Recognition of handwritten flowcharts using convolutional neural networks to generate C source code and reconstructed digital flowchart.
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Updated
Mar 24, 2024 - Python
Recognition of handwritten flowcharts using convolutional neural networks to generate C source code and reconstructed digital flowchart.
Python implementation of tracking surgical attachment for accurate monocular pose estimation with aruco markers.
ROS implementation of shopping bot manager on Pepper. This is for an university project.
Classification System Design using Redundant Robot and Artificial Vision (Diseño de Sistema de Clasificación usando Robot Redundante y Visión Artificial)
The API utilizes the power of the Intel Realsense depth camera. Thanks to infrared sensors, the camera is able to calculate the distance and return the three-dimensional coordinates (x, y, z) of a detected person.
Experiment on the theoretical aspects of color image detection and classification algorithms, and implementation of it for skin segmentation and finger counting. ✌🏼
This programm recognise different objects from a video. Used technologies: Yolov8 and Django
Procesamiento digital de imágenes (algoritmos, operaciones sobre las imágenes, obtención de características, proyectos end2end).
This repository contains the exercises from the course on computer vision, which includes topics such as image classification, object detection, introduction to perceptron, and classification algorithms like KNN and K-means.
This is an API written in Python using the Django framework. It performs face recognition and training of a person's face model.
This project outlines the development and implementation of an automatic cat feeder, leveraging an artificial vision system. The system operates in two modes: automatic and manual, aiming to enhance pet feeding using Raspberry Pi and Arduino.
Artificial vision algorithms.
Traffic lights tracking and color detection with OpenCV. Combination of a MOSSE tracker and inner freehand rectangles.
People detection with a neural network to detect people in urban environments using custom-extracted image features. The NN is trained on a dataset consisting of images categorized into scenes with people and without people but with animals. The dataset used was created by generative AI.
Project made for "Artificial Vision and Biometrics Fundamentals" course. We used facial landmarks to classify subjects emotions expressed through facial expressions
Artificial vision project
This repository was created for the thesis work related to the Artificial Vision subject at the University of Salerno.
Common soft computing techniques in python and Matlab
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