Images are blurred so you can’t tell how messy my desk is.

Motivation

For some of us, one of the changes brought by working from home is that we tend to sit for longer in front of computers. Without the need to go to a meeting room on another floor or the chance to grab a coffee from the coffee shop downstairs, we attend different meetings on the same chair and skip work breaks simply because there is nowhere to go.

During my Christmas staycation, I realized that my activity level, as suggested by Oura ring, has been declining in the second half of the year :( which pushed me to think about…


Summary: since case numbers are heavily dependent on test numbers, it is not enough to look at the case numbers without referencing the test numbers. This article proposes a new way to visualize the data ans understand where we are.

I’ve also made a presentation on my personal channel. The purpose of the presentation is to provide a new perspective to understand the development of the pandemic. It does not provide any advice regarding medical or public health issues. Due to limited time, I only looked at the state-level data in the US.

The data comes from 3 sources…


As of Feb 3, there are over 20,000 confirmed cases, more than 23,000 suspected cases and over 400 deaths in China. Confirmed cases are found in every province of China.

It has become my daily routine to check the latest updates, first thing in the morning.

When I got a chance to check the latest edition of the Economist, I was hoping to find insightful reports of the ongoing Coronavirus crisis. Prior to that, I, like millions of the Chinese people, had lived through a most dreadful Lunar New Year that was filled with fear, sorrow and anger.

But what…


As a state-of-the-art real-time object detection model, YOLO has been widely studied and commonly implemented by CV engineers. In a project which aims to build a wearable for vision-impaired users, I modified the original YOLO v3 model to make it safer and more robust.

2 main changes I made to make YOLO more adaptable: (1) enable YOLO to work in dark environments, and (2) add class-sensitive loss functions to make it safer. This post focuses on the first main change.

Feedback is very welcome and appreciated.

My major takeaway from the project

  1. Think outside the box.
  2. Solving real-life problems is much more complicated than building models. Corner cases and small details add an extra challenge to the technical problems, and also make the whole learning experience rewarding.

The goal: improve YOLO’s performance in low-light environments

While YOLOv3 models can achieve mAP-50 scores of over 50% on the COCO 2014 validation set, their performance will decrease significantly…


Introduction

Super resolution is a challenging task which enhances the resolution of low-resolution images. It has attracted significant research interest in recent years, and many breakthroughs have been made. This project will be focusing on one of the breakthrough models: the Super-Resolution GAN model. (SRGAN)

This blog post has 4 major parts: an introduction of the original model from the original paper, an examination of one implementation on a specific dataset (dog images), a comparison of 4 modified models, and a test of how the model can generalize on images other than dogs. …

Irene Z

Data Scientist; interested in Computer Vision

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