[PDF][PDF] Author profiling from images using 3d convolutional neural networks
2019•ceur-ws.org
With this work we participate in the competition on the author profiling task on the MEX-A3T
track at IberEval 2019. Author profiling task aims to identify gender, occupation and location
from images or text of Mexican Twitter users. We propose a 3D Convolutional Neural
Network for solving this task, using visual information, in this case images extracted from the
user's profile which are grouped to create a unique input of each user.
track at IberEval 2019. Author profiling task aims to identify gender, occupation and location
from images or text of Mexican Twitter users. We propose a 3D Convolutional Neural
Network for solving this task, using visual information, in this case images extracted from the
user's profile which are grouped to create a unique input of each user.
Abstract
With this work we participate in the competition on the author profiling task on the MEX-A3T track at IberEval 2019. Author profiling task aims to identify gender, occupation and location from images or text of Mexican Twitter users. We propose a 3D Convolutional Neural Network for solving this task, using visual information, in this case images extracted from the user’s profile which are grouped to create a unique input of each user.
ceur-ws.org
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