Avinash

Avinash

If you help someone, you help everyone!

Sitemap

A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

Exploring text summarization

less than 1 minute read

Published:

The problem we investigated was exploring and improving text summarization. Between generated and extracted summaries, our main focus was to improve the quality of generated (abstractive) summary. In particular we focused on building upon PEGASUS, a SOTA transformer model and investigate ways to improve the qualitative performance of abstractive summaries. Proposed and implemented Self-Attention Guided Copy Mechanism which guides the summarization model to copy the important source words from the source doc/article to the summary. You can find the project at this link

Discrete Wavelet Transform Image Super-Resolution Analysis and Deep Wavelet Prediction

less than 1 minute read

Published:

Super resolution techniques are useful in a range of industry applications from medical imaging and diagnosis to security and surveillance utilization. Since resolution enhancement of visual data from an imaging hardware point of view is costly, sensitive to environmental conditions, and time consuming, post-processing super resolution methods are a reasonable solution to improving the performance and analysis of imaging applications. In this paper, we analyze the performance of a modified Discrete Wavelet Transform (DWT) based super resolution algorithm on a variety of image acquisition types. A wavelet transform provides a detail as well as coarse separation of the contents of the image. We design a Convolutional Neural Network (CNN) to predict the missing details (residuals) in the wavelet coefficients of the low-resolution images to obtain high-resolution images. The network has multiple input and output channels which allows it to learn the different structures at different levels of the image. You can find more info here

Chest pathology classification in X-rays using GANs

less than 1 minute read

Published:

Medical datasets are often highly imbalanced with overrepresentation of common medical problems and a shortage of data from rare conditions. We propose simulation of pathology in images to overcome the above limitations. Using chest X-rays as a model medical image, we implement a generative adversarial network (GAN) to create artificial images based upon a modest sized labeled dataset. We employ a combination of real and artificial images to train a deep convolutional neural network (DCNN) to detect pathology across fiveclasses (Cardiomegaly, Pleural Effusion ,Pulmonary Edema, Pneumothorax and Normal) of chest X-rays.

Style transfer

less than 1 minute read

Published:

Humans have mastered the method of creating artistic images of different styles using methodology unique to them. Art and painting style is all about percep- tion and hence is considered a interplay of content and style of the scene to be described. Current world art has classified painting styles in different categories like Modernism, Figurative Art etc. Thus far the algorithmic basis of this process is unknown and there exists no artificial system with similar capabilities. However,advances in visual perception and recognition tasks using deep learning methods opens great opportunities for its extension to develop a system for style and contentlearning. This project attempts to understand the use of deep neural net architectures for learning and transfer of style and content of a given image. To know more vist link

Low cost Syringe pump

less than 1 minute read

Published:

Created a low cost syringe pump using a stepper motor and Arduino micro-controller. Fabricated the parts using a Mojo 3D printer. Enabled serial communication between Arduino and the computer using CoolTerm so that commands (for ex:- setting the flow rate) can be given by the user from terminal.This is a prototype of a syringe pump which can be used in applications where we require a fixed and precise fluid rate. A lot of credit goes to Prof. C. A. Varnon who has already created an open source syringe pump, from which we have adapted quite a few ideas. You can find the working demo of the prototype at this link

portfolio

publications

talks

teaching

Signal Processing for Data Analysis

Undergraduate course, UCSD, 2020

I was a teaching assistant for DSC 120 offered by Prof. Alex and Prof. Gal. I held discussion sessions and office hours; prepared and evaluated exams in the course. The course focuses on ideas from both classical and modern signal processing, with the main themes of sampling continuous data and building informative representations of data using orthonormal bases, frames, and data dependent operators. The main topics are sampling theory, Fourier analysis, lossy transformations and compression, time and spatial filters, and random Fourier features and their connections to kernel methods. The main sources of data that are used are time series and streaming signals, and various imaging modalities.

Introduction to Data science

Undergraduate course, UCSD, 2020

Concepts of data and its role in science are introduced, as well as the ideas behind data-mining, text-mining, machine learning, and graph theory, and how scientists and companies are leveraging those methods to uncover new insights into human cognition.

Engineering Probability and Statistics

Undergraduate course, UCSD, 2021

I was a tutor and reader for ECE 109 offered by Prof. Alex. Link to course website This course is an introduction to probability for engineers. You will have the opportunity to learn basic concepts that are used extensively in such areas as machine learning and data science, robotics and control, communication systems, and signal processing. In fact, probability plays a crucial role in many disciplines beyond engineering — computational genomics, quantum mechanics, and stock market analysis, to name a few.