TR U IN G DAI HOC SU' PHAM KY THUAT
t h An h ph 6 h o c h i' m in h
KHOA CO KHI CHE TAO MAY
BO MON CO DIEN TU”
BE THI CUOI KY HK I NAM HOC 2019-2020
Mon: XU LY ANH CONG NGHIfiP
Ma mon hoc: IIPR422529
Be so: 01 Be thi co 02 trang
Ngaythi: 16/12/2019
Thai gian: 75 phut.
Buoc phep sir dung tai lieu giay
Cau 1: (2d)
Xay dung va cai dat thuat toan lam tang do net cua anh bang mat na Laplace. (2d)
Tai sao mat na Laplace lai lam tang do net cua anh? (0.5d)
Cau 2: (3d)
Xay dung va cai dat thuat toan loai bo cac hat gao nho hon 90% hat gao Ion nhdt, tire la
trong anh chi con lai tihung hat gao ldn.
Can 3: (3d)
Ta dinli nghia mang no-ron chap dung de nhan dang 10 chu so viet tay co kich thuoc 28x28
nhu sau:
def build(input_shape, classes):
model = Sequential)
# corn => RELU => POOL
model.add(Conv2D(20, kernel_size=5, padding="same",
input_shape=input_shape))
model. add(Activation("relu"))
model.add(M’axPooling2D(pool _size~-(2, 2), strides=(2, 2)))
# CONV => RELU => POOL
model.add(Conv2D(50, kernel_sizer-5, padding="same"))
model. add( Act i vati on (" re 1 u"))
model.add(MaxPooling2D(pool__size~(2, 2), strides= (2. 2)))
H Flatten => R£LU layers
,i n o d e 1. a d d (F1 a t ten ())
model. add(Den.se( 5 Of)))
mode! add(Aoiivation(v'reIn"))
A a soltmax classifier
model ,add( Dense(classes))
model. add(Activation("softmax'’))
S3 hicu- B M 1 /QT- PDBCL-RDTV Tranu 1/2
