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🧡 Cool Guy 🧡
⚡⚡ Let’s be friends for future games ⚡⚡
🌟🌟 Have a wonderful year🌟🌟
💫💫 Stay safe & take care💫💫
🔥🔥🔥+REP The profile is fire 🔥🔥🔥
════════════🔱🔱🔱🔱🔱🔱═════════════
If you're a beautiful strong black woman, someone will put this in your comments.
╚═══════════════════ ೋღ☃ღೋ ═══════════════════╝
◄☢️●▬▬▬▬~ஜ۩۞۩ஜ~▬▬▬▬▬●☢️►
Friendly Guy !!! ❤️
We can be friends for future games ^_^
✅✅✅+REP Good Player
✅✅✅+REP Good Friend
✅✅✅+REP Nice profile
✅✅✅+REP Have a nice day !
◄☢️●▬▬▬▬~ஜ۩۞۩ஜ~▬▬▬▬▬●☢️►
◄☢️●▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬●☢️►
🌟 +REPUTATION SIR<333!🌟
𝓕𝓻𝓲𝓮𝓷𝓭𝓵𝔂 𝓰𝓾𝔂=)
𝓦𝓮 𝓬𝓪𝓷 𝓫𝓮 𝓯𝓻𝓲𝓮𝓷𝓭𝓼 𝓯𝓸𝓻 𝓯𝓾𝓽𝓾𝓻𝓮 𝓰𝓪𝓶𝓮𝓼^_^
═════════════════ஜ۩۞۩ஜ═══════════════════
absence) of one of the following landmark monuments: 1) the Sydney Opera House, or 2) the
Eiffel Tower (in Paris), in an input RGB image. In other words, the task is to develop a
classification algorithm that classifies an input image into one of the three classes: 1) The image
contains the Sydney Opera House, 2) The image contains the Eiffel Tower, 0) The image does
not contain either of those monuments.
You are provided with a few sample images of occurrences of those monuments (see below), as
examples. However, you can complement your development dataset as you see fit.
You should develop your system so that it reaches high accuracy of recognition on your own
validation dataset, and then on new images never seen before. Consider that the images you
will need to apply your classification algorithm on can be of varying qualities.