Logan Hughes
AI Virtual Staging at colossis.io
Logan Hughes is a PhD candidate in Computer Vision at Stanford University, where his research focuses on generative image models and scalable visual AI pipelines. He investigates evaluation metrics for synthetic imagery and optimization of batch inference workflows for production systems. Deep experience. Intellectual curiosity.
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Recent articles by Logan Hughes
- How much to stage listing photos: TensorRT 10.3 FP8 vs FP16 — $39 per 1,000 on AWS p5.48xlarge in 2026 November 6, 2026
- Stable Diffusion vs Flux vs Midjourney: why FID drift can't be settled at 1024px November 3, 2026
- How the 2024 USGS LULC Update Affects Training Data: A Verify-Before-You-Commit Guide October 31, 2026
- AI Wing Chair: Fréchet Inception Distance vs CLIP Image Quality Assessment: 0.12 Pass/Fail October 28, 2026
- Mother's Day Tribute Art: 3-Pass Latent Compositing vs Texture Loss October 25, 2026
- Fake Home Photo Tests: 10 Step Pipeline, Pick Half in 2026 October 22, 2026
- Yacht Interior Prompts: How to Verify Layout Accuracy Before You Commit October 19, 2026
- FID vs KID for Text-to-Image: Sample Floors and Reporting Rules October 16, 2026