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نمایش تعداد 1-6 از 6

High-Quality Depth Recovery via Interactive Multi-view Stereo

نوع: Conference Paper

نویسنده : Chen, Weifeng; Zhang, Guofeng; Xiang, Xiaojun; Jia, Jiaya; Bao, Hujun

ناشر: IEEE

سال: 2014

An improved algorithm for the detection of photoplethysmographic percussion peaks

نوع: Conference Paper

نویسنده : Luo, Feifei; Li, Jin; Yun, Feng; Chen, Tianjun; Chen, Xiang

ناشر: IEEE

سال: 2014

Compendium of Single Event Effects, Total Ionizing Dose, and Displacement Damage for Candidate Spacecraft Electronics for NASA

نوع: Conference Paper

ناشر: IEEE

سال: 2014

Sudo Pi Cooler / Heater: Raspberry Pi to design an adaptive temperature sensor

نوع: Conference Paper

نویسنده : Ryner, B.; Bishop, W.; Hyland, D.; Drozd, N.; Ghanavati, A.; Bograd, M.; Sena, G.; Nakagomi, R.M.; Miro, Z.

ناشر: IEEE

سال: 2014

The Armington recognition award

نوع: Conference Paper

ناشر: IEEE

سال: 2014

Fast algorithm for computing weighted projection quantiles and data depth for high-dimensional large data clouds

نوع: Conference Paper

نویسنده : Mukherjee, Ujjal Kumar; Chatterjee, Snigdhansu

ناشر: IEEE

سال: 2014

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High-Quality Depth Recovery via Interactive Multi-view Stereo

An improved algorithm for the detection of photoplethysmographic percussion peaks

Compendium of Single Event Effects, Total Ionizing Dose, and Displacement Damage for Candidate Spacecraft Electronics for NASA

Sudo Pi Cooler / Heater: Raspberry Pi to design an adaptive temperature sensor

The Armington recognition award

Fast algorithm for computing weighted projection quantiles and data depth for high-dimensional large data clouds

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High-Quality Depth Recovery via Interactive Multi-view Stereo

An improved algorithm for the detection of photoplethysmographic percussion peaks

Compendium of Single Event Effects, Total Ionizing Dose, and Displacement Damage for Candidate Spacecraft Electronics for NASA

Sudo Pi Cooler / Heater: Raspberry Pi to design an adaptive temperature sensor

The Armington recognition award

Fast algorithm for computing weighted projection quantiles and data depth for high-dimensional large data clouds