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A review of convolutional neural networks in computer vision
In computer vision, a series of exemplary advances have been made in several areas
involving image classification, semantic segmentation, object detection, and image super …
involving image classification, semantic segmentation, object detection, and image super …
Speech recognition using deep neural networks: A systematic review
Over the past decades, a tremendous amount of research has been done on the use of
machine learning for speech processing applications, especially speech recognition …
machine learning for speech processing applications, especially speech recognition …
Branchformer: Parallel mlp-attention architectures to capture local and global context for speech recognition and understanding
Conformer has proven to be effective in many speech processing tasks. It combines the
benefits of extracting local dependencies using convolutions and global dependencies …
benefits of extracting local dependencies using convolutions and global dependencies …
Adan: Adaptive nesterov momentum algorithm for faster optimizing deep models
In deep learning, different kinds of deep networks typically need different optimizers, which
have to be chosen after multiple trials, making the training process inefficient. To relieve this …
have to be chosen after multiple trials, making the training process inefficient. To relieve this …
Deep learning for audio signal processing
Given the recent surge in developments of deep learning, this paper provides a review of the
state-of-the-art deep learning techniques for audio signal processing. Speech, music, and …
state-of-the-art deep learning techniques for audio signal processing. Speech, music, and …
Deep convolutional neural networks for image classification: A comprehensive review
Convolutional neural networks (CNNs) have been applied to visual tasks since the late
1980s. However, despite a few scattered applications, they were dormant until the mid …
1980s. However, despite a few scattered applications, they were dormant until the mid …
Conceptual understanding of convolutional neural network-a deep learning approach
Deep learning has become an area of interest to the researchers in the past few years.
Convolutional Neural Network (CNN) is a deep learning approach that is widely used for …
Convolutional Neural Network (CNN) is a deep learning approach that is widely used for …
Recommendation system based on deep learning methods: a systematic review and new directions
A Da'u, N Salim - Artificial Intelligence Review, 2020 - Springer
These days, many recommender systems (RS) are utilized for solving information overload
problem in areas such as e-commerce, entertainment, and social media. Although classical …
problem in areas such as e-commerce, entertainment, and social media. Although classical …
A convolutional neural network based feature learning and fault diagnosis method for the condition monitoring of gearbox
Feature extraction plays a vital role in intelligent fault diagnosis of mechanical system.
Nevertheless, traditional feature extraction methods suffer from three problems, which are …
Nevertheless, traditional feature extraction methods suffer from three problems, which are …
Recent advances in convolutional neural networks
In the last few years, deep learning has led to very good performance on a variety of
problems, such as visual recognition, speech recognition and natural language processing …
problems, such as visual recognition, speech recognition and natural language processing …