Name: Yasinda Samaranayake
Type: User
Bio: Passionate about providing efficient solutions to real-world problems using computer science and artificial intelligence.
Location: Colombo, Sri Lanka
Yasinda Samaranayake's Projects
This is Piko! A discord bot that can talk to you, do trivia, inspire you, perform mathematical operations, react, see how "valid" you are and more!.
YOLOv8 + Deepsort (to monitor people exiting doors and walking in exit areas)
A simple script to detect faces using Haar feature-based cascade classifier
Labelling dataset with Snorkel and TextBlob, building model with Scikit-Learn (SVM), wiring up a web app using Flask.
Using the YOLOv5 algorithm to classify fresh/rotten fruits to analyze quality of products before shelfing.
Testing different free LLM's with GPT4All
This repo consists of a grocery.c file that handles basic shopping list activities using Linked Lists on C
Using YOLOv3 to detect Haechan from NCT 127.
Detect ongoing and incoming traffic in the highway using YOLOv9C and ByteTrack
These are three simple python scripts that use YOLOv3 for object detection based on the coco dataset.
ā” Building applications with LLMs through composability ā”
Software Maintenance Coursework - Eashan Yasinda Samaranayake
This matlab project segments leaves from a plant using varios pre-processing techniques followed by the watershed segmentation algorithm.
Chat with your PDF files and ask the most specific questions about them!
Created to teach high school students how to visualize data from a CSV.
This is a simple python script to detect circles in images. This was designed for the "Python for Beginners Workshop at University of Nottingham, Malaysia".
This is a simple python script for the game Hangman I created for the "Python for Beginners Workshop at University of Nottingham, Malaysia"
Welcome to the official repository for the "Study into the CNN Framework" research project. This repository serves as a central hub for all datasets, code notebooks, and results generated during the course of our investigation into Convolutional Neural Networks (CNNs).
This is a companion chatbot built using NLP. I fully developed the backend of the chatbot which consists of the CNN used to gauge the user's emotion score per each message, the ability of the bot to reply based on classified emotion, keep track of user independent scores, evaluate overall emotional status to provide with consolidation message and more!
Comparison of a fine-tuned CNN against SOTA architectures (+ transfer learning) on SVHN dataset