Sivaramakrishnan Rajaraman's repositories
Ensemble-of-CNN-and-ViT-for-TB-detection-in-lateral-CXR
An ensemble of convolutional neural network and vision transformer models to improve TB detection in lateral chest radiographs
multiloss_ensemble_models
The code proposes various novel loss functions to train the DL models and construct their ensembles to improve performance in a class-imbalanced multiclass classification task using chest radiographs
Bone-Suppresion-Ensemble
This study proposes a bone suppression model ensemble using novel and state-of-the-art deep learning architectures
Amazing-Semantic-Segmentation
Amazing Semantic Segmentation on Tensorflow && Keras (include FCN, UNet, SegNet, PSPNet, PAN, RefineNet, DeepLabV3, DeepLabV3+, DenseASPP, BiSegNet)
CXR-modality-specific-object-detection-ensemble-for-Pneumonia-detection
Training and constructing ensembles of RetinaNet-based object detection models initialized with random, ImageNet and CXR modality-specific pretrained weights
Unet-ensemble-for-TB-lesion-segmentation
An ensemble of U-Net models to segment TB consistent lesions in frontal chest radiographs
2020-CBMS-DoubleU-Net
DoubleU-Net for Semantic Image Segmentation in TensorFlow Keras (Nominated for Best Paper Award (IEEE CBMS))
adversarial-robustness-toolbox
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
AIF360
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
Awesome-explainable-AI
A collection of research materials on explainable AI/ML
beta_shapley
Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)
CEAL-Medical-Image-Segmentation
Active Deep Learning for Medical Imaging Segmentation
CheXzero
This repository contains code to train a self-supervised learning model on chest X-ray images that lack explicit annotations and evaluate this model's performance on pathology-classification tasks.
Deep-Learning-for-Causal-Inference
Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflow 2.
google-research
Google Research
image-similarity-measures
:chart_with_upwards_trend: Implementation of eight evaluation metrics to access the similarity between two images. The eight metrics are as follows: RMSE, PSNR, SSIM, ISSM, FSIM, SRE, SAM, and UIQ.
imutils
A series of convenience functions to make basic image processing operations such as translation, rotation, resizing, skeletonization, and displaying Matplotlib images easier with OpenCV and Python.
Keras-FewShotLearning
Some State-of-the-Art few shot learning algorithms in tensorflow 2
modAL
A modular active learning framework for Python
models
Models and examples built with TensorFlow
pyfeats
Open source software for image feature extraction.
pytorch-deep-learning
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
ResNeSt-Tensorflow2
ResNeSt: Split-Attention Networks for Tensorflow2
shap
A game theoretic approach to explain the output of any machine learning model.
tf-explain
Interpretability Methods for tf.keras models with Tensorflow 2.x
transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.