Pratinav Seth's repositories

UATTA-ENS

Official implementation of UATTA-ENS: Uncertainty Aware Test Time Augmented Ensemble for PIRC Diabetic Retinopathy Detection.

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Musculoskeletal-Radiographs-Abnormality-Detection

Musculoskeletal Radiographs Abnormality Detection using Stanford MURA dataset.

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Knee-Abnormality-and-Common-Disorders

Deep Learning Based Diagnosis, Abnormality and Common Disorders detection using Knee MRI Stanford MRNet Dataset

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RSM-NLP-BLP-Task2

Shared Task 2 at the EMNLP 2023 BLP Workshop - Sentiment Analysis of Bangla Social Media Posts

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Snapchat_Filters_OPENCV

Trying to recreate Snapchat filters using OpenCV, cvzone, mediapipe and python.

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Stock_Price_Prediction_Workshop

Repository contains all the slides and codes used during the hands-on sessions of IEMCT-ESOM Stock Price Prediction Workshop.

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Satellite_Segmentation-U-NET

Implemented U-Net for semantic segmentation of aerial imagery of Dubai obtained by MBRSC satellite into six classes.

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Shifts_evaluation_metrics_regression

This repository contains the code for reproducing the results of our evaluation metrics on regression tasks.

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SNAP_Recommendation_Engine

A Graph Based Recommendation Engine which recommends appropriate similar products, co-purchased products and high confidence products similar to one viewed by user using the Amazon SNAP Co-Purchasing Dataset.

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Contrail_Segmentation_CCAI_NeurIPS_22

The code for our paper Contrail segmentation using Deep Learning

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Multi_Class_Skin_Lesion_Classification

This Project aims to benchmark various commonly used models for the task of classifying dermoscopic images among nine different diagnostic categories using the ISIC 2019 Challenge dataset.

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test.github.io

(Minimalism Style) Powered by Jekyll, based on the Minimal Mistakes theme and Jason Ansel's website

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U-Mamba

U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

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Webcam_Paint_Digit_Recognition

Drawing Digits through a customizable pointer using opencv and python and using a pretrained CNN model on MNIST to detect digits 0-9.

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What-Should-I-Watch-Next

Designed a Movie Recommendation Engine using content and collaborative filtering based on user and item similarity while incorporating solutions to the cold start problem. Deployed it into an app using Streamlit and fast API.

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