The best way to understand mind is to build it. Interested in cognitive systems, currently learning CV & NLP. Thinking about thinking
The field of Vision-Language Models (VLMs) has witnessed a rapid surge, with diverse approaches emerging, including MultiModal Large Language Models (MLLMs) and Large Multimodal Models (LMMs). Notable examples of these models include Flamingo, LLaVA,...
Foundational models represent a significant advancement in machine learning, characterized by their large-scale training on extensive datasets comprising unlabeled or semi-labeled data. These models exhibit remarkable versatility, serving as a basis ...
Vector Space: We define vector space as a set of all elements that are closed under vector addition and scalar multiplication operations. (closed means that after some operation on vector you will again get vector) Norm: Norm is a function that takes...
Local features: Detection: Identify the interest points Description: Extract feature vector descriptor surrounding each interest point. Matching: Determine correspondence between descriptors in two views Interest Point: Expressive texture: The po...
If you have not read my previous blog then kindly read it at this blog, as it will be a lot helpful to understand this blog :) In the previous blog, I have talked about prewitt and sobel edge detection methods, so lets move on to others. Marr hildre...
I am assuming that you are familiar with what images are and how they are represented. You can read more about images, color in my previous blogs or just google what is new to you and is not explained :) Histogram: Histogram is how frequently gray l...
This post is a continuation of my previous Blog. Subtractive mixing and inks Let's start with subtractive mixing and inks. Unlike what we discussed in the previous blog, pigments in paint interact/mix subtractively. The simplest model to explain how...
Both biological and artificial receptors respond differently to different wavelengths. This response captures some information that is perceived by the brain as color. Color space is a dense forest, one might dedicate his life to exploring the jungle...
Exploratory Data Analysis (EDA) is used to analyze and investigate data sets. It's to get better insight into the data set so that we can summarize their main characteristics. The better you understand the data, the better model you will make. Having...