African WildLife Classification

Get ready to rumble with machine learning in the Wildest Contest of the Semester! Your mission: build a model that can distinguish between the fabulous four of African wildlife—Buffalo, Elephant, Rhino, and Zebra. This Machine Learning Safari meets Creature Classification Challenge runs weekly, with submissions evaluated every Friday at 5pm. So, forget the intimidation from whoever is currently king (or queen) of the AI jungle on the leaderboard. The only way to win this mane event is to git your models in gear and submit!
Ranking Procedure
  • 100 points for completing all steps.
  • 75 points for completing 3 steps.
  • 50 points for completing 2 steps.
  • 25 points for completing 1 step.
  • 0 points for completing 0 steps.
Legend:
A (90%-100%)
B (80%-89%)
C (70%-79%)
D (60%-69%)
E (50%-59%)
F (<50%)
Leaderboard
Contest Details
Submission

Leaderboard

Last updated:

RankNameDepartmentMarks
1
Gop Manyuon kodiComputer Science
100.00%
2
Reeng Kuol ReengInformation Technology
100.00%
3
MOSES LUWALLA WANI NYIGILOInformation Technology
100.00%
4
Nelson Makim AterComputer Science
100.00%
5
Simon Mading AyolComputer Science
100.00%
6
Abraham Dit ManyangInformation Technology
100.00%
7
AYATH AGANY AYATHComputer Science
100.00%
8
Emmanuel Deng MeiComputer Science
100.00%
9
MOU MOU BAKComputer Science
100.00%
10
Deng Kuol Ajak DengComputer Science
100.00%
11
MAWIEN GUET AYIIComputer Science
100.00%
12
Athou Rebecca AjakComputer Science
100.00%
13
mary ojinio lako tombeComputer Science
100.00%
14
Jacob Dau DengComputer Science
100.00%
15
DUOT DENG AJANGComputer Science
100.00%
16
Mawien Tito Ariik TobyInformation Technology
100.00%
17
KUOT JOOL ALUEL DENGComputer Science
100.00%
18
Malish Ben KenyiComputer Science
100.00%
19
Nesnea khadi silvanoComputer Science
100.00%
20
Dominic Paulino OmerComputer Science
100.00%
21
Franco Komma James OgawiComputer Science
100.00%
22
Maxim Edwin Zozimo OgoComputer Science
100.00%
23
Andrew Akuei Atem ManyuonComputer Science
100.00%
24
Christina Adhar MonyjiithComputer Science
100.00%
25
Monica Ayen BolComputer Science
100.00%
26
Mangar makur MachiekInformation Technology
100.00%
27
David Akech Ayor NgongComputer Science
100.00%
28
Peter Arol AwanComputer Science
100.00%
29
Yai simon cholComputer Science
100.00%
30
Alek Garang TorComputer Science
100.00%
31
Jenty jore TheophiluComputer Science
100.00%
32
Deng Dut MayenComputer Science
100.00%
33
Emmanuel Khamis Victor LoyaComputer Science
100.00%
34
Garang Yai GarangComputer Science
100.00%
35
James Dut MathokInformation Technology
100.00%
36
Samuel Jada TombeComputer Science
100.00%
37
Samuel thongbor makethComputer Science
100.00%
38
Edina Yeno JamesComputer Science
100.00%
39
Edmond Anthony MesagaInformation Technology
100.00%
40
Marko Agany KuicComputer Science
100.00%
41
Atem Khor DengComputer Science
100.00%
42
Adam Juma HaruunInformation Technology
100.00%
43
Abraham Ariik MakerComputer Science
100.00%
44
BIET PUORIC MATUONGComputer Science
100.00%
45
YOUSIF JOHN MICHAELComputer Science
100.00%
46
Malong Nuoi Malong AbeiComputer Science
100.00%
47
Deng Zakaria MachComputer Science
100.00%
48
Bol Monica AyuenComputer Science
100.00%
49
Samuel Maker MangarComputer Science
100.00%
50
Mapath Samuel AjithComputer Science
100.00%
51
Emilio Albert ApaiComputer Science
100.00%
52
Betty Juru Patrick WunyiComputer Science
100.00%
53
Deng Kuur NhialComputer Science
100.00%
54
Kuot Chol MajokInformation Technology
100.00%
55
Marko Ngor Wek WekInformation Technology
100.00%
56
Yai Thon NyokComputer Science
100.00%
57
Rhok Longar AkueiComputer Science
100.00%
58
Chris Khamis BobonoComputer Science
100.00%
59
AJACK GUET KUOLComputer Science
100.00%
60
Suzan Adut marialComputer Science
100.00%
61
Agar Marial Riak AtuongtokComputer Science
100.00%
62
Winny poni ErestoComputer Science
0.00%
63
Lomude Charles JamesComputer Science
0.00%
64
Lual dot WieuComputer Science
0.00%
65
James machar makurComputer Science
0.00%
66
John Boush MayiekComputer Science
0.00%
67
Abraham Madit KurComputer Science
0.00%
68
Panom Chot JalComputer Science
0.00%
69
Daniel Clement LejuComputer Science
0.00%
70
Alfred Malek MaborComputer Science
0.00%
71
Bakhita Malek Tong DutComputer Science
0.00%
72
Deng Deng MadutComputer Science
0.00%
73
Dhel Malith CholComputer Science
0.00%
74
George Morbe MikeComputer Science
0.00%
75
Godfrey Lino ArkangeloComputer Science
0.00%
76
Awut Deng AguerComputer Science
0.00%
77
Michael Atem CholComputer Science
0.00%
78
Joseph chol MagaiComputer Science
0.00%
79
Loi Emmanuel TongComputer Science
0.00%
80
Magisto Ohisa LukaComputer Science
0.00%
81
Mary Adut Achiek AruComputer Science
0.00%
82
Stephan Jansuk Jolius YengiComputer Science
0.00%
83
Thomas TODOKO SamuelComputer Science
0.00%
84
Peter Akok NgorComputer Science
0.00%

Challenge Description

As a participant, you are tasked with developing a machine learning model that can accurately classify images of African wildlife into one of four categories:

  • Buffalo
  • Elephant
  • Rhino
  • Zebra

Dataset

The contest provides a dataset split into three parts:

  • Training set: 1,049 labeled images (at least 254 per class)
  • Validation set: 1,000 labeled images (at least 51 per class)
  • Test set: Held-out by instructor for evaluating algorith

All images are 128x128x3 pixels in JPEG format. The dataset includes various lighting conditions, angles, and backgrounds to challenge participants' models. Samples from the dataset are shown below.

Starter Code

Participants can use the following starter code and data to begin their projects:

Rules

  • No teams allowed - individual effort.
  • No modification of the CNN architecture allowed.
  • No external datasets allowed.
  • No pre-trained models allowed.

Submission Instructions

To submit your model for evaluation:

  1. Prepare your model file (saved your model when training)
  2. Create a README file with:
    • Your name, index, and department
    • Brief description of your approach
    • Any special instructions for running your code
  3. Create a Google Drive folder and make sure it is shared with uojdeeplearning@gmail.com
  4. Put all your project files in Google Driver you shared above (code, saved model, readme file)

Evaluation Schedule

Submissions will be evaluated weekly. Results will be posted on the leaderboard by Monday at noon.