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Detecting a goal is easy. Knowing whether the ball actually crossed the line is a geometry problem.
In this #TactiVision R&D module, I combine:
goal keypoint detection to anchor the goal geometry
goal segmentation to estimate the goal area
confidence filtering
geometric projection
polygon-based validation
temporal stabilization The main challenge is robustness: a single weak keypoint near the post can shift the projected goal line, so the system must decide which geometric information can be trusted before confirming a goal. This module is part of my broader football Computer Vision pipeline for detection, tracking, pitch mapping and tactical analysis
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I help founders communicate themselves clearly through pitch deck presentations.
Even a scoring app deserves this design quality 🔥
Great work! The design is very modern. Top!
An AI engineer should make the path from input to output inspectable. In Tenderseal, I shaped an AI-assisted workflow where users READ source material, ASK focused questions, and DRAFT a response while keeping the underlying material close to the work. I build with approvals around consequential actions, read-back after integrations, and a clear boundary between model output and human judgment. If your AI feature needs a dependable workflow, message me.
Great Design :)