krishnasrikard
Graduate Research Assistant at The University of Texas at Austin | EE @ IITH 2022
The University of Texas at AustinAustin
Pinned Repositories
AutoML-Models-for-Wireless-Signals-Classification-and-effectiveness-against-Adversarial-Attacks
Comparing and understanding the performance of AutoML models with state-of-the-art models on wireless signal classification and their vulnerability towards transfer-based Projected Gradient Descent and Carlini-Wagner adversarial attacks.
Autonomous-Driving
C-and-Cpp-Programming-Practice
Practicing Competitive Coding with C++
Convolutional-and-Turbo-Codes
Implementation of Convolutional and Turbo Codes
Effects-of-reduced-frame-corruptions-on-video-classification
IIT-Hyderabad-Semester-Courses
Codes of my Regular Semester Courses
Optical-Flow-Less-Video-Frame-Interpolation
A modified light weight VRT is used to predict intermediate frames by looking only the previous frames or following causality without any use optical flow estimation techniques.
Saliency-Maps-NR-IQA-Classification-Models
Understanding the similarities in perception of image between humans and computer vision classification models using saliency maps between NR IQA models and classification models.
SR-DDPM
Denoising diffusion probabilistic model for low level vision task. Developing a novel DM for super resolution task; later to be extended for general vision tasks such as deblurring, dehazing, rain drop removal, inpainting, etc.
White-Box-Cartoonization
Experiments with two different models mainly VGG19 and VIT-16 which are used for calculating Structure and Content Losses in White Box Cartoonization and understanding the performance of the cartoonization process when trained only on a single dataset.
krishnasrikard's Repositories
krishnasrikard/AutoML-Models-for-Wireless-Signals-Classification-and-effectiveness-against-Adversarial-Attacks
Comparing and understanding the performance of AutoML models with state-of-the-art models on wireless signal classification and their vulnerability towards transfer-based Projected Gradient Descent and Carlini-Wagner adversarial attacks.
krishnasrikard/IIT-Hyderabad-Semester-Courses
Codes of my Regular Semester Courses
krishnasrikard/White-Box-Cartoonization
Experiments with two different models mainly VGG19 and VIT-16 which are used for calculating Structure and Content Losses in White Box Cartoonization and understanding the performance of the cartoonization process when trained only on a single dataset.
krishnasrikard/Autonomous-Driving
krishnasrikard/C-and-Cpp-Programming-Practice
Practicing Competitive Coding with C++
krishnasrikard/Convolutional-and-Turbo-Codes
Implementation of Convolutional and Turbo Codes
krishnasrikard/Coursera
Courses offered by various Universities in Coursera
krishnasrikard/Data-Analysis
Data Analytics
krishnasrikard/Effects-of-reduced-frame-corruptions-on-video-classification
krishnasrikard/Image-Processing
Image Processing using MatLab and TensorFlow
krishnasrikard/Natural-Language-Processing
Natural Language Processing
krishnasrikard/Optical-Flow-Less-Video-Frame-Interpolation
A modified light weight VRT is used to predict intermediate frames by looking only the previous frames or following causality without any use optical flow estimation techniques.
krishnasrikard/Saliency-Maps-NR-IQA-Classification-Models
Understanding the similarities in perception of image between humans and computer vision classification models using saliency maps between NR IQA models and classification models.
krishnasrikard/SR-DDPM
Denoising diffusion probabilistic model for low level vision task. Developing a novel DM for super resolution task; later to be extended for general vision tasks such as deblurring, dehazing, rain drop removal, inpainting, etc.
krishnasrikard/Deep-Learning
Deep Learning and Neural Networks
krishnasrikard/edx
Courses on edx
krishnasrikard/Elan-n-Vision-Machine-Learning-Contests
Machine Learning Contests held for Elan n Vision
krishnasrikard/Elektronica
Projects done under and for Elektronica Electronics Club of IIT Hyderabad
krishnasrikard/Generative-Adversarial-Networks
Building and Training Generative Adversarial Networks(GAN)
krishnasrikard/Hypothesis-Testing-vs-Binary-Classification
krishnasrikard/Internships
krishnasrikard/Introduction-to-Deep-Learning
MIT.S191 Introduction to Deep Learning
krishnasrikard/Java-Programming-Practice
Practicing Java
krishnasrikard/JavaScript-CSS-and-HTML-Programming-Practice
krishnasrikard/Machine-Learning
Machine Learning
krishnasrikard/Python-Programming-Practice
Practicing Python
krishnasrikard/Reinforcement-Learning
Learning Reinforcement Learning
krishnasrikard/Speech-and-Audio-Processing
Speech and Audio Signal Processing using Deep Learning