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Generalized Gradient Flow Based Saliency for Pruning Deep Convolutional Neural Networks
Model filter pruning has shown efficiency in compressing deep convolutional neural networks by removing unimportant filters without sacrificing the...
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Object detection and classification of butterflies using efficient CNN and pre-trained deep convolutional neural networks
With over 18,000 species, butterflies account for nearly one-quarter of all identified species on the planet. The images of different butterfly...
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Automatic Food Recognition Using Deep Convolutional Neural Networks with Self-attention Mechanism
The significance of food in human health and well-being cannot be overemphasized. Nowadays, in our dynamic life, people are increasingly concerned...
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Deep multi-scale convolutional neural networks for automated classification of multi-class leaf diseases in tomatoes
Deep learning techniques have gained immense popularity recently because of their remarkable capacity to learn complex patterns and features from...
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Classification of non-small cell lung cancers using deep convolutional neural networks
Lung cancer is a major cause of cancer-related deaths worldwide, and early detection is crucial in reducing mortality rates. To aid in this effort,...
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A Deep Convolutional Spiking Neural Network for embedded applications
Deep neural networks (DNNs) have received a great deal of interest in solving everyday tasks in recent years. However, their computational and energy...
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Improve the efficiency of handcrafted features in image retrieval by adding selected feature generating layers of deep convolutional neural networks
Today, with the rapid growth of communication technology and the development of social networks and smartphones, the amount of data stored by users...
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Comprehensive comparison of modified deep convolutional neural networks for automated detection of external and middle ear conditions
Otitis media disease, a frequent childhood ailment, could have severe repercussions, including mortality. This disease induces permanent hearing...
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DeepCONN: patch-wise deep convolutional neural networks for the segmentation of multiple sclerosis brain lesions
Segmentation is a critical process for examining Multiple Sclerosis (MS) brain lesions for diagnosis, follow-up, and prognosis of the disease. The...
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Use of artificial neural networks in architecture: determining the architectural style of a building with a convolutional neural networks
The discussion of "can machines think?" which started with the invention of the modern computer, brought along the question of "can machines design?"...
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Optimization of microscopy image compression using convolutional neural networks and removal of artifacts by deep generative adversarial networks
Nowadays, microscopy images are significant in medical research and clinical studies. However, storage and transmission of data such as microscopy...
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Deep Convolutional Neural Network for Knowledge-Infused Text Classification
Deep neural networks are extensively used in text mining and Natural Language Processing is to enable computers to understand, analyze, and generate...
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Convolutional Neural Networks and Architectures
This chapter briefly introduces Convolutional Neural Networks (CNNs). One of the first CNNs is proposed in [41] (known as LeNet) to deal with...
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A dimensionality reduction approach for convolutional neural networks
The focus of this work is on the application of classical Model Order Reduction techniques, such as Active Subspaces and Proper Orthogonal...
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Learning to rank influential nodes in complex networks via convolutional neural networks
AbstractIdentifying influential nodes is crucial for enhancing information diffusion in complex networks. Several approaches have been proposed to...
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Multiple features-based adverse drug reaction detection from social media using deep convolutional neural networks (DCNN)
Adverse drug responses (ADRs) are unfavourable side effects of using a medication that result from the medication's pharmacological activity. Social...
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Gaze estimation using convolutional neural networks
Numerous investigations on gaze estimate techniques for analyzing human behavior have been made in recent years, the majority of which have focused...
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Leveraging Quantum computing for synthetic image generation and recognition with Generative Adversarial Networks and Convolutional Neural Networks
The generation and classification of synthetic images is a challenging and important task in the digital age. Generative Adversarial Networks are...
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Image category classification using 12-Layer deep convolutional neural network
In comparison to human vision, it’s hard for systems to understand images and figure them out on their own. In the modern world, image processing is...
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New design strategies of deep heterogenous convolutional neural networks ensembles for breast cancer diagnosis
One of the most consequential public health issues in the world and a major factor in women's mortality is breast cancer. Early detection and...
