Applied and Freelance Research Projects
Published:
This page summarizes applied and freelance research projects completed between 2017 and 2022.
Overview
These projects covered a wide range of academic and industrial problems in medical imaging, computer vision, machine learning, and intelligent decision systems.
Domains
- Medical imaging using MRI, CT, dermoscopy, and fundus images.
- Computer vision pipelines for segmentation, enhancement, and stitching.
- Intelligent decision systems using machine learning and ensemble methods.
- Optimization-based problem solving.
Deliverables
- End-to-end research prototypes.
- GUI-based applications.
- Healthcare-oriented computer vision systems.
- Image processing and machine learning pipelines.
Completed Research Projects
Before and during my early research career, I completed a wide range of applied research and freelance projects in Computer Vision, Machine Learning, Medical Imaging, and Image Processing. These projects were delivered for international clients, academic collaborators, and student researchers, with several implementations made publicly available on GitHub. The original project archive is available here: Completed Projects Repository. :contentReference[oaicite:0]{index=0}
🚀 Highlights from Applied Research and Freelance Projects
A selection of computer vision, machine learning, medical imaging, and AI systems developed for academic and industrial clients between 2017 and 2022.
Figure 1. Representative Computer Vision, Machine Learning, and Medical Imaging projects developed for international clients and research collaborators.
Figure 2. Examples of applied AI systems including medical image analysis, computer vision applications, intelligent decision systems, and machine learning solutions delivered during freelance and research collaborations.
Figure 3. Bone Cancer detection: Examples of applied AI systems including medical image analysis, computer vision applications, intelligent decision systems, and machine learning solutions delivered during freelance and research collaborations.
Figure 4. Driver Drowsiness System: Examples of applied AI systems including computer vision applications, intelligent decision systems, and machine learning solutions delivered during freelance and research collaborations.
Figure 5. Image Denoising: Examples of applied AI systems including computer vision applications, intelligent decision systems, and machine learning solutions delivered during freelance and research collaborations.
Figure 6. Plaque Identification: Examples of applied AI systems including medical imaging, computer vision applications, intelligent decision systems, and machine learning solutions delivered during freelance and research collaborations.
| Year | Project | Domain | Platform | Link |
|---|---|---|---|---|
| 2022 | PSO and Ensemble Learning Models to Predict Heart Diseases | Healthcare AI / ML | Python, Jupyter | Open Project |
| 2022 | Lungs Nodule Cancer Detection and Classification | Medical Imaging | MATLAB GUI | Open Project |
| 2022 | Polynomial Regression Based on Deep Learning | Deep Learning | MATLAB, Python | Open Project |
| 2022 | Image Matching Using Point Features and Epipolar Lines | Computer Vision | MATLAB, Python | Open Project |
| 2022 | DOM Creation using Computer Vision and Machine Learning | Computer Vision / ML | MATLAB | Open Project |
| 2022 | Skin Lesion Detection, Segmentation, and Classification | Medical Imaging | MATLAB GUI | Open Project |
| 2022 | Brain Tumor Detection and Identification | Medical Imaging | MATLAB GUI | Open Project |
| 2021 | Ant Movement Simulator using Genetic Algorithm | Optimization / Simulation | MATLAB | Open Project |
| 2021 | Fruit Classification for Automated Harvesting and Packing | Computer Vision | MATLAB GUI | Open Project |
| 2021 | Image Fusion Based on Correlation | Image Processing | MATLAB | Open Project |
| 2021 | Bone Cancer Detection using MRI Images | Medical Imaging | MATLAB GUI | Open Project |
| 2021 | Driver Drowsiness Detection using Facial Features | Computer Vision | MATLAB GUI | Open Project |
| 2021 | Image Denoising using Contourlet Feature Pyramid | Image Processing | MATLAB | Open Project |
| 2020 | Skin Segmentation from Face Images using DLIB | Computer Vision | MATLAB | Open Project |
| 2020 | Image Stitching using SIFT Features for Panorama Creation | Computer Vision | MATLAB | Open Project |
| 2020 | Patch-Based Image Enhancement using CLAHE | Image Processing | MATLAB | Open Project |
| 2019 | Low-Light Image Enhancement | Image Processing | MATLAB | Open Project |
| 2019 | Blood Vessel Extraction from Fundus Images | Medical Imaging | MATLAB | Open Project |
| 2019 | Document Classification Based on Deep Learning | Deep Learning | MATLAB | Open Project |
| 2018 | Person Re-Identification using Multiple Cameras | Computer Vision | MATLAB | Open Project |
| 2018 | Heart Vein Blockage Detection | Healthcare AI | MATLAB | Open Project |
| — | Fake News Detection using ML Classifiers | Machine Learning / NLP | Python | Open Project |
| — | Graph Neural Network on MNIST | Deep Learning / GNN | Python | Open Project |
| — | Diabetic Retinopathy Classification | Medical Imaging | MATLAB | Open Project |
| — | Automatic Polyp Detection and Stomach Disease Detection | Medical Imaging | MATLAB | Open Project |
| — | Skin Lesion Segmentation using Active Contour and JSEG | Medical Imaging | MATLAB | Open Project |
Project Areas
These projects can be grouped into five major areas:
- Medical Imaging: lung nodules, brain tumor detection, bone cancer detection, blood vessel extraction, diabetic retinopathy, skin lesion analysis, and polyp detection.
- Computer Vision: image matching, image stitching, person re-identification, driver drowsiness detection, fruit classification, and DOM creation.
- Image Processing: low-light enhancement, patch-based enhancement, image fusion, denoising, and segmentation.
- Machine Learning: fake news detection, heart disease prediction, polynomial regression, and ensemble learning.
- Deep Learning: document classification, Graph Neural Networks, and medical image classification.
These applied projects helped me build strong practical experience in transforming research ideas into working software prototypes, including preprocessing, model development, GUI design, experimentation, evaluation, and delivery of usable AI systems.
Technologies
MATLAB · Python · Deep Learning · Machine Learning · Image Processing · Computer Vision