Sadhasivam's repositories
Boar-Hunting-YOLOv8
YoloV8-based boar detection system with Arduino-triggered buzzer for enhanced security.
StereoVision
stereovision with esp32 cams for depth estimation , using Yolo , Opencv etc
Crop-Disease-Detection
Applying CNN (Convolutional Neural Network) for crop disease classification, aiding precision agriculture and yield protection.
Gesture-Recognition-Mediapipe
Gesture-controlled LED light using MediaPipe
MPU6050-Simulation
This project involves simulating the motion of a cube using an MPU6050 sensor.
Object-Tracking-YOLOv8
Raspberry Pi and YOLOv8: Real-time object tracking for efficient surveillance.
PipeLine-Inspection-Bot
A Bot to inspect and maintain pipelines
Ai-Car-Mediapipe
Use machine learning to control cars via hand gestures
ComputerVision-Explored
Exploring ComputerVision from scratch
Digits-Recognition-tensorflow
Simple Tensorflow model for recognizing digits, built over the MIST dataset
Emotion-Classification
Emotion Classification Model using Naïve bayes algorithm
LSTM-BTC-Prediction
LSTM (Long Short-Term Memory) BTC Prediction refers to the use of LSTM, a type of recurrent neural network, for forecasting the price movements of Bitcoin (BTC).
NLP-LEDio
Deep learning and NLP classify text for Arduino LED control.
NLP-Temperature-Chatbot
Coco: A minimalist NLP project leveraging NLTK for extracting temperature data.
RFID-SecurePass
Security system uses RFID & ML to control area access.
EPPROM-AT24C256
Using AT24C256 i2c EPPROM module with arduino , esp32 etc
Oled-imgShow-Arduino
Python application that converts an image to an array format suitable for displaying on an OLED display with an Arduino.
Package-Verification-YOLOv5
A YOLOv5-based packing verification model utilizes real-time object detection to ensure accurate and efficient product packing
SadhaSivamx.github.io
My Dummy Portfolio Website 🚀
Simple-Arduino
This repository consists of simple projects for getting started with Arduino.
Smart-Ai-Car
Raspberry Pi and YOLO-powered car for precise ball tracking and thrilling remote control fun
Weather-Classification-Model
Weather-Classification Model uses K-Nearest Neighbors (KNN) to classify local weather conditions (e.g., cold, moderate, hot) based on temperature, aiding residents in planning their day