[PDF][PDF] 卷积神经网络研究综述
周飞燕, 金林鹏, 董军 - 计算机学报, 2017 - cjc.ict.ac.cn
摘要作为一个十余年来快速发展的崭新领域, 深度学习受到了越来越多研究者的关注,
它在特征提取和模型拟合上都有着相较于浅层模型显然的优势. 深度学习善于从原始输入数据中 …
它在特征提取和模型拟合上都有着相较于浅层模型显然的优势. 深度学习善于从原始输入数据中 …
A comprehensive survey on convolutional neural network in medical image analysis
CNN is inspired from Primary Visual (V1) neurons. It is a typical deep learning technique
and can help teach machine how to see and identify objects. In the most recent decade …
and can help teach machine how to see and identify objects. In the most recent decade …
[HTML][HTML] Convolutional neural networks: A survey
M Krichen - Computers, 2023 - mdpi.com
Artificial intelligence (AI) has become a cornerstone of modern technology, revolutionizing
industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of …
industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of …
[HTML][HTML] Developing a speech recognition system for recognizing tonal speech signals using a convolutional neural network
S Dua, SS Kumar, Y Albagory, R Ramalingam… - Applied Sciences, 2022 - mdpi.com
Deep learning-based machine learning models have shown significant results in speech
recognition and numerous vision-related tasks. The performance of the present speech-to …
recognition and numerous vision-related tasks. The performance of the present speech-to …
Flexflow: A flexible dataflow accelerator architecture for convolutional neural networks
Convolutional Neural Networks (CNN) are very computation-intensive. Recently, a lot of
CNN accelerators based on the CNN intrinsic parallelism are proposed. However, we …
CNN accelerators based on the CNN intrinsic parallelism are proposed. However, we …
Automatic sleep stage scoring with single-channel EEG using convolutional neural networks
We used convolutional neural networks (CNNs) for automatic sleep stage scoring based on
single-channel electroencephalography (EEG) to learn task-specific filters for classification …
single-channel electroencephalography (EEG) to learn task-specific filters for classification …
Far-field automatic speech recognition
The machine recognition of speech spoken at a distance from the microphones, known as
far-field automatic speech recognition (ASR), has received a significant increase in attention …
far-field automatic speech recognition (ASR), has received a significant increase in attention …
Comparison of machine learning algorithms for predicting crime hotspots
Crime prediction is of great significance to the formulation of policing strategies and the
implementation of crime prevention and control. Machine learning is the current mainstream …
implementation of crime prevention and control. Machine learning is the current mainstream …
LSTM time and frequency recurrence for automatic speech recognition
Long short-term memory (LSTM) recurrent neural networks (RNNs) have recently shown
significant performance improvements over deep feed-forward neural networks (DNNs). A …
significant performance improvements over deep feed-forward neural networks (DNNs). A …
A feature fusion-based convolutional neural network for battery state-of-health estimation with mining of partial voltage curve
Accurately estimating the state-of-health of batteries is critical for effective battery monitoring
and management. However, the estimation remains challenging due to dynamic operation …
and management. However, the estimation remains challenging due to dynamic operation …