Mlearning.ai

APRIL 8, 2023

With the rise of deep learning (deep learning means multiple levels of neural networks) and neural networks, models such as Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs) began to be used in NLP.

NLP 98

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Viso.ai

APRIL 29, 2024

It was introduced by Geoffrey Hinton and his team in 2012, and marked a key event in the history of deep learning, showcasing the strengths of CNN architectures and its vast applications. The methods and innovation introduced became a standard for training Deep Neural Networks. Makes it difficult for the model to overfit.

Deep Learning 52

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Viso.ai

MARCH 12, 2024

Today’s boom in computer vision (CV) started at the beginning of the 21 st century with the breakthrough of deep learning models and convolutional neural networks (CNN). The same CNN, with an extra sixth convolutional layer, was used to classify the entire ImageNet Fall 2011 release (15M images, 22K categories).

Computer Vision 52

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Towards AI

JULY 20, 2023

Introduction to Region with Convolutional Neural Networks (R-CNNs) Photo by Edward Ma on Unsplash Region with Convolutional Neural Network (R-CNN) is proposed by Girshick et al. achieved a very good result in VOC 2012. It changed the object detection field fundamentally.

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Viso.ai

MAY 7, 2024

However, GoogLeNet demonstrated by using the inception module that depth and width in a neural network could be increased without exploding computations. GooLeNet – source Historical Context The concept of Convolutional Neural Networks ( CNNs ) isn’t new.

Explainability 52

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Flipboard

JULY 31, 2023

Nowadays, with the advent of deep learning and convolutional neural networks, this process can be automated, allowing the model to learn the most relevant features directly from the data. a convolutional neural network), which then learns to map the features of each image to its correct label.

Machine Learning 104

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Viso.ai

FEBRUARY 19, 2024

To overcome this IP concern – researchers have applied a Convolutional Neural Network (CNN) to detect plagiarized text and images as well as problematic deepfakes on the internet. In visual media, deepfake tools employ several methods to manipulate different characteristics or features. Footprint recognition – source.

Computer Vision 52

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Lexalytics

APRIL 5, 2021

And indeed we can see other machine learning topics arising to take their place, like “optimization” in the mid-’00s, with “deep learning” springing out of nowhere in 2012. So, whatever did happen to neural networks? The CNN was a 6-layer neural net with 132 convolution kernels and (don’t laugh!) Hinton (again!)

Neural Network 52

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deepsense.ai

MAY 7, 2023

This solution is based on several Convolutional Neural Networks that work in a cascade fashion to locate the face with some landmarks in an image. The first network is called a Proposal Network – it parses the image and selects several bounding boxes that surround an object of interest: a face, in our case.

Neural Network 52

Neural Network Convolutional Neural Networks Explainability Deep Learning 52

Viso.ai

DECEMBER 21, 2023

From the development of sophisticated object detection algorithms to the rise of convolutional neural networks (CNNs) for image classification to innovations in facial recognition technology, applications of computer vision are transforming entire industries. Thus, positioning him as one of the top AI influencers in the world.

Convolutional Neural Networks 52

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