Pinned Repositories
Attention-Mechanism-Basics
Automatic-Image-Captioning
In this project, I have created a neural network architecture to automatically generate captions from images. After using the Microsoft Common Objects in COntext (MS COCO) dataset to train my network, I have tested my network on novel images!
Dog-Breed-Classifier
This project classifies breeds of dogs using CNN.
Facial-Keypoint-Detection
This project combines the knowledge of computer vision techniques and deep learning architectures to build a facial keypoint detection system that takes in any image with faces, and predicts the location of 68 distinguishing keypoints on each face!
Flower_Classification_Tensorflow.js
For this project, I'll be using the 'Flower Classification' dataset which I downloaded from Kaggle. This project has been made using Tensorflow.js.
Kalman-Filters
Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe. The filter is named after Rudolf E. Kálmán, one of the primary developers of its theory.
Landmark-Detection-Tracking-SLAM-
SLAM gives you a way to track the location of a robot in the world in real-time and identify the locations of landmarks such as buildings, trees, rocks, and other world features. This is an active area of research in the fields of robotics and autonomous systems.
MNIST_GAN
In this notebook, we'll be building a generative adversarial network (GAN) trained on the MNIST dataset. From this, we'll be able to generate new handwritten digits! GANs were first reported on in 2014 from Ian Goodfellow and others in Yoshua Bengio's lab. Since then, GANs have exploded in popularity. Here are a few examples to check out: Pix2Pix CycleGAN & Pix2Pix in PyTorch, Jun-Yan Zhu A list of generative models The idea behind GANs is that you have two networks, a generator 𝐺 and a discriminator 𝐷 , competing against each other. The generator makes "fake" data to pass to the discriminator. The discriminator also sees real training data and predicts if the data it's received is real or fake. The generator is trained to fool the discriminator, it wants to output data that looks as close as possible to real, training data. The discriminator is a classifier that is trained to figure out which data is real and which is fake. What ends up happening is that the generator learns to make data that is indistinguishable from real data to the discriminator. The general structure of a GAN is shown in the diagram above, using MNIST images as data. The latent sample is a random vector that the generator uses to construct its fake images. This is often called a latent vector and that vector space is called latent space. As the generator trains, it figures out how to map latent vectors to recognizable images that can fool the discriminator. If you're interested in generating only new images, you can throw out the discriminator after training. In this notebook, I'll show you how to define and train these adversarial networks in PyTorch and generate new images!
ORB
Oriented FAST and Rotated BRIEF (ORB)
YOLO-Object-Detection
YOLO is a state-of-the-art, real-time object detection algorithm. In this notebook, we will apply the YOLO algorithm to detect objects in images.
Garima13a's Repositories
Garima13a/YOLO-Object-Detection
YOLO is a state-of-the-art, real-time object detection algorithm. In this notebook, we will apply the YOLO algorithm to detect objects in images.
Garima13a/Kalman-Filters
Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe. The filter is named after Rudolf E. Kálmán, one of the primary developers of its theory.
Garima13a/Automatic-Image-Captioning
In this project, I have created a neural network architecture to automatically generate captions from images. After using the Microsoft Common Objects in COntext (MS COCO) dataset to train my network, I have tested my network on novel images!
Garima13a/Landmark-Detection-Tracking-SLAM-
SLAM gives you a way to track the location of a robot in the world in real-time and identify the locations of landmarks such as buildings, trees, rocks, and other world features. This is an active area of research in the fields of robotics and autonomous systems.
Garima13a/Facial-Keypoint-Detection
This project combines the knowledge of computer vision techniques and deep learning architectures to build a facial keypoint detection system that takes in any image with faces, and predicts the location of 68 distinguishing keypoints on each face!
Garima13a/Flower_Classification_Tensorflow.js
For this project, I'll be using the 'Flower Classification' dataset which I downloaded from Kaggle. This project has been made using Tensorflow.js.
Garima13a/Grad-CAM-with-fastai
Use Grad-cam with fastai
Garima13a/Denoising-Autoencoder
Denoising auto-encoder forces the hidden layer to extract more robust features and restrict it from merely learning the identity. Autoencoder reconstructs the input from a corrupted version of it."
Garima13a/Dog-Breed-Classifier
This project classifies breeds of dogs using CNN.
Garima13a/Beer_Label_Classification
Create a beer label classifier using SIFT, SURF, ORB.
Garima13a/Foveal-Hyperplasia-classification
this proof-of-concept study reveals the first use of AI in distinguishing between normal and pathological retinal development, with an application in paediatric ophthalmology to detect the presence and severity of foveal hypoplasia from OCT images.
Garima13a/Gaze-tracker
Garima13a/Leetcode_solutions
Garima13a/Retinal-OCT-Scan-segmentation
We have aimed to create a retinal OCT scan segmentation system that predicts all ten layer segments present on retina.
Garima13a/build-your-own-x
🤓 Build your own (insert technology here)
Garima13a/coding-interview-university
A complete computer science study plan to become a software engineer.
Garima13a/CRAFT-pytorch
Official implementation of Character Region Awareness for Text Detection (CRAFT)
Garima13a/Garima13a
Garima13a/Garima13a.github.io
Garima13a/handwritten-text-recognition
Handwritten Text Recognition (HTR) using TensorFlow 2.x
Garima13a/handwritten-text-recognition-for-apache-mxnet
This repository lets you train neural networks models for performing end-to-end full-page handwriting recognition using the Apache MXNet deep learning frameworks on the IAM Dataset.
Garima13a/live-resume
:anchor: Stand out of the crowd by showing a professional website/resume. :necktie: :briefcase: Build fast :rocket: and easy the best Personal Web Application resume!
Garima13a/mokkapps
My GitHub profile README which is automatically updated. Please ⭐️ if you like it
Garima13a/mscoutermarsh
SECRETS!
Garima13a/printed-hw-segmentation
Printed and handwritten text segmentation using fully convolutional networks and CRF post-processing
Garima13a/Projects-from-Scratch
Read and do projects.
Garima13a/Shandilya21
Garima13a/Tom-and-Jerry-Emotion-Detection-Challenge
Garima13a/Ujwal2910
Garima13a/Useful_code