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MMAT5390202021 - Shared screen with speaker view
Ka Lung CHAN
16:53
YES
Ho Renee TIN
16:56
yes
Chin Ting Timothy TSANG
16:56
yes
Chu Wing Suet
17:28
yes
Ka Lung CHAN
17:28
YES
Zhe CHEN
17:30
yes
James Tung
22:39
what is tr?
Ho Renee TIN
23:27
yes
James Tung
23:47
ok
Ka Lung CHAN
25:01
YES
Zhe CHEN
25:04
yes
Chu Wing Suet
25:04
yes
James Tung
25:05
yes
Ho Renee TIN
26:10
yes
Ka Lung CHAN
26:10
yes
James Tung
26:12
no
Ray JIN
26:16
yes
Ho Renee TIN
26:34
the col vector of the matrix is orthonormal
James Tung
27:17
ok
Ho Renee TIN
31:23
yes
Zhe CHEN
31:27
yes
James Tung
31:27
yes
Chin Ting Timothy TSANG
31:29
yes
Kwong Ming KWOK
31:30
yes
Chu Wing Suet
31:31
yes
Zhe CHEN
33:49
yes
Ho Renee TIN
33:50
yes
Chin Ting Timothy TSANG
33:51
yes
Ho Renee TIN
36:30
yes
James Tung
36:31
yes
Chu Wing Suet
36:31
yes
Chin Ting Timothy TSANG
36:36
yes
Ka Lung CHAN
36:36
YES
Ka Lung CHAN
38:34
YES
Ray JIN
38:34
yes
Ho Renee TIN
38:34
yes
Jin QIAN
38:37
yes
Yulin LI
38:39
yes
Ho Renee TIN
40:55
ok
Zhe CHEN
40:56
yes
Ho Renee TIN
42:51
yes
Ka Lung CHAN
42:52
YES
Zhe CHEN
42:52
yes
Kwong Ming KWOK
42:54
yes
Chin Ting Timothy TSANG
43:03
me
Ray JIN
43:17
we have learned in term1==
Ho Renee TIN
43:31
yes
James Tung
47:14
I haven't
Chin Ting Timothy TSANG
47:16
me
Ka Lam LEE
47:18
me
Wing Sze TAM
47:19
me
James Tung
53:43
yes
Chin Ting Timothy TSANG
53:44
yes
Ka Lung CHAN
53:45
yes
Ho Renee TIN
01:02:04
Sorry to interrupt. Do we seldom use reduced SVD in image processing? (Although it spend less memory for storage and some computation steps?)Because we mainly focus on the singular values?
Ho Renee TIN
01:02:58
the sigma is n byn
Ho Renee TIN
01:03:09
and U m by n
Ho Renee TIN
01:05:05
but we still have to compute the m-n orthonormal vecto in U that reduced SVD do not need to compute
Ka Lung CHAN
01:05:33
with the singular value ordered in descending order?
Ho Renee TIN
01:05:36
I understand the part for lowering the rank
Ka Lung CHAN
01:06:19
YES?
Ho Renee TIN
01:06:20
but it only associate with the zero value
Ho Renee TIN
01:06:21
ok
Ho Renee TIN
01:06:24
thank you
Ho Renee TIN
01:07:04
ohhhhhh
Ho Renee TIN
01:07:26
that's interesting
Ho Renee TIN
01:08:06
yes
Ho Renee TIN
01:09:50
yes
Ka Lung CHAN
01:09:54
yes
Chin Ting Timothy TSANG
01:10:39
can we use matlab in the exam?
Ka Lung CHAN
01:10:40
do we need to order the eigenvector and eigenvalue or just in any order?
James Tung
01:13:46
if we reĀ­-order the eigenvectors and eigenvalues, would we mess up the image?
