Below are the prerequisites for this project: Python (3.7.4 used) IDE (Jupyter used) Required frameworks are Numpy (version 1.16.5) cv2 (openCV) (version 3.4.2) Keras (version 2.3.1) Tensorflow (Keras uses TensorFlow in backend and for some image preprocessing) (version 2.0.0) Matplotlib (version 3.1.1) Pandas (version 0.25.1)

Object recognition by random binary data lookup proof of concept for QMNIST

Work area recognition for small robots. Computer Vision Research Internship. TUAT, Japan.

Created an ASR (Automatic Speech Recognition) system that takes in individual recordings. Each recording represents a sentence composed of 5-10 English language digits, separated by adequate pauses. The system involves segmenting the sentence using a classifier, differentiating between background and foreground sounds.

A Real Time Kurdish handwriting Language Number Recognition Model Using Deep Learning (AlexNet) over used website

Computer vision is a field of artificial intelligence (AI) that uses machine learning and neural networks to teach computers and systems to derive meaningful information from digital images, videos and other visual inputs—and to make recommendations or take actions when they see defects or issues.

The goal is to recognize fruit through machine learning algorithm implementations such as K-NN algorithm or K-Mean algorithm.

Object recognition by random binary data lookup for Oracle MNIST

Esse jogo utiliza uma Api de reconhecimento de voz para gerar interatividade com o usuário que deve acertar um numero aleatório sorteado pelo sistema. Jogo feito por Vinícius Dias Rodrigues

Automatic License Plate Recognition System.

Object recognition by random binary data lookup for QMNIST

This space contains the code developed for the image pattern recognition lecture

Object recognition by random binary data lookup for Fashion MNIST

This project was my final Bachelor's degree thesis. In it I decided to mix my passion, music, and the syllabus that I liked the most in my degree, deep learning.

Object recognition by random binary data lookup proof of concept for Fashion MNIST

Esse projeto utiliza uma API de reconhecimento de voz para gerar interatividade com o usuário que deve acertar o nome da cor sorteada pelo sistema. Projeto ainda em processo de construção.

It's an app built in Flutter that allows you to recognize the kana (hiragana and katakana) drawn in the app.

Semantic Graph Representation Learning for Handwritten Mathematical Expression Recognition (ICDAR 2023)

The C++ neural network for handwritten digit recognition with online demo