首页|Reports from University of Maryland Baltimore County Advance Knowledge in Networks (Reg-tunev2: a Hardware-aware and Multiobjective Regression-based Fine-tuning Approach for Deep Neural Networks On Embedded Platforms)
Reports from University of Maryland Baltimore County Advance Knowledge in Networks (Reg-tunev2: a Hardware-aware and Multiobjective Regression-based Fine-tuning Approach for Deep Neural Networks On Embedded Platforms)
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By a News Reporter-Staff News Editor at Network Daily News - Research findingson Networks are discussed in a new report. According to news reporting originating in Baltimore, Maryland,by NewsRx journalists, research stated, “Fine-tuning deep neural networks (DNNs) for deployment hastraditionally relied on computationally intensive methods such as grid searches and neural architecturesearches, which may not consider hardware-aware metrics. Moreover, it is essential to consider multipleobjectives to develop a range of solutions for tiny machine learning hardware deployment with real-timelatency and low power constraints.”
BaltimoreMarylandUnited StatesNorth and Central AmericaNetworksNeural NetworksUniversity of Maryland Baltimore County
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