Abstract: As AI technology evolves, seeing is not believing. The boundary between human and machine creativity is increasingly blurred, presenting challenges for the art industry. This is more ...
Learn what CNN is in deep learning, how they work, and why they power modern image recognition AI and computer vision ...
Abstract: This paper introduces a deep learning-assisted joint transmit and receive beam tracking approach for uplink multiple-input multiple-output (MIMO) communication over millimeter wave (mmWave) ...
Abstract: This article proposed a wired network fault diagnosis method based on 1-D convolutional neural network (1D-CNN) and distributed reflectometer. This article improved the distributed ...
Abstract: An effective temporal modeling approach is crucial for improving traffic flow prediction accuracy. Traditional traffic flow prediction methods have certain limitations in capturing long-term ...
Behavioral Classification of Sequential Neural Activity Using Time Varying Recurrent Neural Networks
Abstract: Shifts in data distribution across time can strongly affect early classification of time-series data. When decoding behavior from neural activity, early detection of behavior may help in ...
President Donald Trump suggested Thursday that the United States is preparing to take new action against alleged drug trafficking networks in Venezuela, telling service members during a Thanksgiving ...
A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN ...
Abstract: ’Fake news’ refers to false, inaccurate, or misleading information that spreads as real news. Fake news primarily aims to affect societies and individuals by spreading false or misleading ...
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