Bag of Visual Words — Finding similar Images
ML concepts : k-means cluster and TF-IDF in Robotics
Finding similar images in a database has many applications in robotics, computer vision, and other fields. The basic idea is to find a similar image in the database for a given query image. A popular technique used for this is Bag of Visual Words (BoVW), where images are not stored as they are but as histograms of image f...
ORB SLAM 2 under the hood
from paper
Brief SLAM understanding
Structure of a typical SLAM System. Back-end infor-
mation can sometimes be fed back into the front-end to assist in data
SLAM, describes a solution to the problem of placing a robot at an unknown location and having it to build a map of its environment while localizing itself inside the map. The vehicle should be able to estimateits t...
Edge Accelerators- Solves Conflict Of Quantization Between A Dynamic Range And The Precision
Why we need quantization in edge computing?
a neuron
The edges and nodes are computational operations and there are some mappings with the hardware. But when every edge eventually has some transfer of data and that needs some storage even if temporary and very close to memories. Hence, if there is low bit, there will be less transfers amount of transfer of data and ...
Understanding Why Quantization Is Beneficial In Neural Network Specially For Llama 2 Or For Edge Computing.
Let’s start with floating point representation, it is a tradeoff between precision and long range. This requires large compute resources.
Moving from floating-point representation to quantization involves converting the continuous range of floating-point numbers to a discrete set of values represented by integers. This process is important for optimizing machine le...
