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Name: Aditya Rana
Type: User
Twitter: adityassrana
Blog: adityassrana.github.io
Name: Aditya Rana
Type: User
Twitter: adityassrana
Blog: adityassrana.github.io
Archived Notebooks from Neural Networks course at BITS Pilani. Course website at https://bitsnnfl.github.io/
https://adityassrana.github.io/blog
PyTorch implementation of Learning Convolutional Networks for Content-Weighted Image Compression
Experiments with things I learned while doing the fast.ai course.
Content Based Image Retrieval. Implementations of color histograms, spatial pyramids, HOG, DCT, LBP, top hat and low hat filters, background and text removal, image denoising, and keypoints descriptors SIFT, SURF, ORB.
Optimization in Computer Vision. Implementations of Image Inpainting, Poisson Editing, Chan-Vese Segmentation and Markov Random Fields for Image Segmentation.
Image classification - Bag of Visual Words, Keypoints and Descriptors, Spatial Pyramids, K-Means and GMM clustering, PCA, LDA, SVM, Fisher Vectors, Fine Tuning CNNs, Training CNNs from scratch.
Implemented image warping, affine and metric rectification, DLT, RANSAC, panorama stitching Zhangโs calibration method, view morphing, stereo matching, depth-map computation, bundle adjustment and resectioning for Structure from Motion
Detectron2 implementations of object detection and instance segmentation on KITTI, KITTI-MOTS and MOTS Challenge datasets. Extensively experimented with different Faster-RCNN, RetinaNet and Mask-RCNN architectures available in the Model Zoo.
Weekly progress made on the task of Multi-Target Multi-Camera Tracking by implementing background modelling, object detection, IoU and Kalman tracking, block matching optical flow, video stabilization, metric learning using Siamese networks and tracklet matching algorithms.
Efficient architectures for image compression
RGBD-Scene Classification. Inroductory problem to get started with multimodal deep learning
Toy problem to get started with object detection and bounding box regression using MNIST
A script to quickly evaluate image classification performance on different architectures, optimizers and datasetss
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.