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Ondrej Novak: Learning Convolutional Neural Networks for Age Estimation.
Master's thesis. Czech Technical University in Prague, Faculty of Information Technology, 2018.


Predictions

Jump to prediction examples

CNN model VGG16 architecture

See how to use saved model for predictions (download source ipynb file)

model-128x128x3-vgg.hdf5 (260.0 MiB, SHA-256 hash, visualization, layers summary)

Trained on Wikipeople, results on standard benchmarks, see thesis for detail.

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Proportion of samples with absolute deviation up to a certain threshold.

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True v. predicted age distribution.

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Distribution of age prediction error, absolute.

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Distribution of error, relative.

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Mean absolute error of age prediction per age and gender.

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Mean absolute error for positive and negative deviations separately.

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Test set results

for

model-128x128x3-vgg

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#Most monthly pageviews (men)
1Elon Musk11969012
2Pablo Escobar10422266
3Bill Paxton8374975
4Harvey Weinstein8340612
5Winston Churchill7788729
6Elvis Presley6597361
7Johnny Depp6158281
8Ryan Reynolds5788159
9Rafael Nadal5706966
10Hugh Jackman5401283
11The Undertaker5015332
12Brad Pitt4926225
13Chelsea Manning4806770
14Stephen King4500261
15Drake (musician)4430536
16Salman Khan4429387
17Bob Marley4315680
18Idris Elba4262447
19Jason Statham4228905
20Kurt Russell3904137
21Walt Disney3847050
22Kobe Bryant3779355
23Charlie Sheen3442947
24Bob Dylan3442617
25Wayne Rooney3375958
#Most monthly pageviews (women)
1Scarlett Johansson7107389
2Miley Cyrus5656505
3Jennifer Lopez5655912
4Marilyn Monroe5492037
5Priyanka Chopra4992078
6Nicki Minaj4442773
7Kristen Stewart4308554
8Goldie Hawn4260071
9Britney Spears3990997
10Zendaya3952314
11Rose Leslie3926589
12Tiffany Trump3654295
13Sophie Turner3647172
14Kirsten Dunst3180802
15Sarah Paulson3104470
16Nikki Bella3074762
17Felicity Jones2959805
18Laura Prepon2921736
19Khloé Kardashian2868780
20Jessica Chastain2847654
21Aaliyah2768054
22Lisa Marie Presley2761955
23Bryce Dallas Howard2760366
24Ronda Rousey2758038
25Jada Pinkett Smith2736780

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#Largest positive deviation (men)
1Peter Allam39
2Wayne Carleton38
3Orla Hyllested35
4George Macculloch Miller34
5Joseph S. Kozlowski33
6Erich Büttner (painter)33
7Glenn Hartranft32
8Jaap Mol32
9Mark Jansen31
10George C. Cox31
11Corrado Alvaro31
12Jimmy Armistead31
13George R. Stewart30
14Edmund Montgomery30
15Kelly Willie29
16Clare Magee29
17Scott Russell (tenor)28
18Herman Gesellius28
19Justin Boston28
20Sándor Bihari28
21Pat Trammell27
22Simon Rich27
23Egon Schweidler27
24Gordon Steege27
25Mick Shann27
#Largest positive deviation (women)
1Jan Taylor39
2Zulfiya Chinshanlo36
3Iris Tree30
4Marianne Vos30
5Alice Rohe29
6Caitlin Lowe28
7Milena Palakarkina27
8Rena Matsui27
9Heike Nagel26
10Rosemarie Gabriel26
11Jo Duffy25
12Sarah Cowell Le Moyne25
13Krissy Chin24
14Meta von Salis23
15La Tana23
16Taís Rochel23
17Elizabeth Meriwether22
18Dorian Gray (actress)22
19Jessica Nigri22
20Sofie Hagen22
21Virginia Haviland21
22Flora Eldershaw21
23Nikki Phillips (soccer)21
24Magaly Solier21
25Mree21

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#Largest negative deviation (men)
1Sergiu Celibidache-46
2Bob Giraldi-45
3Wacław Struszyński-44
4George Chan Hong Nam-44
5Petru Gherghel-41
6Bror Munck (born 1857)-41
7Rolf Gohs-40
8Ramon S. Subejano-39
9Jerzy Bartmiński-39
10Naoto Kan-38
11Ettore Bastico-38
12Thomas Jefferson Cowie-38
13Michael Martin Murphey-37
14Butch Warren-37
15Thilo Sarrazin-37
16John Jenkins (jazz musician)-35
17G. Flint Taylor-35
18Aaron Neville-34
19Christopher Stone (broadcaster)-33
20George Bell (basketball)-33
21Abdur-Raheem Adebayo Shittu-33
22Henry B. Metcalf-32
23Robbie Shakespeare-31
24Otto Kruger-31
25Charles Grodin-30
#Largest negative deviation (women)
1Eve Drewelowe-45
2Harriet Backer-44
3Frederikke Federspiel-38
4Kay Dian Kriz-38
5Christiana Herringham-37
6Phoebe Anna Traquair-36
7Elizabeth Kenny-34
8Julia Holmes Smith-34
9Ethel Ennis-33
10Valentina Tolkunova-33
11Marilla Ricker-33
12Marguerite de Witt-Schlumberger-33
13Françoise Sullivan-33
14Tania Maria-32
15Renate Bertlmann-32
16Victoria Puig de Lange-32
17Elizabeth Arden-30
18Martha Reeves-30
19Dorothee Wilms-30
20Lourdes Cirlot-30
21Phyllis Digby Morton-30
22Linda Coleman (North Carolina politician)-29
23Ernestine Carter-29
24Beulah Gundling-29
25Hattie Carnegie-28

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AgeAge-gender categoryTest samples
16 16-MF 16-M 16-F 54
17 17-MF 17-M 17-F 83
18 18-MF 18-M 18-F 149
19 19-MF 19-M 19-F 207
20 20-MF 20-M 20-F 273
21 21-MF 21-M 21-F 337
22 22-MF 22-M 22-F 426
23 23-MF 23-M 23-F 471
24 24-MF 24-M 24-F 498
25 25-MF 25-M 25-F 504
26 26-MF 26-M 26-F 509
27 27-MF 27-M 27-F 491
28 28-MF 28-M 28-F 474
29 29-MF 29-M 29-F 445
30 30-MF 30-M 30-F 436
31 31-MF 31-M 31-F 404
32 32-MF 32-M 32-F 380
33 33-MF 33-M 33-F 356
34 34-MF 34-M 34-F 326
35 35-MF 35-M 35-F 333
36 36-MF 36-M 36-F 294
37 37-MF 37-M 37-F 292
38 38-MF 38-M 38-F 277
39 39-MF 39-M 39-F 266
40 40-MF 40-M 40-F 274
41 41-MF 41-M 41-F 265
42 42-MF 42-M 42-F 261
43 43-MF 43-M 43-F 268
44 44-MF 44-M 44-F 248
45 45-MF 45-M 45-F 259
46 46-MF 46-M 46-F 263
47 47-MF 47-M 47-F 261
48 48-MF 48-M 48-F 260
49 49-MF 49-M 49-F 246
50 50-MF 50-M 50-F 250
51 51-MF 51-M 51-F 233
52 52-MF 52-M 52-F 240
53 53-MF 53-M 53-F 228
54 54-MF 54-M 54-F 208
55 55-MF 55-M 55-F 210
56 56-MF 56-M 56-F 207
57 57-MF 57-M 57-F 203
58 58-MF 58-M 58-F 200
59 59-MF 59-M 59-F 187
60 60-MF 60-M 60-F 191
61 61-MF 61-M 61-F 177
62 62-MF 62-M 62-F 170
63 63-MF 63-M 63-F 158
64 64-MF 64-M 64-F 150
65 65-MF 65-M 65-F 134
66 66-MF 66-M 66-F 127
67 67-MF 67-M 67-F 120
68 68-MF 68-M 68-F 115
69 69-MF 69-M 69-F 106
70 70-MF 70-M 70-F 107
71 71-MF 71-M 71-F 90
72 72-MF 72-M 72-F 80
73 73-MF 73-M 73-F 71
74 74-MF 74-M 74-F 73
75 75-MF 75-M 75-F 65

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