codewithahad01
🌟 I believe in the power of collaboration and continuous learning. Let's connect, learn, and build together!
@NETLINKSAFLimassol, Cyprus
Pinned Repositories
30DaysOfCodeChallengeInHackerRank
I am Going to Solve the 30 Days of Code Challenge of HackerRank
codewithahad
Personal Web app
discover-coffee-stores
discover the location and information of coffee stores using Nextjs and Tailwindcss
Front_End_Mentor_Challenges
In this Repo I am going to solve the Front End Challenges of Frontend Mentor Platform
Hospital-MIS
This project covers all sections in a hospital for management its recourses .
House-Marketplace-App
Real state market place house with React and Firebase
Portfolio
my portfolio
time-tracking-dashboard
The dashboard Switch between viewing Daily, Weekly, and Monthly stats, developed by Nextjs and Tailwindcss
tip-calculator-app
calculate the amount of tip component with TailwindCSS and Nextjs
Web-Dev-For-Beginners
24 Lessons, 12 Weeks, Get Started as a Web Developer
codewithahad01's Repositories
codewithahad01/FAQ_Component
FAQ Components with Tailwindcss and daisyui
codewithahad01/order_summary_component
order summary component with tailwindcss and daisyui
codewithahad01/NFT_Prewiew_Card
NFT preview card with and tailwindcss
codewithahad01/huddle-two
codewithahad01/Front_End_Mentor_Challenges
In this Repo I am going to solve the Front End Challenges of Frontend Mentor Platform
codewithahad01/beautify-github-profile
This repository helps you to have a more beautiful and attractive github profile, and you can access a complete set of tools and guides for beautifying your github profile. 🪄 ⭐
codewithahad01/House-Marketplace-App
Real state market place house with React and Firebase
codewithahad01/tailwind-landing-page
landing page with tailwindcss
codewithahad01/getamover
codewithahad01/burger_builder
creating burger builder that uses components and state in React
codewithahad01/public-apis
A collective list of free APIs
codewithahad01/BBQ-UI-Design
Responsive UI Design of BBQ master
codewithahad01/snake_game
snake game using JavaScript
codewithahad01/javascript-exercises
codewithahad01/javascript-basic-projects
codewithahad01/grocery_list_in_js
grocery list in javascript used for crud client side auth
codewithahad01/page_template
this is the simple template of a page in a structure
codewithahad01/wesbos
codewithahad01/30DaysOfCodeChallengeInHackerRank
I am Going to Solve the 30 Days of Code Challenge of HackerRank
codewithahad01/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.
codewithahad01/Technical-Documentation-Page
Documetation page that shows the basic things of javaScript
codewithahad01/modern-js-cheatsheet
Cheatsheet for the JavaScript knowledge you will frequently encounter in modern projects.
codewithahad01/MUM-Entrance-Exam-Solution
codewithahad01/DeepLearning_PlantDiseases
Training and evaluating state-of-the-art deep learning CNN architectures for plant disease classification task.
codewithahad01/plantvillage_deeplearning_paper_dataset