Rohit Gandikota

sliders. Concept Sliders for Precise Control of Diffusion Models

erasing. Erasing Concepts from Diffusion Models

unified-concept-editing. Unified Concept Editing in Diffusion Models

sliderspace. SliderSpace: Decomposing the Visual Capabilities of Diffusion Models

distillation. Distilling Diversity and Control in Diffusion Models

erasing-llm. Erasing conceptual knowledge from language models through low-rank fine-tuning

hiding-audio-in-images. Generative Models to hide Audio inside Images using custom loss functions and Spectrogram Analysis

Stock-News-Scrapping-With-Python. API for scrapping news on stock market for sentiment analysis and stock prediction

Hiding-Images-using-VAE-Genarative-Adversarial-Networks. Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to hide data inside images

bert-qa. This project shows the usage of hugging face framework to answer questions using a deep learning model for NLP called BERT. This work can be adopted and used in many application in NLP like smart assistant or chat-bot or smart information center.

sar2optical. A Conditional Patch GAN for synthesis of optical images from SAR data as a 24X7, all weather disaster surveillance

gaze-heads. Gaze Heads: How VLMs Look at What They Describe

Land-Use-Land-Cover-Classification-of-Satellite-Images-using-Deep-Learning. This work discusses how high resolution satellite images are classified into various classes like cloud, vegetation, water and miscellaneous, using feed forward neural network. Open source python libraries like GDAL and keras were used in this work. This work is generic and can be used for satellite images of any resolution, but with MX band sensors.

automatic-image-quality. Automatic Image Quality Analysis (AIQA) has become a very crucial module in remote sensing industry. With increasing competition and institutions that provide remote sensing images, the quality of images provided to the users has a huge impact.

satellite-to-map. Generative Model to generate Map layers from Satellite Data

Real-Time-Cloud-Detection-of-Satellite-Images-during-Acquisition. This project deals with the real time cloud detection of the ongoing acquisition data of satellite images. For this end, we use a simple and light MLP for classification of the image pixels. This work can classify the satellite images of size ranges till 64000 pixels width.

progressive-diffusion. We explore the concept of progressive growth of network layers in denoising diffusion probabilistic models.

NLP-based-Smart-Search-for-Satellite-Data-Ordering. Text-based and Voice-based search for satellite data ordering will massively improve user usability in terms of time spent and ease. This work focuses on satellite specific lingo and uses databases to search for data.

sliderspaceweb. HTML

cdqn-detect. This project harnesses deep reinforcement learning to detect cars in aerial images

deprecated-code. This repository contains our initial experiments to study code deprecation in codeLLMs

Image-Rotation-Angle-Detection-with-Python. This code can be used for finding the angle that the image has been rotated by. Especially is tested on satellite data where geo-referencing rotates the image.

Hiding-Video-in-Images-using-Deep-Generative-Adversarial-Networks. This is a preliminary attempt on hiding video data inside images using deep learning. We design a custom adversarial network with custom losses and additional discriminator. We call this multi-discriminator and multi-objective training framework.