Complexity of Deep Convolutional Neural Networks in Mobile Computing

Table 1

Comparison.

Ref.	Techniques/common parameters	Initialization	Compression	Quantization	Speed-up	Onboard
1(1)	Accelerated learning	✔	✘	✘	✔	✔
2(2)	Discrete cosine transform	✔	✔	✔	✘	✔
3(3)	Deep compression	✔	✔	✔	✔	✔
4(4)	Neural network compression	✘	✔	✘	✔	✔
5(5)	Mobile devices	✘	✘	✘	✔	✘
6(6)	Model compression	✔	✔	✔	✔	✔
7(7)	Proper parameters	✔	✘	✘	✔	✔
8(8)	YOLO platform	✔	✘	✘	✔	✔
9(9)	Light-weight CNNs	✘	✘	✘	✔	✔
10(10)	Distributed network architecture	✘	✘	✘	✔	✘
11(11)	Quantized CNNs	✘	✔	✔	✔	✔
12(12)	ShuffleNet architecture	✘	✘	✔	✔	✔