Towards AI

MAY 12, 2024

Photo by Erik Mclean on Unsplash This article uses the convolutional neural network (CNN) approach to implement a self-driving car by predicting the steering wheel angle from input images of three front cameras in the car’s center, left, and right. Levels of Autonomy. [3] Yann LeCun et al., Yann LeCun et al.,

Convolutional Neural Networks 119

Convolutional Neural Networks Neural Network Auto-classification Categorization 119

Becoming Human

MARCH 16, 2023

This post includes the fundamentals of graphs, combining graphs and deep learning, and an overview of Graph Neural Networks and their applications. Through the next series of this post here , I will try to make an implementation of Graph Convolutional Neural Network. So, let’s get started! What are Graphs?

Neural Network 87

Neural Network Auto-classification Convolutional Neural Networks Auto-complete 87

Unite.AI

AUGUST 29, 2023

The implementation of TinyML for computer vision based application on edge platforms required developers to overcome the major challenge of CNN or Convolutional Neural Networks with a high generalization error, and high training & testing accuracy.

Neural Network 246

Neural Network ML Algorithm Auto-classification 246

Heartbeat

JUNE 27, 2023

Neural networks leverage the structure and properties of graph and work in a similar fashion. Graph Neural Networks are a class of artificial neural networks that can be represented as graphs. Edge-level tasks , on the other hand, entail edge classification and link prediction.

Neural Network 59

Neural Network Convolutional Neural Networks Auto-classification Deep Learning 59

PyImageSearch

FEBRUARY 6, 2023

Table of Contents Training a Custom Image Classification Network for OAK-D Configuring Your Development Environment Having Problems Configuring Your Development Environment? Furthermore, this tutorial aims to develop an image classification model that can learn to classify one of the 15 vegetables (e.g.,

Auto-classification 137

Auto-classification Computer Vision Neural Network Deep Learning 137

Google Research AI blog

JANUARY 18, 2023

Complex, information-seeking tasks. Transform modalities, or translate the world’s information into any language. Additionally, language models of sufficient scale have the ability to learn and adapt to new information and tasks, which makes them even more versatile and powerful. All kinds of tasks.

Computer Vision 132

Computer Vision Auto-classification Large Language Models Neural Network 132

Viso.ai

DECEMBER 3, 2023

Today, the most powerful image processing models are based on convolutional neural networks (CNNs). This field has attracted much interest in recent years since it is used to provide extensive 3D structure information related to the human body. Planar Model , or contour-based model, is used for 2D pose estimation.

Deep Learning 98

Deep Learning Computer Vision Neural Network Robotics 98