Welcome to my miscellaneous writings section!!
Browse through my posts by selecting a category from the navigation bar on the left.
In Video Assessment Part 2, we looked at spatial quality metrics — how sharp, clear, and natural individual frames look. But for livestreaming or video conferencing, another dimension matters just as much: time.
(Even if each frame looks perfect, a video can still feel low-quality if motion is jerky, frames are dropped, or the playback stutters.)
In Video Quality Part 1 we introduced the basic idea of video quality metrics and the difference between reference-based and no-reference approaches.
In this part, we’ll go a bit deeper and look at how these methods work at a conceptual level, focusing on spatial quality—how individual video frames are evaluated for issues like blur, noise, and compression artifacts.
Video quality metrics like PSNR, SSIM, and VMAF were originally developed to evaluate video fidelity in controlled, offline settings, providing objective measurements of how closely a compressed or transmitted video matches its original.
In this series of articles on Video Quality Metrics, we’ll go through various approaches across different scenarios—ranging from offline comparison to live streaming, and from spatial to temporal quality assessment.
JavaScript frameworks like React and Vue were created to dramatically boost developer productivity, often enabling developers to write code up to 10 times faster.
But now, with the rise of AI-powered code generators, it's worth asking: is it time to reconsider using plain vanilla JavaScript, especially when AI can produce it just as quickly?
While Docker and Python virtual environments both help manage software and dependencies, they have important differences.
This section compares Docker and Python virtual environments to help understand these differences and choose the right tool for one's needs.
While the distinction between GUI apps and game-like interfaces may seem straightforward, choosing the right approach can sometimes be unexpectedly challenging.
Once upon a time, error handling in code was simple: just good old if-else checks. No drama, no flair.
Then came try-catch, promoted as a cleaner, more elegant way to handle errors. And it quickly became the new standard in many languages.
You hear people say “work smart, not hard” all the time. And sure, it sounds great—who doesn’t want to be efficient?
A lot of folks take it the wrong way and end up thinking they don’t have to go through the struggle. Like, just be clever and everything will magically fall into place. That mindset? It can lead to laziness, entitlement, and chasing shortcuts instead of actually doing the work.
Structured programming became mainstream in the 1970s and 1980s. It is a programming paradigm that emphasizes writing clear, logical, and well-organized code using:
In this post, I’ll share some insights on some basic considerations in order to be able to utilize N3IWF for seamless handover between 5G networks and Wifi.