通过在不同阶段共享Dec,模型变得紧凑,并且已经取得了更好的结果。然而,由于共享了公共的模型参数,Dec会以相同的方式处理来自不同阶段的输入 qi 和 bi ,这可能会降低其适应性,并限制其性能。作者打算引入更多来自上一阶段的信息,并进行补偿,以便Dec能够感知解码阶段并相应地进行调整。 值得注意的是,对于DETR系列,通...
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Combining CNN and LSTM yielded an RMSE of 32.436 and an MAE of 25.382, demonstrating the potential for significantly improving neonatal care.I Komang Agus Ady AryantoDechrit ManeethamPadma Nyoman CrisnapatiApplied Sciences-Basel
Combining CNN and LSTM yielded an RMSE of 32.436 and an MAE of 25.382, demonstrating the potential for significantly improving neonatal care.Aryanto, I Komang Agus AdyManeetham, DechritCrisnapati, Padma NyomanApplied Sciences (2076-3417)
Findings from University of Malaga Broaden Understanding of Electronics (FPGA-Based CNN for Eye Detection in an Iris Recognition at a Distance System)University of MalagaElectronicsEmerging TechnologiesEngineeringIris RecognitionMachine LearningNetworks