sddaphal Goto Github PK

leaf_disease_detection-classification

Flask App Which detects 15 variety of plants [Pepper , Potato , Tomato ]

learning-r

Learning Process- R

maskdetection

This is the work done by mitaoe students

mobile-application-to-detect-tomato-leaf-diseases

Accounting to almost 6.0% of the total tomato production in the world. Tomato is the third most significant vegetable of India by sharing 8.5% of all out vegetable creation.This shows The importance of tomatoes in India. In this section we discuss a solution wherein farmers can take pictures of diseased tomato leaves , the image taken is sent to the flask server, the flask server has a pre-trained CNN model. The image is fed as input to the CNN model. The CNN model is already trained on diseased tomato leaf images consisting of the 9 different types of tomato leaf diseases,the model can also predict if the leaf is healthy.The Dataset used here is the plant village dataset. Each tomato leaf disease consists of around 700 images. The output of the model is the type of disease the plant is affected with or if the leaf is healthy.

montecarloworkshop

Course material for a tutorial on Monte Carlo for uncertainty evaluation with Python

multimodal-image-classifier

Image classifier for multimodal input (Image + non-Image features). Useful when we have additional data for images which may be useful for classification

neural_networks_for_computer_vision

Implementing Neural Networks for Computer Vision in autonomous vehicles and robotics for classification, pattern recognition, control. Using Python, numpy, tensorflow. From basics to complex project

object-localization

Object localization in images using simple CNNs and Keras

opencv-tutorials

Algorithms related to image processing using OpenCv libraries

pflu-fpflu

Codes of the paper "PFLU and FPFLU: Two novel non-monotonic activation functions in convolutional neural networks"

plant-diseases-classification-using-ml-web-app-flutter-app

My project plan was based on an image dataset of the leaves of a specific group of crops called "Plant Village". I used this dataset to build four custom trained models using machine learning (ML) techniques. Next, I deployed these custom ML models to make them available to the end-users. These models are accessible via a website and via a nice android mobile application using Flutter

plantsapp

Plants App is my graduation project built using android studio combined with deep learning code. It is an application to detect plants leaves disease using deep learning CNN model

project-2021

Image feature database creation of crop type identification

speaker-recognition

Speaker Recognition System using MFCC and GMM.

sugarcane

B.E Project

svm_for_classification

This implements SVM to solve binary classification problems

swapnil-resume

This repository contains the samples we used for creating resume

tactode_recognition

Code repository for Tactode tiles recognition using: (i) machine learning with HOG&SVM, (ii) deep learning with some neural networks like VGG16/19, ResNet152, MobileNetV2, YOLOv4 and SSD, (iii) matching of handcrafted features with SIFT, SURF, ORB and BRISK, and (iv) template matching.

tensorflow-tutorials

Simple tutorials using Google's TensorFlow Framework

tflite2onnx

Convert TensorFlow Lite models (*.tflite) to ONNX.

tipl

template image processing library

tomato-leaf-disease-detection

A simple CNN model to detect and classify ten different types of tomato leaf disease.

transfer_learning_comparision

Comparison of CNN Models by performing classification on Medical MNIST data-set via Transfer Learning.

uday_information

This repository is just for test purpose

unsupervised-classification-with-autoencoder

Using Autoencoders for classification as unsupervised machine learning algorithms with Deep Learning.

unsupervised_crack_segmentation

K-means clustering algorithm is trained over GLCM texture property features of the concrete images with crack to detect the crack location

useful_functions

vehicle_counting

Vehicle detection, tracking and counting by blob detection with OpenCV on c++.

wcnn

A novel dual-tree complex wavelet transform based Convolutional Neural Network (WCNN) to perform organ tissue segmentation from medical images.

wine-quality

Predicting wine quality