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What is Convolutional Neural Networks

Encyclopedia of Information Science and Technology, Fourth Edition
A multi layer neural network similar to artificial neural networks only differs in its architecture and mainly built to recognize visual patterns from image pixels.
Published in Chapter:
An Insight Into Deep Learning Architectures
Nishu Garg (VIT University, India), Nikhitha P (VIT University, India), and B. K. Tripathy (VIT University, India)
DOI: 10.4018/978-1-5225-2255-3.ch393
Abstract
Information retrieval can be visualized as the extraction of the desired information from the flooded resources that spread over World Wide Web. Image retrievals are the fundamental and critical problem that arises in the retrieval activities. In this regard, it is considered to be a challenging task which requires utmost care. Diverse characteristics of data such as noisy, heterogeneity impose a great barrier over image retrieval applications. This article aims to come up with a state of art approach for overcoming these problems by clubbing together widely recognized deep architecture along with natural language processing. This novel design methodology utilizes the latent query features, deep belief network, Restricted Boltzmann Machine for learning tasks. This collaborative work can be used to reduce the epoch in the learning periods whereas the rest of the methods fail to achieve the constraints.
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Automated Essay Scoring Using Deep Learning Algorithms
A type of deep learning algorithm commonly applied in analyzing image inputs.
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Ethical Considerations and Challenges in Neurodegenerative Diseases Using Machine Learning
Convolutional neural networks (CNNs) are deep learning models specifically designed for processing grid-like data, using convolutional layers to automatically and adaptively learn spatial hierarchies of features from input images.
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Harnessing the Power of Machine Learning for Parkinson's Disease Detection
It is a deep learning network design that derives its knowledge directly from data. CNNs are very helpful for recognizing objects, classifications, and categories in photos by looking for patterns in the images.
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Digital Recognition of Breast Cancer Using TakhisisNet: An Innovative Multi-Head Convolutional Neural Network for Classifying Breast Ultrasonic Images
A convolutional neural network (CNN) is a type of artificial neural network used in image recognition and processing that is specifically designed to process pixel data by means of learnable filters.
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Model Optimisation Techniques for Convolutional Neural Networks
It is the most common deep learning architecture and is based on the convolution process. These models are mainly applied to the computer vision applications.
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Text-Based Image Retrieval Using Deep Learning
A multi-layer neural network similar to artificial neural networks only differs in its architecture and mainly built to recognize visual patterns from image pixels.
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Artificial Intelligence in Teleradiology: A Rapid Review of Educational and Professional Contributions
A type of artificial neural network specifically designed to process data that has a grid-like structure and is used in computer vision and image processing tasks, such as object recognition and classification.
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Subjective and Objective Assessment for Variation of Plant Nitrogen Content to Air Pollutants Using Machine Intelligence: Subjective and Objective Assessment
A convolutional neural network (CNN) is a type of artificial neural network used in image recognition and processing that is specifically designed to process pixel data. CNNs are powerful image processing, artificial intelligence (AI) that use deep learning to perform both generative and descriptive tasks, often using machine vision that includes image and video recognition, along with recommender systems and natural language processing (NLP).
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