In this chapter, we introduced the problem of semantic segmentation and implemented U-Net: a deep encoder-decoder architecture used to tackle this problem. A short introduction about the possible use cases and the challenges this problem poses has been presented, followed by an intuitive introduction of the deconvolution (transposed convolution) operation, used to build the decoder part of the architecture. Since, at the time of writing, there is not a dataset for semantic segmentation that's ready to use in TensorFlow Datasets, we took the advantage of this to show the architecture of TensorFlow Datasets and show how to implement a custom DatasetBuilder. Implementing it is straightforward, and it is something that's recommended to every TensorFlow user since it is a handy way of creating a high-efficiency data input pipeline (tf.data.Dataset). Moreover, by implementing...
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You're reading from Hands-On Neural Networks with TensorFlow 2.0
Paolo Galeone is a computer engineer with strong practical experience. After getting his MSc degree, he joined the Computer Vision Laboratory at the University of Bologna, Italy, as a research fellow, where he improved his computer vision and machine learning knowledge working on a broad range of research topics. Currently, he leads the Computer Vision and Machine Learning laboratory at ZURU Tech, Italy.
In 2019, Google recognized his expertise by awarding him the title of Google Developer Expert (GDE) in Machine Learning. As a GDE, he shares his passion for machine learning and the TensorFlow framework by blogging, speaking at conferences, contributing to open-source projects, and answering questions on Stack Overflow.
Read more about Paolo Galeone
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Paolo Galeone is a computer engineer with strong practical experience. After getting his MSc degree, he joined the Computer Vision Laboratory at the University of Bologna, Italy, as a research fellow, where he improved his computer vision and machine learning knowledge working on a broad range of research topics. Currently, he leads the Computer Vision and Machine Learning laboratory at ZURU Tech, Italy.
In 2019, Google recognized his expertise by awarding him the title of Google Developer Expert (GDE) in Machine Learning. As a GDE, he shares his passion for machine learning and the TensorFlow framework by blogging, speaking at conferences, contributing to open-source projects, and answering questions on Stack Overflow.
Read more about Paolo Galeone