MV Robotics's repositories
torchkeras
Pytorch❤️ Keras 😋😋
deepdance
An app to improve your Tik-Tok dances and burn some calories during quarantine
Fast-Planner
A Robust and Efficient Trajectory Planner for Quadrotors
peeqo
Peeqo - the robot that responds entirely through videos and GIFs
RL-Quadcopter-2
A Deep Learning project which designs an agent that can fly a quad-copter, and then train it using a reinforcement learning algorithm DDPG
Raspberry-Pi-Surveillance-System-with-Cloud-based-Object-Detection
Implemented a cloud-based real-time face-swapping tool to swap faces in a video. Used CNN auto-encoder based deepfake algorithm and Google Cloud Platform (GCP) based services - Google App Engine (GAE), Google AI Platform for efficient deployment on cloud.
simple-cryptography
Scripts that illustrate basic cryptography concepts based on Coursera Standford Cryptography I course and more.
OpenCat
A programmable and highly maneuverable robotic cat for STEM education and AI-enhanced services.
lcdchargen
Custom Character Generator for HD44780 LCD Modules
Planetary-Orbit
Simulation of our solar system
face-mask-detector
Simple Model that detects the face mask
HousePricePredictor
House Prediction Model
YOLO_Object_Detection
YOLO Object Detection
stanford-tensorflow-tutorials
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
Autonomous-Forest-Surveillance-Safety-System-using-OpenCV
The current forest surveillance systems methods consume a lot of resources and are less efficient, not reliable and require a constant human presence whose tasks can be easily automated using new technology. To solve these problems we propose an autonomous surveillance system which uses object detection to identify specified animals. It is capable of monitoring forest fires, intruders, wildlife etc, all at once and alerts the concerned officials immediately and precisely. It has a hybrid object detection system using HAAR and Backpropagation neural network algorithms which can be used to train and detect animals and predict from the data obtained respectively. This helps in detecting various unwanted visitors, dangerous animals, or restricted tools into the forest. The system can not only store the video feed but can also determine population , track a specific animal or human and sends the pictures to your email directly along with real-time video monitoring via the internet which allows the users to monitor from anywhere in the world and sends instant alerts to your phone via an SMS even in remote areas in case of emergencies, and it stores all the data in a repository. We can control the system using a windows app which allows us to select which animals to be detected by the camera modules and their alert levels along with other settings and also provides a detailed analysis on various things like forest fires, animal population, trespassed areas etc, to users in simple charts. It is a smart, automatic, modular system which is cheap and easily expandable.
Detecting-COVID-19-using-Xray
Detect Disease using Deep Learning and Transfer Learning(ResNet50)
Cardio-Disease-Prediction-Using-ANN
Cardio Disease Prediction using ANN
Bankrupt-Classification
bankrupt-classification-using-oversampling
RacingRobot
Autonomous Racing Robot With an Arduino, a Raspberry Pi and a Pi Camera
CarND-Behavioral-Cloning-P3
Starting files for the Udacity CarND Behavioral Cloning Project
Micro_RC_Receiver
An Atmega328P based 2.4GHz receiver with integrated TB6612FNG motor driver
Placement-Analysis
detect the factors affecting the placement of the college by the given factors
Social-Distancing-Analyser-COVID-19
A social distancing analyzer AI tool to regulate social distancing protocol using video surveillance of CCTV cameras and drones. Social Distancing Analyser to prevent COVID19
fake_news_classifier
Fake News Classifier
social_distance_tool_of__face_date__using_openCV
Social Distance Tool using Face Data
heart_disease_detector
Heart Disease Detector
DNA_Classifier
DNA_Classifier
Face_Detector_using_openCV
Face Detector tool using openCV