feature fusionconvolutional neural network-gated recurrent unit neural networkWith the popular application of deep learning-based models in various classification problems, more and more researchers have applied these models to environmental sound classification (ESC) tasks in recent years. However, the ...
SQUAD 排名靠前的模型中,基本都是以词向量和字符向量共同输入到模型中的,而为了提升效果,似乎也要把字向量和词向量同时输入。但并不想将模型做得太庞大,于是在人工特征这里,加入了字符级特征。 前面介绍的 4 个特征,都是以词为基本单位来计算的,事实上也可以以字为基本单位算一次,然后把每个词内的字的结果平均...
Advanced series decomposition with a gated recurrent unit and graph convolutional neural network for non-stationary data patterns Huimin Han, Harold Neira-Molina, Asad Khan, Meie Fang, Haitham A. Mahmoud, Emad Mahrous Awwad, Bilal Ahmed & Yazeed Yasin Ghadi Journal of Cloud Computing ...
Advances in neural network models and deep learning mark great impact on sentiment analysis, where models based on recursive or convolutional neural networks show state-of-the-art results leaving behidoi:10.1007/978-3-319-64206-2_9Marcin Kuta...
1607.Gated Siamese Convolutional Neural Network Architecture for Human Re-identificationl论文笔记,程序员大本营,技术文章内容聚合第一站。
In this paper, we present a gated convolutional neural network and a temporal attention-based localization method for audio classification, which won the 1st place in the large-scale weakly supervised sound event detection task of Detection and Classification of Acoustic Scenes and Events (DCASE) 201...
gated recurrent unit; GloVe; long short term memory; precision; recall; recurrent neural network; regionbased convolutional neural network; text classification... P Sunagar,A Kanavalli - 《International Journal of Advanced Computer Science & Applications》 被引量: 0发表: 2022年 A multimodal biometri...
Recently, efforts on the residual connections were devoted to improve the feature extraction performances. Huang et al. [28] proposed the densely connected convolutional neural network (DenseNet) structure, where the feature connection between any network layer pair was established. Furthermore, with th...
Network-wide Traffic Speed Prediction (GCGRNN)We are using the traffic speed data from Los Angeles (metr-la.h5) provided in the following paper:Yaguang Li, Rose Yu, Cyrus Shahabi, Yan Liu, "Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting", ICLR 2018....
In this paper, a hybrid neural network short-term load forecasting model based on temporal convolutional network (TCN) and gated recurrent unit (GRU) is proposed. Firstly, the correlation between meteorological features and load is measured with the distance correlation coefficient, and the fixed-...