Clevert, D.-A., Untertiner, T., and Hochreiter, S. (2016). Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs). arXiv [Preprint]. Available ...
Abstract: We present a procedure for computing the convolution of (analog-time) exponential signals without the need of solving integrals. The procedure is algebraic and requires the resolution of a ...
It is difficult for humans to recognize recessive diseases in navel oranges. Therefore, deep neural networks are applied to plant disease identification. To improve the feature extraction ability of ...
calc_broad: broaden theoretically calculated line shape spectrum with voigt profile calc_dads: Calculates decay associated difference spectrum from experimental energy scan and sum of exponential ...
As the exponential advancement of technology accelerates through the knee of the curve, organizational IT departments must lean into the curve and adapt foundational management and governance ...
Proceedings of the 2024 IEEE Texas Power and Energy Conference (TPEC) The exponential electrification of transportation has contributed to highly intermittent load variations in the distribution grid.
In a world where change is not only a constant but also rapidly accelerating, conventional thought patterns are not merely insufficient—they're risky. As an innovation expert, I've observed that the ...
Abstract: This article introduces a new flexible four parameter distribution by convolution of the exponential and Weibull distribution using the odd function transformation, which offers greater ...
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