Pinned Repositories
-E-mail-Analysis
Analysis of emails of college email.
algorithms_and_data_structures
180+ Algorithm & Data Structure Problems using C++
budget-app
A Finances application made to manage all your day to day expenses
CGProject
Coding-Interview-Problems
This repository contains the coding interview problems along with solutions.
Competitive_Coding
This repository contains some useful codes, techniques, algorithms and problem solutions helpful in Competitive Coding.
cpp
Implementation of All ▲lgorithms in C++ Programming Language
Currency_Converter
It is a python program that uses the forex-python library to convert currency. A tkinter GUI is also made for better experience
DiceGame
Mini Project
Plant-Disease-Detection-Web-application
Deep learning with convolutional neural networks (CNNs) has achieved great success in the classification of various plant diseases. However, a limited number of studies have elucidated the process of inference, leaving it as an untouchable black box. Revealing the CNN to extract the learned feature as an interpretable form not only ensures its reliability but also enables the validation of the model authenticity and the training dataset by human intervention. In this study, a variety of neuron-wise and layer-wise visualization methods were applied using a CNN, trained with a publicly available plant disease image dataset. We showed that neural networks can capture the colors and textures of lesions specific to respective diseases upon diagnosis, which resembles human decision-making. While several visualization methods were used as they are, others had to be optimized to target a specific layer that fully captures the features to generate consequential outputs. Moreover, by interpreting the generated attention maps, we identified several layers that were not contributing to inference and removed such layers inside the network, decreasing the number of parameters by 75% without affecting the classification accuracy. The results provide an impetus for the CNN black box users in the field of plant science to better understand the diagnosis process and lead to further efficient use of deep learning for plant disease diagnosis.
yasharth328's Repositories
yasharth328/-E-mail-Analysis
Analysis of emails of college email.
yasharth328/algorithms_and_data_structures
180+ Algorithm & Data Structure Problems using C++
yasharth328/budget-app
A Finances application made to manage all your day to day expenses
yasharth328/CGProject
yasharth328/Coding-Interview-Problems
This repository contains the coding interview problems along with solutions.
yasharth328/Competitive_Coding
This repository contains some useful codes, techniques, algorithms and problem solutions helpful in Competitive Coding.
yasharth328/cpp
Implementation of All ▲lgorithms in C++ Programming Language
yasharth328/Currency_Converter
It is a python program that uses the forex-python library to convert currency. A tkinter GUI is also made for better experience
yasharth328/DiceGame
Mini Project
yasharth328/Plant-Disease-Detection-Web-application
Deep learning with convolutional neural networks (CNNs) has achieved great success in the classification of various plant diseases. However, a limited number of studies have elucidated the process of inference, leaving it as an untouchable black box. Revealing the CNN to extract the learned feature as an interpretable form not only ensures its reliability but also enables the validation of the model authenticity and the training dataset by human intervention. In this study, a variety of neuron-wise and layer-wise visualization methods were applied using a CNN, trained with a publicly available plant disease image dataset. We showed that neural networks can capture the colors and textures of lesions specific to respective diseases upon diagnosis, which resembles human decision-making. While several visualization methods were used as they are, others had to be optimized to target a specific layer that fully captures the features to generate consequential outputs. Moreover, by interpreting the generated attention maps, we identified several layers that were not contributing to inference and removed such layers inside the network, decreasing the number of parameters by 75% without affecting the classification accuracy. The results provide an impetus for the CNN black box users in the field of plant science to better understand the diagnosis process and lead to further efficient use of deep learning for plant disease diagnosis.
yasharth328/Drum-Kit
Mini Project which includes some work with audio and Vanilla JS.
yasharth328/Email-analysis
yasharth328/Feature-Engineering-and-Classification-of-Audio-Data
yasharth328/Finding-cabs-using-great-circle-distance-formula
It is a CPP project which based upon finding nearest cab using great circle distance formula.
yasharth328/Hacktober2021
Contribute in Open Source Projects 2021
yasharth328/HacktoberFest
yasharth328/Hacktoberfest-2021
A platform for developers 👩💻 who wants to participate in Hacktoberfest 2021 👕
yasharth328/Hacktoberfest-2022
This is A Hacktoberfest 2021 Python Repository
yasharth328/HacktoberFest-21
A mentorship initiative to help beginners kickstarting their open-source journey by completing Hacktoberfest'21 challenge | Curated list of beginner-friendly issues for Hacktoberfest 2021 | Raise PR to add your issues
yasharth328/Hacktoberfest2020
Make your first Pull Request and earn a free tee from GitHub!
yasharth328/idiomatic.js
Principles of Writing Consistent, Idiomatic JavaScript
yasharth328/Mini_Python_Projects
This repository will help beginners kickstarting their open-source journey by completing Hacktoberfest'21 challenge || Just need to make a mini python project that can be done within an hour also || Can also add programming questions and their solutions only in Python || Make sure you add everything in the right directory || HAPPY HACKING!!!
yasharth328/multimedia
yasharth328/Object-Detection
Object Detection model using YOLOv3 and openCV.
yasharth328/Python_Scripts
It contains all the Python Programs, whether it's a GUI, basic, Data Structures, etc. It's a collection of some great Python scripts from basic to advance levels for automating some monotonous tasks.
yasharth328/Sorting-Algorithm
A handful list of Sorting Algorithms
yasharth328/stalin-sort
Add a stalin sort algorithm in any language you like ❣️ if you like give us a ⭐️
yasharth328/TNP-portal
yasharth328/yasharth328
Config files for my GitHub profile.
yasharth328/yasharth328.github.io
Personal website