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Karim . Gasmi

Assistant Professor

Karim . Gasmi
6625
kgasmi@ju.edu.sa
Cyber Security - College of Applied
Collage
College of Applied
الكلية التطبيقية
Department
Cyber Security
الأمن السيبراني
Researches
18
18
Page Visits
No view count available

Current courses

Code Year Course Name
AITA 243 Data management

Recent courses

Code Year Course Name
ACCS 102 Introduction to Programming
CIS 101 Computer Skills
AITA 123 Programming and applications
AITA 243 Data management

Fm researches

Last Researches

Optimized Hybrid Deep Learning Framework for Early Detection of Alzheimer’s Disease Using Adaptive Weight Selection
Karim Gasmi
Enhanced brain tumor diagnosis using combined deep learning models and weight selection technique
Karim Gasmi
Optimized automated blood cells analysis using Enhanced Greywolf Optimization with integrated attention mechanism and YOLOv5
Karim Gasmi

fm info

Researches

Optimized Hybrid Deep Learning Framework for Early Detection of Alzheimer’s Disease Using Adaptive Weight Selection
Karim Gasmi
Enhanced brain tumor diagnosis using combined deep learning models and weight selection technique
Karim Gasmi
Optimized automated blood cells analysis using Enhanced Greywolf Optimization with integrated attention mechanism and YOLOv5
Karim Gasmi
Enhancing Medical Image Retrieval with UMLS-Integrated CNN-Based Text Indexing
Karim Gasmi
Modelling for disability: How does artificial intelligence affect unemployment among people with disability? An empirical analysis of linear and nonlinear effects
Karim Gasmi
A Granular Computing Classifier for Human Activity with Smartphones
Karim Gasmi
Usability-driven Mobile Application Development
Karim Gasmi
ViT-TB: Ensemble Learning Based ViT Model for Tuberculosis Recognition
Karim Gasmi
SolarRadnet: A novel variant input scoring optimized recurrent neural network for solar irradiance prediction
Karim Gasmi
Detecting Hateful and Offensive Speech in Arabic Social Media Using Transfer Learning
Karim Gasmi
Expansion of the olive crop based on modeling climatic variables using geographic information system (GIS) in Aljouf region KSA
Karim Gasmi
Improving Bert-Based Model for Medical Text Classification with an Optimization Algorithm
Karim Gasmi
Olive Disease Classification Based on Vision Transformer and CNN Models
Karim Gasmi
Hybrid Deep Learning Model for Answering Visual Medical Questions
Karim Gasmi
Optimal Deep Learning Model for Olive Disease Diagnosis Based on an Adaptive Genetic Algorithm
Karim Gasmi
Optimal Deep Neural Network-Based Model for Answering Visual Medical Question
Karim Gasmi
Document/query expansion based on selecting significant concepts for context based retrieval of medical images
Karim Gasmi
Graph-based methods for significant concept selection
Karim Gasmi

Education

BA
Monastir university - Higher Institute of Computer Science and Mathematics of Monastir
2008 - 2004
M.A.
Sfax university - National School of Engineers of Sfax
2010 - 2008
Ph.D.
Sfax university - National School of Engineers of Sfax
2017 - 2012

Certifications

IEEE Xplore: Search strategies to optimize your research
2021 - 2021
Introduction to ASCE Library: Civil Engineering Research on the Platform
2024 - 2024
Wiley Digital Archiving - WDA
2021 - 2021

Experience

Contracted Assistant professor
Sousse university
2010 - 2015
Assistant professor
Sousse University
2015 - 2018
Assistant Professor
Jouf university
2018 - 2024

Projects

Visual Question Answering Using Deep Learning
2021 - 2022
CNN-based Text Indexing for Medical Image Retrieval
2024 - 2024

In these last years, Convolutional Neural Network (CNN) models have shown significant performance
improvements in several fields as image classification, and Natural Language Processing (NLP). Given
their success in image classification, it seems that they should have an important impact on image
retrieval.
However, until now, such success has not yet been accomplished for medical image retrieval, especially
text-based medical image retrieval (TBMIR) tasks. It could be due to the complexity of the ranking

An Optimal Deep Learning and Ensemble Learning Framework for Early Detection of Alzheimer's Disease
2024 - 2024

Alzheimer's disease presents a significant and unyielding challenge, particularly among the elderly
population, where its insidious progression of memory loss casts a profound global impact, especially on
individuals aged 65 and above. Detecting this condition early is paramount for a comprehensive
evaluation of its evolving symptoms. However, the current reliance on manual diagnosis by healthcare
professionals proves to be both labor-intensive and susceptible to inaccuracies, primarily due to the sheer

Usability Engineering in Mobile Application Development
2021 - 2022
Automatic Classification and Segmentation of tuberculosis based on Optimization Algorithms
2021 - 2022
Classification of MRI Brain Tumors Based on Registration Preprocessing and Deep Belief Networks ا
2024 - 2024

In recent years, augmented reality has emerged as an emerging technology with huge potential in imageguided surgery, and in particular, its application in brain tumor surgery seems promising. Augmented
reality can be divided into two parts: hardware and software. Further, artificial intelligence and deep
learning in particular have attracted great interest in research to be used in the medical field, especially in
the diagnosis of brain tumors. Recent research from the Saudi Cancer Registry, conducted in 2014, found

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