James Tung
01:15:57
ok
Zhe CHEN
01:20:28
yes
Chu Wing Suet
01:20:31
yes
James Tung
01:20:34
yes
Chu Wing Suet
01:21:34
yes
Zhe CHEN
01:21:38
ok
Ho Renee TIN
01:21:41
yes
Ka Lung CHAN
01:26:33
Yes for me
Zhe CHEN
01:26:36
ok
James Tung
01:26:40
yes
JIAJI LIN
01:26:46
ok
Ho Renee TIN
01:30:22
yes
Ka Lung CHAN
01:30:31
yes
Ka Lung CHAN
01:31:39
yes
James Tung
01:31:48
Can you explain the red text again?
JIAJI LIN
01:31:50
not ui ui
Ka Lam LEE
01:31:51
Yes
James Tung
01:33:35
M1 is the fist column of lambda?
James Tung
01:34:09
okok
JIAJI LIN
01:34:11
yes confusing haha
James Tung
01:34:21
ok
JIAJI LIN
01:34:28
OK
James Tung
01:35:00
yes
James Tung
01:37:58
yes
Ray JIN
01:37:58
yes
JIAJI LIN
01:37:58
no problem
Ho Renee TIN
01:42:55
okMay I know what kind of image associate with high rank?
Ho Renee TIN
01:44:01
Thank you
Ka Lung CHAN
01:44:14
ok
Ray JIN
01:44:16
yes
Zhe CHEN
01:44:19
ok
Ka Lam LEE
01:44:44
yes
Ka Lung CHAN
01:44:45
YES
Chu Wing Suet
01:44:46
yes
Ho Renee TIN
01:44:47
yes
Zhe CHEN
01:44:47
yes
Ho Renee TIN
01:55:48
yes
Ka Lung CHAN
02:03:39
YES
Ho Renee TIN
02:03:39
yes
Daixi HONG
02:03:40
ok
Zhe CHEN
02:03:41
yes
Ka Lung CHAN
02:19:01
YES
Ka Lung CHAN
02:19:25
YES
James Tung
02:24:46
what about uj and vj?
Ka Lung CHAN
02:24:47
yes
Ho Renee TIN
02:24:55
ok
James Tung
02:25:59
I mean how come the summation does not include uj and vj
Zhe CHEN
02:25:59
yes
James Tung
02:26:40
okok
Chu Wing Suet
02:26:57
yes
Ray JIN
02:27:15
yes
Wing Sze TAM
02:27:15
yes
Ka Lung CHAN
02:30:34
yes
Ho Renee TIN
02:30:36
yes
Ray JIN
02:30:36
Yes
James Tung
02:30:36
yes
Chu Wing Suet
02:30:38
yes
James Tung
02:35:33
1
Ho Renee TIN
02:35:33
square of 2 norm
Ho Renee TIN
02:35:36
1
Ho Renee TIN
02:35:47
orthonormal
Ka Lung CHAN
02:36:06
Yes
JIAJI LIN
02:36:25
0
Ray JIN
02:36:26
0
James Tung
02:37:09
ok
James Tung
02:37:11
yes
Ka Lung CHAN
02:40:14
lose of digit?
Ho Renee TIN
02:42:46
ok
Ka Lung CHAN
02:42:47
yes
Chin Ting Timothy TSANG
02:42:51
yes
Ho Renee TIN
02:49:13
yes
Ka Lung CHAN
02:49:14
YES
Chu Wing Suet
02:49:16
yes
Zhe CHEN
02:49:16
yes
Jin QIAN
02:50:05
thx
Ka Lam LEE
02:50:10
thanks
James Tung
02:50:11
Thank you
Ronald LUI
02:50:13
Thank you very much for attending the lecture.
Ka Lung CHAN
02:50:14
Thank you
Chin Ting Timothy TSANG
02:50:15
thank you and goodbye
Daixi HONG
02:50:16
thanks
Ho Renee TIN
02:50:31
Thank you and I am sorry to ask too much questions and affecting the lesson's schedule
Chu Wing Suet
02:50:31
thank you
JIAJI LIN
02:50:32
thank you and good night
Jufen CHEN
02:50:32
thanks
Ho Renee TIN
02:50:35
good night