Pinned Repositories
code-cse.github.io
personal-portfolio-and-blog
command-installation
Command for different package installation in GPU/CPU
Deep-Learning-in-Production
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
Deep-learning-Models
This repository contains the code for various deep learning models and different architecture.
DL-using-Numpy
This repository contains different implementation of deep learning model using Numpy.
Face-Detection-SSD
This repository contains the code for Face detection using SSD.
Mind-Blowing-DSA-Problem
Mind-Blwoing-DSA-Problem is the combination of different Competitive-Programming challenging problem asked by different Compaines and various Coding-Competition.
object-tracking
This repo contains code for object tracking based on centroid value.
SODWTSMFW
Pointer-Generator Network, NLP, Summarization-of-documents-with-title-of-doc-summary-of-doc-and-most-frequent-word
Splice-DNA-Gene
Splice-Gene-Prediction, Healthcare, Medical-science, DNA
code-cse's Repositories
code-cse/academicpages.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
code-cse/AI-Deep-Learning-Lab-2021
Data, notebooks, and articles associated with the RSNA AI Deep Learning Lab at RSNA 2021
code-cse/awesome-radiology-report-generation
A curated list of radiology report generation (medical report generation) and related areas. :-)
code-cse/Brats21_KAIST_MRI_Lab
Codes and pretrained weights for winning submission of 2021 Brain Tumor Segmentation (BraTS) Challenge
code-cse/CheXbert
Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT
code-cse/Chexpert
Top 1 solution of Chexpert
code-cse/chexpertplusplus
Source implementation and pointer to pre-trained models for Chexpert++, a BERT-based approximation to CheXpert for radiology report labeling.
code-cse/clinicalBERT
repository for Publicly Available Clinical BERT Embeddings
code-cse/Data-Preparation
There are lot of things that need to be done on the given dataset before we feed it to the machine, these things come under data preprocessing. In this repository I have tried to explain those things with some examples.
code-cse/deepmind-research
This repository contains implementations and illustrative code to accompany DeepMind publications
code-cse/DPGN
This repository contains the official implementation of DPGN: Distribution Propagation Graph Network for Few-shot Learning.
code-cse/fairseq-image-captioning
Transformer-based image captioning extension for pytorch/fairseq
code-cse/GPT2-Chest-X-Ray-Report-Generation
This is the implementation of the CDGPT2 model mentioned in our paper 'Automated Radiology Report Generation using Conditioned Transformers'
code-cse/graph-based-deep-learning-literature
links to conference publications in graph-based deep learning
code-cse/ifcc
The code of Improving Factual Completeness and Consistency of Image-to-text Radiology Report Generation
code-cse/image-gpt
code-cse/kubeflow
Machine Learning Toolkit for Kubernetes
code-cse/Leetcode
🎓Leetcode solutions in Python 📚
code-cse/leetcode-patterns
A curated list of leetcode questions grouped by their common patterns
code-cse/Leetcode-Premium
code-cse/LeetCode-Solutions
🏋️ (Weekly Update) Python / Modern C++ Solutions of All 1955 LeetCode Problems
code-cse/machine-learning-systems-design
A booklet on machine learning systems design with exercises
code-cse/MONAI
AI Toolkit for Healthcare Imaging
code-cse/PaddleDetection
Object detection and instance segmentation toolkit based on PaddlePaddle.
code-cse/R2Gen
code-cse/SegLoss
A collection of loss functions for medical image segmentation
code-cse/torchsample
High-Level Training, Data Augmentation, and Utilities for Pytorch
code-cse/varadbhogayata.github.io
My Portfolio - Personal Website
code-cse/vertex-ai-samples
Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud
code-cse/X-Ray-Report-Generation
This is the implementation of the 'VSGRU' model mentioned in our paper 'Automated Radiology Report Generation using Conditioned Transformers'.