公开(公告)号：US20230368017A1

公开(公告)日：2023-11-16

申请号：US18042994

申请日：2021-10-05

Applicant: Khalifa University of Science and Technology

Inventor： Mohammed F. TOLBA ,  Hani SALEH ,  Mahmoud AL-QUTAYRI ,  Baker MOHAMMAD

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: A method can be used to reduce the memory storage and energy used by deep neural networks. The method can include determining the weights associated with the deep neural network. An input feature map can be received and used with the weights to generate approximated weights. Using the approximated weights and the input feature map a convolution inference can be performed.

公开(公告)号：US20210116410A1

公开(公告)日：2021-04-22

申请号：US17058485

申请日：2019-06-03

Applicant: Khalifa University of Science and Technology

Inventor： Heba ABUNAHLA ,  Baker MOHAMMAD ,  Anas ALAZZAM ,  Maguy Abi JAOUDE ,  Mahmoud AL-QUTAYRI

IPC: G01N27/327 ,  G01N33/49 ,  G01N33/66

Abstract: A glucose sensor includes an insulating metal oxide layer and at least one pair of metallic electrodes arranged on the insulating metal oxide layer and separated by a gap containing the metal oxide layer. In operation, a probe including a voltage supply and current sensor can provide a voltage difference across the first and second metallic electrodes while a sample is present across the gap between the electrodes. A measured current between the first and second metallic electrodes when the voltage difference is provided can be correlated to a glucose level of the sample.