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Updated: Feb 15, 2026

Deep Learning-Based Segmentation of Cryo-Electron Tomograms
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D2Dミリ波通信におけるディープラーニングベースの予測による中断の確率とエネルギー消費の最小化

N Md Bilal1, T Velmurugan2

  • 1School of Electronics Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India.

Scientific reports
|February 13, 2026
PubMed
まとめ

この研究は,デバイス対デバイス (D2D) のミリ波通信における中断の確率とエネルギー使用量を減らすためにディープラーニングモデルを導入しています. 新しいFEHO+DSNNアプローチは,ネットワークの強度と効率を高めます.

キーワード:
D2D ミリメートル波通信ディープスパイキングニューラルネットワークElk Herdの最適化についてフラミンゴ・エルク群の最適化フラミンゴの検索アルゴリズム

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