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What is Convolutional Neural Network (CNN)

Smart Systems Design, Applications, and Challenges
A class of deep neural networks applied to image processing where some of the layers apply convolutions to input data.
Published in Chapter:
Deep Learning on Edge: Challenges and Trends
Mário P. Véstias (INESC-ID, ISEL, Instituto Politécnico de Lisboa, Portugal)
Copyright: © 2020 |Pages: 20
DOI: 10.4018/978-1-7998-2112-0.ch002
Abstract
Deep learning on edge has been attracting the attention of researchers and companies looking to provide solutions for the deployment of machine learning computing at the edge. A clear understanding of the design challenges and the application requirements are fundamental to understand the requirements of the next generation of edge devices to run machine learning inference. This chapter reviews several aspects of deep learning: applications, deep learning models, and computing platforms. The way deep learning is being applied to edge devices is described. A perspective of the models and computing devices being used for deep learning on edge are given, as well as what challenges face the hardware designers to guarantee the vast set of tight constraints like performance, power consumption, flexibility, etc. of edge computing platforms. Finally, a trends overview of deep learning models and architectures is discussed.
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Contemporary Biometric System Design
These are neural networks used primarily to classify images, cluster images by similarity and perform object recognition within scenes.
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Automatic Detection of Tumor and Bleed in Magnetic Resonance Brain Images
In machine learning, a convolutional neural network is a class of deep, feed-forward artificial neural networks that has successfully been applied to analyzing visual imagery. CNNs use a variation of multilayer perceptrons designed to require minimal preprocessing. They are also known as shift invariant or space invariant artificial neural networks (SIANN), based on their shared-weights architecture and translation invariance characteristics.
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Plant Disease Classification Using Deep Learning Techniques
It is a type of deep neural network that is commonly used in computer vision tasks such as image recognition and classification. It uses convolutional layers to automatically learn and extract features from images.
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Harnessing the Power of Artificial Intelligence for Modelling and Understanding Cultural Heritage Data
is a type of artificial neural network used in image recognition and processing that is specifically designed to process pixel data.
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Deep Learning Applied to COVID-19 Detection in X-Ray Images
It is a type of deep learning model commonly used for image-related tasks. It uses the mathematical operation of convolution to extract features from images. In this chapter the models developed are based on CNN.
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Real-Time Object Detection in Video for Traffic Monitoring
A type of deep neural network that is commonly used for image and video processing tasks, including object detection.
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Design of a Blockchain-Powered Biometric Template Security Framework Using Augmented Sharding
A convolutional neural network (CNN) is a type of artificial neural network used in image recognition and processing.
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Deep Learning for Facial Skin Issues Detection: A Study for Global Care With Healthcare 5.0
A convolutional neural network (CNN or convnet) is a subset of machine learning. It is one of the various types of artificial neural networks which are used for different applications and data types. A CNN is a kind of network architecture for deep learning algorithms and is specifically used for image recognition and tasks that involve the processing of pixel data.
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Deep Learning in Instructional Analysis, Design, Development, Implementation, and Evaluation (ADDIE)
The convolutional neural network (e.g., CNN) is a DL algorithm that can analyze image data and differentiate different objects observed in the data.
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Convolutional Neural Network
A class of deep neural networks applied to image processing where some of the layers apply convolutions to input data.
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Cancer Diagnosis Using Artificial Intelligence (AI) and Internet of Things (IoT)
The two major architectures of DL is Artificial Neural Network (ANN) a sub class of this is Convolutional Neural Network.
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Big Data Application of Breast Cancer Prediction: A Healthcare 5.0 Application for Smart Cities
A Convolutional Neural Network (CNN) is an advanced deep learning algorithm used for image and video recognition. It mimics the human visual processing system, extracting key features through convolutional and pooling layers.
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Precious Metal Prediction by Using XAI in the Perspective of Digital Transformation
Convolutional neural network is an evolution-based math operation that works to perform feature selection and classification tasks through data information.
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