Annie Lee - OpenGenus IQ: Computing Expertise & Legacy

Summary: The Case for Learned Index Structures

This outlines and evaluates the potential of a new approach to build indexes that is the merge of Algorithms/ Data Structures and Machine Learning.

Machine Learning (ML)

Adversarial Examples are not Bugs but are Features of AI

Adversarial Vulnerability is a direct result of our models' sensitivity to well-generalizing features in the data. We explored the research paper.

Machine Learning (ML)

The Indirect Convolution Algorithm

Indirect Convolution is as efficient as the GEMM primitive without the overhead of im2col transformations - instead of reshuffling the data, an indirection buffer is introduced.

Machine Learning (ML)

Summary: Learning to See by Moving

Research question: Is it also possible to learn useful features for a diverse set of visual tasks using any other form of supervision?

Machine Learning (ML)

Wiener filter

Wiener filter performs two main functions - it inverts the blur of the image and removes extra noise. It is particularly helpful when processing images that have been through a degradation filter.

Machine Learning (ML)

Summary: High Performance Convolutional Neural Networks for Document Processing

We have explored the paper "High Performance Convolutional Neural Networks for Document Processing" by Microsoft Research. It explores techniques to compute convolution layer in CNN faster.

Machine Learning (ML)

Understanding Deep Image Representations by Inverting Them

We have explore the problem that given an encoding of an image, to which extent is it possible to reconstruct the image itself? We have explored the paper "Understanding Deep Image Representations by Inverting Them".

Machine Learning (ML)

Solving Jigsaw Puzzles using Machine Learning

The paper "Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles" describes a convolutional neural network (CNN) that aims to solve a pretext task, solving Jigsaw puzzles without manual labelling, and then to solve object classification and detection tasks.

Machine Learning (ML)

Gaussian blur (filter to blur images)

Gaussian blur is a type of image processing that applies a convolution filter on an image. This filter takes the surrounding pixels and returns a single number calculated with a weighted average based on the normal distribution.

Machine Learning (ML)

Sobel Filter/ Operator for Edge Detection

Sobel Filter/ Operator is a filter used in Convolution that is used to detect edges in an image. This is one of the fundamental approaches in Image Processing/ Machine Learning to detect edges.

Software Engineering

Boolean and None in Python

"if x" and "if x is not None" are not equivalent - the proof can be seen by setting x to an empty list or string. In this article, we have explored the two important concepts namely boolean and none in Python.