Comment for Final Examination

Regrading Policy for the midterm exam

  1. Regrading request will be accepted in the format of resubmission of graded finals until 1pm, Thursday, December 19, 2002.  No exception.
  2. When you resubmit, please accompany extra sheets of paper where you type out reasons for regrading for specific quesions. No exception. (hand written request will be ignored.)
  3. Submit it to the TA mail box or to DEN.
  4. Please DO NOT contact TA or the professor in person or by email for regrading; the message will be ignored.
  5. Only for obvious mistake of the grader such as miscounting lost points.
  6. Only when you have explicitly stated the answers correctly but still lost point >= 5. (Please DO NOT argue "implied answers, etc.".)
    1. Please don't come for point loss less than 5
  7. Regrading will be done on the entire exam, which may reduce your grade. No exception.
  8. No argument against the grading standard given below.

Grading Standard for the final exam

1
d
genetic algorithm or random starting point (2)
e
depth - disparity; motion - aperture; object - view; visual - inform; scene - integrative (1)
f
PPC (2)
g
The origin moves with the first saccade (5)
h
look up when needed (3)
reason (1)

2
a
self-organization.(1)
one eye repels its own and attract the others.(2)
resource competition geographically splits neurons with simultaneous firing apart(3)
b
all columns in a hypercolum correspond to one visual field.(2)
each column processes different cue.(2)
cooperation and competition(2)
easy integration(2)
c
resource/work competition (3)
d
correct explanation of Ferromagnetism (4)

3
a
GEON definition (1)
Recognition by component (1)
Each property (1)
b
edges (3)
c
graphs (2)
missing matrix info (2)
boy&girl (indistinguishable) (2)
d
curvature of each facial feature isolated in a GEON (3)
relative sizes (3)
relative distribution of facial features isolated in a GEON (3)
e
specific (2)
general with learning (2)
general (1)

4
a
first order derivative (2)
second order derivative or inflection point (3)
b
noise reduction (3)
c
noise reduction and edge detection in one step. (3)
Gaussian and Laplacian in one step (restatement of the term itself) (2)
Two step to one step (2)
d
builtin population of filters with various scales (3)
e
a good example (3)

5
a one correct label (1)
b
i
Critic (2)
A or whatever you marked in that box (2)
ii
availability of direction and possibly amount to change (3)
answer reversed (1)
iii
yes (1)
meaning(2)
no(3)
c
i
additional/other feedback (3)
ii
assosiative (3)
iii
dashed input (3)
some good qualitative input (3)