Niranjan1005

Niranjan1005's Stars

• ItzCrazyKns/Perplexica

  Perplexica is an AI-powered search engine. It is an Open source alternative to Perplexity AI

  Language:TypeScript11.5k1k

• foolwood/DaSiamRPN

  [ECCV2018] Distractor-aware Siamese Networks for Visual Object Tracking

  Language:Python1.3k364

• HamadYA/GhostFaceNets

  This repository contains the official implementation of GhostFaceNets, State-Of-The-Art lightweight face recognition models.

  Language:Python17032

• Niranjan1005/FaceRecognition

  Language:Python1

• Niranjan1005/GeminiAI

  This project is a simple chat application utilizing the Gemini API.

  Language:Python2

• imranpollob/ehmr

  Electronic Health and Medical Record System

  Language:HTML61

• haochunchang/Diabetic-Retinopathy-website

  A django-based website for displaying Diabetic Retinopathy Auto-Detection.

  Language:HTML98

• akshitadixit/Retinopathy

  This is a Categorical Detection and Prediction Task based on subset of a Kaggle dataset from Eye Images (Aravind Eye hospital) - APTOS 2019 Challenge. The goal is to predict the Blindness Stage (0-4) class from the Eye retina Image using Deep Learning Models (transfer learning via resnet50). This Automated System would speed up Blindness detection on Patients. Work in progress.

  Language:Jupyter Notebook8

• AutomationPanda/tau-pytest-bdd

  Test Automation University: Behavior-Driven Python with pytest-bdd

  Language:Python109128

• mehra-deepak/Plant-Disease-Detection

  Plant Disease Detection is one of the mind-boggling issues when we talk about using Technology in Agriculture. Although researches have been done to detect whether a plant is healthy or diseased using Deep Learning and with the help of Neural Network, new techniques are still being discovered. For Fewer Data Classical Machine Learning Models are said to outstand given the data is pre-processed well. On the same theory here is my approach for Detecting whether a plant leaf is healthy or unhealthy by utilizing the classical Machine Learning Models, Pre-processing the Image Data. The data was fed to 7 Machine Learning Models with 10 fold cross-validation out of which Random Forest Classifier outperformed all the other models giving an accuracy of 97% on the test set.

  Language:Jupyter Notebook16479

• a-roomana/django-multi-captcha-admin

  easy add captcha to login page of django admin

  Language:Python4116

• nachi-hebbar/Login-Page-With-Flask-HTML

  A basic login page using html and flask

  Language:Python1913

• Faouzizi/Create_LoginPage

  This project will allow you to create a login page using Flask

  Language:Python3943

• manthan89-py/Plant-Disease-Detection

  Bases on Leaf images we are trying to predict plant disease using convolutional neural network. PyTorch implementation

  Language:Jupyter Notebook176151