A Turning Point in AI History: The Difference Between Before and After Deep Learning

The image recognition system AlexNet, unveiled at an international conference in 2012, demonstrated performance that ...
BIOENGINEER

Deep Learning Meets Multi-Objective Optimization to Grade Vocational Teaching Quality

A new hybrid AI framework combining deep convolutional networks with multi-objective evolutionary optimization achieves 98.5 ...
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What is a convolutional neural network (CNN)?

A convolutional neural network (CNN) is a category of machine learning model. Specifically, it is a type of deep learning algorithm that is well suited to analyzing visual data. CNNs are commonly used ...
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Understanding convolutional neural networks

The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...

Terms from Convolution Output Size to Natural Language Processing Vectorization Methods Asked in the 2nd G-Certification Mock Exam

Source: Yoshitaka Tomiyama Published: 2020-03-04 / 44 minutes / 24,000 views Scope: The second in a series of explanations ...
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Deep Learning Cheat Sheet for Beginners & Professionals

Overview:  Deep learning uses multi-layer neural networks to learn patterns from data.CNNs, RNNs, LSTMs, transformers, and ...
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What are graph neural networks (GNNs)?

Graph neural networks (GNNs) are a type of neural network architecture and deep learning method that can help users analyze graphs, enabling them to make predictions based on the data described by a ...