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Transformers have established their importance in natural language processing (NLP), their ability to learn a general language representation and transfer it to specific tasks has made them invaluable. And with the advent of Vision Transformer (ViT)...

Continuing from where we left off in the previous part of the statistics series, let's talk about the remaining probability distributions, starting with the binomial distribution. Binomial Distribution Bernoulli Trial Bernoulli trial is a random expe...

In the first two parts of this series, we covered the fundamental concepts of statistics namely measures of central tendency and measures of dispersions, and the basics of probability. Check them out if you haven't already: Basics Of Statistics & Wh...

With the advent of better and faster computer vision models, panoptic driving perception systems have become an essential part of autonomous driving. So much so that companies like Comma.ai are ditching additional sensors like Lidars and radars altog...

YOLOR, You Only Learn One Representation, is a state-of-the-art object detection model that is 88% faster than Scaled-YOLOV4 and 3.8% more accurate than PP-YOLOV2. This makes it the best YOLO variant to date. YOLOR has a unified network that models h...

If you come from a statistical or data science background you must be familiar with the importance of data cleaning and feature engineering. Well, what's the computer vision equivalent of the two? Image transformations. From removing noise and fixing...