In Advanced Machine Learning We investigate a CNN composed of three convolution layers: kernel = 3 × 3, stride = 2, padding = same. The lowest layer outputs 100 feature maps, the middle layer 200 feature maps and the highest layer 400 feature maps. The input is a 200 × 300 RGB image. Then:

1 How many parameters does the first layer contain?
A2700
B2800
C3200
D6400
2 How many parameters does the second layer contain?
A180200
B180000
C360000
D184000
3 How many parameters does the third layer contain?
A720000
B720400
C722400
D1440000

answer: this doesnt make any sense especially the photo.

step-by-step explanation:

answer: ratio of volume of cone (with 3 times the height and equal diameter) to volume of cylinder is 2 to 1. the value of π is not used.

step-by-step explanation:

radius is diameter/2 = 4.

area of circle is π r^2.

volume of cylinder is height × area of base = hπr^2 = 3(4^2) π = 48π cubic inches.

not knowing the formula for volume of cone, i calculate it using calculus (which is for calculating things).

volume of cone is integral 0 to h area(y) dy. area(y) is π r(y)^2. r(y) runs r to zero as y runs zero to h, r(0) = r, r(h) = 0.

r(y) = r - r/h y

area(y) = π (r - r/h y)^2 = π (r^2 - 2r^2y/h + r^2y^2/h^2) = π r^2(1-2y/h+y^2/h^2)

antiderivative area(y) = π r^2 (y-y^2/h+y^3/(3h^2))

integral 0 to h = π r^2(h-h^2/h+h^3/(3h^2) - (0)) = π r^2(h - h + h/3) = π r^2(h/3) = π/3 r^2 h

volume of this cone is π/3(4^2)18 cubic inches.

= 6 16 π = 96π cubic inches.

cone has twice the volume, 96/48.

cone height is 6 times the cylinder.

ratio of volume formula: π r^2 cancels.

cone over cylinder ratio is 6h/3 to h, 2 to 1.

answer: your correct answer is b. d.

step-by-step explanation:

i think it would be c

mark brainliest if im right

step-by-step explanation: