مشروع البحث: A NOVEL STATISTICAL APPROACH FOR FEATURE EXTRACTION: APPLYING TO MACHINE LEARNING METHODS
| dc.contributor.advisor | Prof. Dr. Yüksel ÇELİK | |
| dc.date.accessioned | 2025-10-28T09:09:26Z | |
| dc.date.available | 2025-10-28T09:09:26Z | |
| dc.description | Machine learning algorithms, particularly those in computer vision, have proven to be highly effective in processing these datasets, offering solutions that are faster, more accurate, and less prone to human error than traditional methods However, the application of AI and ML to medical imaging is challenging. Medical images are inherently complex and vary significantly due to patient demographics, imaging techniques, and disease manifestations. | |
| dc.description.abstract | The AI and ML revolution has revolutionized digital image analysis, transforming industries from autonomous vehicles and robotics to healthcare, environmental monitoring, and forecasting. These technologies have opened up unprecedented opportunities for innovation by enabling systems to learn from data, identify patterns, and make decisions with little or no human intervention [1]. In engineering, AI and ML are widely used for prediction, optimization, and automation, while in healthcare, they have become indispensable tools for diagnosis, treatment planning, patient care, medical image profiling, and disease prediction. Among their many applications, medical image analysis stands out as an area where AI and ML have made great strides, particularly in automating the interpretation of complex datasets, such as X-rays, MRIs, | |
| dc.identifier | 796 | |
| dc.identifier.uri | https://dspace.academy.edu.ly/handle/123456789/1818 | |
| dc.subject | APPLYING TO MACHINE LEARNING METHODS | |
| dc.title | A NOVEL STATISTICAL APPROACH FOR FEATURE EXTRACTION: APPLYING TO MACHINE LEARNING METHODS | |
| dspace.entity.type | Project | |
| project.endDate | 2025 | |
| project.funder.name | هندسة الحاسوب | |
| project.investigator | أشرف رافع محمد | |
| project.startDate | 2024 | |
| relation.isOrgUnitOfProject | d70558aa-ae49-4279-9e5d-a763f40a7531 | |
| relation.isOrgUnitOfProject.latestForDiscovery | d70558aa-ae49-4279-9e5d-a763f40a7531 |