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CNN

Last updated May 21, 2025, generated by Sumble

What is CNN?

CNN stands for Convolutional Neural Network. It is a type of deep learning neural network primarily used for analyzing visual data, such as images and videos. CNNs are commonly used for image recognition, object detection, image classification, and other computer vision tasks. They work by using convolutional layers to extract features from the input data, followed by pooling layers to reduce the dimensionality of the feature maps, and finally fully connected layers to make predictions.

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What other technologies are related to CNN?

CNN Competitor Technologies

RNN

Recurrent Neural Networks (RNNs) are an alternative architecture for processing sequential data and are used in tasks where CNNs might also be applicable, like video analysis.

LSTM

Long Short-Term Memory networks are a type of RNN, and are therefore an alternative architecture. They are used in tasks where CNNs might also be applicable, like video analysis.

Transformer

Transformers are an alternative architecture primarily for sequence-to-sequence tasks, but have begun competing in areas traditionally served by CNNs, such as image recognition.

SVM

Support Vector Machines are a different machine learning approach that competes with CNNs for classification and regression tasks, although less common in image recognition.

GNN

Graph Neural Networks operate on graph-structured data, providing an alternative approach to CNNs when the underlying data can be represented as a graph.

ANN

Artificial Neural Networks are a broader category that includes CNNs, but also represents alternative architectures, such as MLPs, which can be used for similar tasks.

FCN

No summary available

Fully Convolutional Networks are a specific architecture related to CNNs, but they represent a design choice that competes with other CNN architectural decisions.

DNN

Deep Neural Networks is a broad term that encompasses many architectures, including CNNs, but they can also be alternative architectures, such as deep belief networks.

Number of organizations that mention technology

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CNN Complementary Technologies

TensorFlow

TensorFlow is a deep learning framework that provides tools and libraries to implement and train CNNs.

PyTorch

PyTorch is a deep learning framework that provides tools and libraries to implement and train CNNs.

distributed training

Distributed training is a technique used to accelerate the training of large CNN models by distributing the workload across multiple devices.

Number of organizations that mention technology

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Which job functions commonly mention CNN?

Machine Learning

1.0% of all Machine Learning jobs mention CNN

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AI Engineer

0.7% of all AI Engineer jobs mention CNN

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Applied Scientist

0.6% of all Applied Scientist jobs mention CNN

View 70 jobs on Sumble

Data Scientist

0.5% of all Data Scientist jobs mention CNN

View 1.3k jobs on Sumble

Data, Analytics & Machine Learning

0.2% of all Data, Analytics & Machine Learning jobs mention CNN

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Which organizations are mentioning CNN?

JPMorgan Chase

Finance and Insurance

Morningstar

Finance and Insurance

Qualcomm

Scientific and Technical Services

Amazon

Retail Trade

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