DataHour: Feature Engineering on Images using Convolutional Neural Networks(CNN)

DataHour: Feature Engineering on Images using Convolutional Neural Networks(CNN)

22 Jul 202213:07pm - 22 Jul 202214:07pm

DataHour: Feature Engineering on Images using Convolutional Neural Networks(CNN)

About the Event

Convolutional Neural Networks constitute a way to represent abstract features in different kinds of data samples, mainly images. CNNs mimic the behavior of human and animal brains, setting up a complex hierarchy of interpretative neuronal layers and other elements that lend a more robust set of features for distinguishing objects and characteristics present on images. With this new information added before the basic dense neuronal layers, we can develop highly accurate classification and object detection Machine Learning models for images.

In this DataHour, CNNs basic concepts will be explained, and some examples will be covered using Python and Tensorflow/Keras. Besides, some state of the art architectures will be described, as well as the possibilities of using them in software development. 

Prerequisites: Enthusiasm for learning Deep Learning and basic knowledge of Python.

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Who is this DataHour for?

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About the Speaker

Eduardo Xamena

Eduardo Xamena

Scientific Researcher at National Scientific and Technical Council (CONICET)

Eduardo has done PhD in Computer Science, on the subject of structural analysis of mathematical models from chemical engineering and relevance propagation in topical networks. Currently, Scientific Researcher working on the development of methodologies and architectures for information retrieval and extraction over large volumes of text. The application fields covered with such tools are the Argentinian revolution history and the volume of complaints of the Public Ministry of Salta (Argentina). Carrying on tasks of text cleaning in OCR acquired volumes, and building representations of text suitable for classification procedures. Besides, he’s working on Deep Learning applied to Image processing tasks, including Handwritten Text recognition. Currently, he’s also a professor in Computer Vision and Data Science chairs.You can follow him on Linkedin and Twitter.

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