Highlights
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Stars
This is the code that was used for our comparative study on face anti spoofing techniques
Solutions to all questions of the book Introduction to the Theory of Computation, 3rd edition by Michael Sipser
ML Project to predict students' responses to diagnostic questions: From a perspective of recommender systems
This code can be used to perform gaussian elimination. It was coded in julia as julia is faster in dealing with matrices compared to python.
Single-Side Domain Generalization for Face Anti-Spoofing, CVPR2020
KL severity grading using SE-ResNet and SE-DenseNet architectures trained with Cross Entropy loss and Focal Loss. The hyperparameters of focal loss have been fine-tuned as well. Further, Grad-CAM h…
Knee osteoarthritis analysis with X-ray images using CNN with Squeeze-and-Excitation blocks
Programming assignments from the Deep Learning course offered at IITH in my 6th semester.
Web app to predict knee osteoarthritis grade using Deep Learning and Streamlit
UTRNet: High-Resolution Urdu Text Recognition In Printed Documents (ICDAR'23)
Prediction of Total Knee Replacement and Diagnosis of Osteoarthritis using Deep Learning on Knee Radiographs: Data from the Osteoarthritis Initiative
Knee Osteoarthritis Analysis with X-ray Images using CNN
Encryption and Decryption using AES-128
PyTorch implementation of STR models for transfer learning in Indic Languages
Pytorch implementation of RetinaNet object detection.
Image Steganography using K-Means clustering and DES encryption