Abstract: Electroencephalography (EEG) is an effective assessment tool to identify autism spectrum disorders with low cost, and deep learning has been applied in EEG analysis for extracting meaningful ...
Abstract: Convolutional neural networks (CNNs) have been foundational in deep learning architectures for image processing, and recently, Transformer networks have emerged, bringing further ...
Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
Abstract: The utilization of digital video alterations has been observable for an extended period thanks to skillful deployment of visual enhancements; however, the latest progressions in deep ...
Abstract: Orthogonal Frequency Division Multiplexing (OFDM) enables high-rate data transmission wards wirelss broadband connections. Accurate channel estimation continues to be an unsolved issue in ...
CNN is on the brink of having yet another new owner and, as of this moment, it's anyone's guess as to who it'll be. In October, CNN's parent company, Warner Bros. Discovery announced it was putting ...
Paramount Skydance’s hostile takeover bid of Warner Bros. Discovery, announced Monday, places CNN and its sister cable networks squarely back into what is likely to be an extended period of management ...
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: Marine exploration, environmental monitoring as well as autonomous underwater vehicles need underwater imaging, however, it is severely degraded by light absorption, scattering and color ...
Abstract: High impedance ground faults are widely recognized as one of the most frequent failures in high-speed railway traction networks. Due to the complex multi-conductor structure and significant ...