TY - GEN
T1 - Deployment of Object Detection Enhanced with Multi-label Multi-classification on Edge Device
AU - Oderhohwo, Ogheneuriri
AU - Odetola, Tolulope A.
AU - Mohammed, Hawzhin
AU - Rafay Hasan, Syed
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/8
Y1 - 2020/8
N2 - This paper presents a method that enables detecting multiple mutually exclusive features of each class using the same convolutional neural network (CNN). This method proposes the design of a Multi-Label Multi-Classification (MLMC) deep learning model on resource-constrained edge devices. The proposed technique is also extended to utilizing the same CNN for classifying heterogeneous datasets. The MLMC model is used in conjunction with object detection techniques that leverage on a cropping system. The combined model used in conjunction with Intel's Neural Compute Stick (NCS) achieves the detection of an object of interest at the rate of 10.51FPS out-performing conventional object detection speed on edge devices.
AB - This paper presents a method that enables detecting multiple mutually exclusive features of each class using the same convolutional neural network (CNN). This method proposes the design of a Multi-Label Multi-Classification (MLMC) deep learning model on resource-constrained edge devices. The proposed technique is also extended to utilizing the same CNN for classifying heterogeneous datasets. The MLMC model is used in conjunction with object detection techniques that leverage on a cropping system. The combined model used in conjunction with Intel's Neural Compute Stick (NCS) achieves the detection of an object of interest at the rate of 10.51FPS out-performing conventional object detection speed on edge devices.
UR - http://www.scopus.com/inward/record.url?scp=85090565070&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85090565070&partnerID=8YFLogxK
U2 - 10.1109/MWSCAS48704.2020.9184601
DO - 10.1109/MWSCAS48704.2020.9184601
M3 - Conference contribution
AN - SCOPUS:85090565070
T3 - Midwest Symposium on Circuits and Systems
SP - 986
EP - 989
BT - 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems, MWSCAS 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 63rd IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2020
Y2 - 9 August 2020 through 12 August 2020
ER -