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Schedule Interview NowMy name is Isaac M. and I have over 2 years of experience in the tech industry. I specialize in the following technologies: Computer Vision, YOLO, OpenCV, OCR Software, Image Processing, etc.. I hold a degree in Master of Computer Science (MSCS). Some of the notable projects I’ve worked on include: Text Extraction from Large Image, License plate recognition and traffic light detection, Automate Driving Test, Shelf Products Counts, OCR Enhancements – 26 Digit Number Extraction, etc.. I am based in Santo Domingo, Dominican Republic. I've successfully completed 14 projects while developing at Softaims.
I am a dedicated innovator who constantly explores and integrates emerging technologies to give projects a competitive edge. I possess a forward-thinking mindset, always evaluating new tools and methodologies to optimize development workflows and enhance application capabilities. Staying ahead of the curve is my default setting.
At Softaims, I apply this innovative spirit to solve legacy system challenges and build greenfield solutions that define new industry standards. My commitment is to deliver cutting-edge solutions that are both reliable and groundbreaking.
My professional drive is fueled by a desire to automate, optimize, and create highly efficient processes. I thrive in dynamic environments where my ability to quickly master and deploy new skills directly impacts project delivery and client satisfaction.
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Data IT
Unlock the potential of cutting-edge computer vision technology with my project! I've tackled the challenge of extracting text from large images, up to 700x14558 in size, in a single shot Using OpenCV, I've implemented robust line detection algorithms to segment the image into manageable chunks. These chunks undergo various preprocessing techniques, enhancing text readability and accuracy. Then, employing PaddleOCR, I've achieved remarkable text detection accuracy.
This project helps to define license plates and traffic light violations.
Introducing our state-of-the-art automated driving test application, where innovation meets precision Designed to streamline the evaluation process, I have incorporated cutting-edge technology, including the renowned YOLOv8 world model and VisionEye object mapping system. Our application revolutionizes the traditional driving test by harnessing the power of advanced computer vision techniques. With real-time object tracking and distance measurement powered by OpenCV, I provide unparalleled accuracy in assessing a vehicle's proximity to boundaries and obstacles.
Implemented a YOLOv8 detection model trained on SKU datasets, coupled with PyTorch OpenCLIP ViT embeddings for efficient product classification. This solution, deployed on a GCP GPU-integrated instance, revolutionized shelf product counting via a mobile app interface.
Goal: Create a lightweight Python OCR script to extract 26-digit reference numbers from scanned documents. Tasks: - Applied image preprocessing to enhance OCR accuracy - Used custom regex to isolate and validate 26-digit number patterns - Designed fallback handling for noisy scans or partially read numbers - Ensured clean and consistent output for automation workflows
Master of Computer Science (MSCS) in Computer science
2013-01-01-2016-01-01