Merke tree visualization library for browser, works with merkletreejs

(Migrated from CodePlex) SQL Template Library Manager, SQL Generator.

Git Based Leaves management system

ISeeYou can use the Replay API provided by the Leaves core to record every move of the player in .mcpr format.

Manage time invested in various activities in your office. HRs and Managers can view and manage time for all employees and employees can view their overtime, leaves and holidays in an easy to use application

Wave:https://wave-effects.netlify.app/ Leaves: https://leaves-animation-css.netlify.app/ Product:https://product-display-css.netlify.app/ Emoji:https://emoji-animation.netlify.app/ Smoke:https://smoke-effect.netlify.app/

Plant science stomatal outreach game project

Identification of Species of Medicinal Leaves using a pre-trained CNN model

Crunch! Crunch! A game of satisfying autumn sounds

This project's sole motto is to make process of leaves easy for teachers.

Aplikasi Cuti Online

Count the number of leaves present in an image using OpenCV-python.

Supplimental information, data, and code for Newsome et al. 2020. "Variation within laminae: Semi-automated methods for quantifying leaf venation using phenoVein" in Applications in Plant Sciences 8(5) e11346.

This repository contains code and algorithms for working with binary trees, including creation, traversal, and various tree operations. It serves as a resource for learning and implementing binary tree data structures in C programming language which could be adapted to any language of choice.

Rasilmali a product developed and maintained by Kichwen Service Limited meaning (Resources). Rasilmali is a business process management software that allows an organization to use a system of integrated applications to manage the business and automate many back-office functions related to technology, services and human resources. customizable ERP

Streamline your ecoacoustic analysis with LEAVES, offering advanced tools for large-scale soundscape annotation and visualization. Join researchers and citizen scientists using LEAVES to analyze complex soundscapes faster and more accurately.