagnosis and treatment of various lung diseases. In this paper, we …
Vision transformer with feature calibration and selective cross-attention for brain tumor classification
MAL Khaniki, M Mirzaeibonehkhater… - Iran Journal of Computer …, 2024 - Springer
Brain tumor classification is a challenging task in medical image analysis, with significant
implications for patient diagnosis and treatment. The objective of this paper is to propose a …
implications for patient diagnosis and treatment. The objective of this paper is to propose a …
BetaVAEClassifier vs PCAEClassifier: investigating variational autoencoder and classification for accurate identification of white lesions in multiple sclerosis brain …
Multiple sclerosis is one of the critical autoimmune diseases that require early detection. The
central nervous system (CNS) is demyelinated by multiple sclerosis (MS), which causes …
central nervous system (CNS) is demyelinated by multiple sclerosis (MS), which causes …
Comparative analysis of white matter lesion segmentation in multiple sclerosis patients' MRIs: evaluating the results of FCNN architecture and CVIPtools software on …
This study builds upon our previous investigations into identifying and classifying white
matter lesions on the brain surfaces of multiple sclerosis patients using both traditional …
matter lesions on the brain surfaces of multiple sclerosis patients using both traditional …
Adaptive Terminal Sliding Mode Control Using Deep Reinforcement Learning for Zero-Force Control of Exoskeleton Robot Systems
This paper introduces a novel zero-force control method for upper-limb exoskeleton robots,
which are used in a variety of applications including rehabilitation, assistance, and human …
which are used in a variety of applications including rehabilitation, assistance, and human …
Crisis Alpha: A High-Performance Trading Algorithm Tested in Market Downturns
MK Gharanchaei, R Babazadeh - arXiv preprint arXiv:2409.14510, 2024 - arxiv.org
Forming quantitative portfolios using statistical risk models presents a significant challenge
for hedge funds and portfolio managers. This research investigates three distinct statistical …
for hedge funds and portfolio managers. This research investigates three distinct statistical …