An new framework to detect highly informative and discriminative Keypoints from the dense descriptors.

In recent years, Computer vision has opened up several new possibilities in almost every field that we can imagine. The whole focus of research has been shifted from classification to various applications like SLAM, Multiple object tracking, Information retrieval, Camera localization, etc. Extracting meaningful descriptions from the data has been a crucial problem in their pipeline. It involves the process of detecting keypoints using feature detectors and extracting information based on feature descriptors. The final features are expected to be very informative, can be easily localized, and should be adapted to the different needs of an application.

The history of…

A clear talk about the four fundamental spaces of it

We have learned a lot about Vectors and Matrices in our school days, they taught us every possible operation on Matrices, Vector scaling, and a lot of other stuff too. But, one thing that left out was visualizing their geometrical representation to understand what they are capable of, or the real picture of them. Does anyone know Gravity or the Human body can be represented as matrices back then? Probably, shouldn’t blame our system though!

When I jumped onto Deep Learning, I’ve been said that Linear algebra is everything. Then I thought, Oh great! I’ve been good at that in…

Top 9 tricks on Geo-spatial features and visualization technique

We come across many features while working on data sets for real. Geo-spatial features are the ones that I encountered recently while working with some data sets from Kaggle. As an amateur, This was my first-time using Geo-Spatial data. I wondered what to do with these data as there were no inter-related meaning within these points. what I see is just two numbers with a lot of noise around and even couldn’t find any ordinal property within it like with the age, year, experience and so on.

I asked, “If not useful, Why can’t we simply drop it?

Nah! It…

Bala Manikandan

Practicing Machine-learning in graduate level at Amrita University.

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