TMCnet

Bridging Silence: A Real-Time Sign Language to English Text Translation System Using Python, OpenCV, and Convolutional Neural Networks

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive technology and inclusive education. In an attempt to close that gap, I developed a ...
Hosted on MSN

Build a deep neural network from scratch in Python

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...
Scientific Research Publishing

Honnibal, M., Montani, I., Van Landeghem, S. and Boyd, A. (2020) SpaCy 2: Natural Language Understanding with Bloom Embeddings, Convolutional Neural Networks and Incremental ...

ABSTRACT: This paper examines the extent to which competencies taught in Congolese universities match the skills required by the labour market. Using official curricula from the Ministry of Higher and ...
IEEE

Inception V4 Convolution Neural Network towards Detection and Classification of Brain Hemorrhage using CT Images

Abstract: Brain Hemorrhage is occurs due to obstruction of blood vessels in the brain. It causes high mortality and disability across the human population in the world. Due to advancement of the ...
IEEE

Handwritten Digit Recognition with Feed-Forward Multi-Layer Perceptron and Convolutional Neural Network Architectures

Abstract: Nowadays, Artificial Intelligence (AI) is playing a vital role in data classification. In this work, a Python library called as Keras, is used for classification of MNIS T dataset, a ...
Hosted on MSN

Dropout In Neural Networks — Prevent Overfitting Like A Pro (With Python)

This video is an overall package to understand Dropout in Neural Network and then implement it in Python from scratch. Dropout in Neural Network is a regularization technique in Deep Learning to ...
GitHub

convolution_neural_network.py

self, conv1_get, size_p1, bp_num1, bp_num2, bp_num3, rate_w=0.2, rate_t=0.2 :param conv1_get: [a,c,d], size, number, step of convolution kernel :param size_p1 ...