For my first post, I’m sharing a letter @NVIDIA signed on why open models matter.
AI will transform every industry, power every company, and be built by every country.
Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty.
The world needs both frontier closed models and frontier open models.
https://t.co/AUKzoQ5Ikb
Excited to share that our paper, "Two-Stage Noise-Reduced Pneumonia Detection in Chest X-Ray Images using Denoising Autoencoder–CNN Integration," has been published at IEEE QPAIN 2026!
A proud milestone in my research journey. 🎉
The proposed DAE-CNN outperformed a CNN-only baseline, showing that learnable denoising can significantly improve the robustness of AI-assisted pneumonia detection from chest X-ray images, especially for screening applications.
Pneumonia diagnosis from chest X-rays can be affected by image noise and poor quality. To address this, we developed a two-stage deep learning framework that combines a Denoising Autoencoder (DAE) with a CNN for more robust detection.
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