Enhancement of Detection of Diabetic Retinopathy Using Harris Hawks Optimization with Deep Learning Model

Algorithm 1

HHO Algorithm Pseudocode [18].

(1)	Inputs: All features extracted from fundus image data set.
(2)	Outputs: Optimal feature set
(3)	Initialize the population randomly, Ci(i = 1,2,…,M)
(4)	Set C    while until end condition met do Compute the hawk’s fitness values. Victim as the victim best location
(i)	end
(5)	for each hawk (Ci) do
(6)	Update the strength of jump S and initial energy G0
	end
(7)	G0 = 2rand() − 1, S = 2(1 − rand())
(8)	Update the energy G using (3)
	end
(9)	if |G| ≥ 1 then
(10)	The vector of location is updated using Eq.
	end
(11)	if |G| < 1 then
(12)	if |G| ≥ 0.5 and q ≥ 0.5 then
(13)	The vector of location is updated using (4)
	end
(14)	else if |G| < 0.5 and q ≥ 0.5 then
(15)	The vector of location is updated using (6)
	end
(16)	else if |G| ≥ 0.5 and q < 0.5 then
(17)	The vector of location is updated using (10)
(18)	else if |G| < 0.5 and q < 0.5 then
(19)	The vector of location is updated using (11)
(20)	end
(21)	return Cvictim