Research, Notes & Progress
Documenting mathematical derivations, physical hardware experiments, and computational insights as they evolve.
Theoretical knowledge only settles when tested against physical silicon and real-world forces.
Chronological Journey
2024 – 2027Active Study Benchmarks
TrackingPublished Research Notes
Residual Learning — More Doesn’t Always Mean Good
A personal research note taken from the famous research paper "Deep Residual Learning for Image Recognition" (He et al., the ResNet paper) — exploring why deeper networks suffer from the degradation problem and how residual shortcut connections solved it.
#2 You Only Look Once (YOLO) — Real-Time Object Detection
A personal research note on the seminal YOLO paper (Redmon et al.) — reframing object detection from complex multi-stage pipelines into a single unified regression problem running at 45–155 FPS.
UAV Disaster Mapping
Rapid post-disaster reconnaissance using aerial photogrammetry and semantic segmentation in mountainous topography.
From Vacuum Tubes to Modern Chips
How does a computer actually compute? Tracing computing history from 1804 punch cards to 1940s vacuum triodes, relays, and early binary switching logic.
Computer Vision Experiments
Hands-on experimentation with image processing pipelines, feature descriptors, camera calibrations, and optical flow.