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Finds degree of similarity between two strings, based on Dice's Coefficient, which is mostly better than Levenshtein distance.
3D U-Net model for volumetric semantic segmentation written in pytorch
Use of state of the art Convolutional neural network architectures including 3D UNet, 3D VNet and 2D UNets for Brain Tumor Segmentation and using segmented image features for Survival Prediction of patients through deep neural networks.
A fuzzy matching string distance library for Scala and Java that includes Levenshtein distance, Jaro distance, Jaro-Winkler distance, Dice coefficient, N-Gram similarity, Cosine similarity, Jaccard similarity, Longest common subsequence, Hamming distance, and more..
Loss function Package Tensorflow Keras PyTOrch
string similarity based on Dice's coefficient in go
Pytorch Implementations of Common modules, blocks and losses for CNNs specifically for segmentation models
This Repo is for implementation of 3D unet in Tensorflow 2.0v
This was my research project at IIT Bombay on Lung Segmentation from Chest X-Rays Images
Image Segmentation using U-Net, U-Net with skip connections and M-Net architectures
An image segmentation project using PyTorch to segment the Left Atrium in 3D Late gadolinium enhanced - cardiac MR images of the human heart.
Report various statistics stemming from a confusion matrix in a tidy fashion. 🎯
ML/CNN Evaluation Metrics Package
Adversarial Attack on 3D U-Net model: Brain Tumour Segmentation.
Compare the sameness of two strings
Finds degree of similarity between two strings, based on Dice's Coefficient and Levenshtein Distance.
CNN for Synovitis Segmentation in MRI
This is a project that put in a sample resume then extract the skills, and then use those skills to find the best matches in the resume dataset.
A routine for assigning spam probability to a given set of text messages by comparing each text to the rest of the corpus, checking the frequency of spam and non-spam messages in the corpus. The probability is ranged from 0 to 1, where 0 is no spam and 1 is certain spam.
Semantic Segmentation with FCN Autoencoders
Imaging Coursework: Non-Deep-Learning Segmentation of Pap Smear Images
Finds degree of similarity between two strings, based on Dice's Coefficient, which is mostly better than Levenshtein distance.
The Dice Coefficient Is Scale Sensitive, Mathematical Proof.
Natural Language Processing (classification and machine translation) codes and analysis done for the year long practicum in Dublin City University (2019-20)
Data Structures: Arrays, Stacks, Queues, Graphs applications in image processing, tag parsing and routes/maps respectively.
A movie recommender written in Go that suggests movies considering various factors within a particular dataset, encompassing users, movies, and movie ratings.
Example of brain tumor segmentation.
Semantic segmentation solution for Airbus Challenge Task
Attention Residual UNet for vein image segmentation in the field of biometric identification
U-Net from Scratch for Brain Tumor Segmentation