نتایج جستجو برای: k stage network

تعداد نتایج: 1358583  

1997
Chiang-Ling Ng Seung-Woo Seo Hisashi Kobayashi

This paper describes the performance analysis of a class of two-connected multihop shuf lenets , known as generalized s h u f l e networks. The topology of such networks is described mathematically b y the equation N = kn, where N is the total number of nodes in the network, k the number of stages i n the network and n the number of nodes in each stage. Compared t o classical shuf lenets , the ...

Journal: :Sustainability 2021

Convolutional Neural Networks (CNNs) have become common in many fields including computer vision, speech recognition, and natural language processing. Although CNN hardware accelerators are already included as part of SoC architectures, the task achieving high accuracy on resource-restricted devices is still considered challenging, mainly due to vast number design parameters that need be balanc...

Journal: :Experimental animals 2003
Hideki Katoh Koji Oda Kyoji Hioki Kaori Muguruma

We have established a genetic quality testing system for early stage embryos of the mouse. A method of preparation of template DNA for PCR was established using the lysis buffer (1 x PCR reaction buffer supplemented with proteinase K at a concentration of 40 microg/ml) developed by the authors. We demonstrated that two 8-cell embryos of an inbred strain provide sufficient volumes of template DN...

Journal: :Journal of Network and Systems Management 2012

ژورنال: مرتع 2020
Dashtizadeh, Mahmood, Kabiri Fard, Abdlomahdi, Kamali, Amirarsalan, Khaj, Hossein, Sadeghi, MohammadHadi, Sadeghi, Seyed Abootaleb,

This research was carried out to determine nutritive value of Medicago polymorpha and Malva parviflora in various growth stages. The study was conducted at three rangelands during December 2013 to May 2014. The samples of plants were randomly taken in three stages including vegetative growth, flowering and maturity (seed production). Samples of each stage and place were analyzed for DM, CP, EE,...

Journal: :Computers & Security 2022

Deep neural networks are vulnerable to adversarial examples, which can fool deep models by adding subtle perturbations. Although existing attacks have achieved promising results, it still leaves a long way go for generating transferable examples under the black-box setting. To this end, paper proposes improve transferability of and applies dual-stage feature-level perturbations an model implici...

نمودار تعداد نتایج جستجو در هر سال

با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید