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Schedule Interview NowMy name is Antonio L. and I have over 2 years of experience in the tech industry. I specialize in the following technologies: Computer Vision, Object Detection, Object Detection & Tracking, Image Processing, Artificial Intelligence, etc.. I hold a degree in Bachelor of Engineering (BEng), Master of Science (MS). Some of the notable projects I've worked on include: Real-Time Retail Customer Behavior Analytics Platform, Soccer Game Analysis System, Interactive Local Image Segmentation Tool Using Ultralytics SAM2, Squash Game Analysis System. I am based in Tijuana, Mexico. I've successfully completed 4 projects while developing at Softaims.
My passion is building solutions that are not only technically sound but also deliver an exceptional user experience (UX). I constantly advocate for user-centered design principles, ensuring that the final product is intuitive, accessible, and solves real user problems effectively. I bridge the gap between technical possibilities and the overall product vision.
Working within the Softaims team, I contribute by bringing a perspective that integrates business goals with technical constraints, resulting in solutions that are both practical and innovative. I have a strong track record of rapidly prototyping and iterating based on feedback to drive optimal solution fit.
I'm committed to contributing to a positive and collaborative team environment, sharing knowledge, and helping colleagues grow their skills, all while pushing the boundaries of what's possible in solution development.
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Nola
This project developed an AI-powered video analytics platform that captures and analyzes customer behavior in retail stores in real-time. The system uses computer vision to detect individuals, estimat
The Soccer Game Analysis System is a computer vision prototype designed to automate the detection, tracking, and mapping of soccer players using YOLOv8 and advanced homography techniques. The system c
This tool employs Meta’s SAM2 model integrated through Ultralytics to achieve precise object segmentation locally. Built with a Tkinter GUI, the application enables users to input positive and negativ
The Squash Game Analysis project utilizes a computer vision system to track and analyze squash players from video feeds. Leveraging YOLO object detection, the system identifies player movements, calcu
Bachelor of Engineering (BEng) in Mechatronics
2016-01-01-2020-01-01
Master of Science (MS) in Computer Vision
2021-01-01-2023-01-01