sambhav37/Keras-learning-rate-finder

Stars
1
Language
Python
Created about 5 years ago
Updated about 5 years ago

sambhav37/Keras-learning-rate-finder

sambhav37

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

An algorithm to find an optimal decay for Gradient Descent and Learning Rate for training of Neural Network models.

Mask-R-CNN

Explaining the differences between traditional image classification, object detection, semantic segmentation, and instance segmentation is best done visually. When performing traditional image classification our goal is to predict a set of labels to characterize the contents of an input image (top-left). Object detection builds on image classification, but this time allows us to localize each object in an image. The image is now characterized by: Bounding box (x, y)-coordinates for each object An associated class label for each bounding box.Instance segmentation algorithms, on the other hand, compute a pixel-wise mask for every object in the image, even if the objects are of the same class label (bottom-right). Here you can see that each of the cubes has their own unique color, implying that our instance segmentation algorithm not only localized each individual cube but predicted their boundaries as well.

sambhav37.github.io

Hashing-Image-Search-Engine

Searching duplicate and near duplicate images using a hashing algorithm and VP trees.

Scala-Stream

This helps you to understand working of Scala Stream