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Metaheuristic-Optimized Convolutional Neural Network for Automated Diagnosis of Viral Pneumonia and Tuberculosis from Chest X-Rays. [PDF]
Diagnostics (Basel)Hermosilla P +5 more
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DK-CNNs: Dynamic kernel convolutional neural networks [PDF]
Neurocomputing, 2021 This paper introduces dynamic kernel convolutional neural networks (DK-CNNs), an enhanced type of CNN, by performing line-by-line scanning regular convolution to generate a latent dimension of kernel weights. The proposed DK-CNN applies regular convolution to the DK weights, which rely on a latent variable, and discretizes the space of the latent ...
Changjing Shang +2 more
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C-CNN: Contourlet Convolutional Neural Networks
IEEE Transactions on Neural Networks and Learning Systems, 2021Extracting effective features is always a challenging problem for texture classification because of the uncertainty of scales and the clutter of textural patterns. For texture classification, spectral analysis is traditionally employed in the frequency domain.
Mengkun Liu +5 more
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Convolutional Neural Networks (CNN)
2021Convolutional neural networks (CNN or ConvNet) are a specific type of neural networks for processing grid-like data such as images and time series. In healthcare applications, the CNN models are widely used in automatic feature learning and disease classification from medical images, for example, automatic classification of skin lesions, detection of ...
Cao Xiao, Jimeng Sun
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Cellular neural network friendly convolutional neural networks — CNNs with CNNs
Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017, 2017This paper discusses the development and evaluation of a Cellular Neural Network (CeNN) friendly deep learning network for solving the MNIST digit recognition problem. Prior work has shown that CeNNs leveraging emerging technologies such as tunnel transistors can improve energy or EDP of CeNNs, while simultaneously offering richer/more complex ...
András Horváth +4 more
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Convolutional Neural Networks (CNN)
2022Deep learning is one of the main technologies of machine learning. With deep learning, this chapter is talking about algorithms capable of mimicking the actions of the human brain through artificial neural networks. Compared to other algorithmic structures, neural networks have great advantages: first, their structure based on the stacking of non ...
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Convolutional Neural Network (CNN): The architecture and applications
Applied Journal of Physical Science, 2022The human brain is made up of several hundreds of billions of interconnected neurons that process information in parallel. Researchers in the field of artificial intelligence have successfully demonstrated a considerable level of intelligence on chips and this has been termed Neural Networks (NNs).
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