Garment Type Classification Vision AI
A CNN classifier and data pipeline for apparel categories whose definitions differ from storefront to storefront
- category classification accuracy
- 90%+
- images used to train the model on a single RTX 2080
- 32,474
What it does
- I trained a CNN on 32,474 crawled images with a single RTX 2080.
- I wrote the Python pipeline that does the vector-comparison data cleansing and post-processing.
Stack
Python TensorFlow Keras CNN
Skills demonstrated
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Product & Full-stack
TypeScript · JavaScript · Python · C/C++ · C# · Java · Next.js · Nuxt.js · Vue.js · React · React Native · Expo · PostgreSQL · Supabase · AWS · GCP · Docker · UX design for ERP, CRM and LMS operational screens
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Research Methodology & Benchmarking
Pre-registered hypotheses, rejection thresholds and the commit hash at registration · Paired statistical tests implemented directly (McNemar · Fisher · Wilcoxon · Holm-Bonferroni) · Same-arm controls to establish the noise floor; pooled replicates to test whether significance reproduces · Blinded LLM judge panels, false-negative controls, and deterministic scoring with no judge · Adversarial refutation rounds; null results and failures to reproduce on the public record; do-not-re-propose lists · Public benchmarks measured first-hand: SWE-bench · MuSiQue · DP-Bench · OmniDocBench
Recognised in
- TensorFlow Korea — Rising Star TensorFlow Korea Honours & Activities