Search results for "Convolutional Neural Network"

Photo of a dog at the beach.

How to Develop a Deep Learning Photo Caption Generator from Scratch

Develop a Deep Learning Model to Automatically Describe Photographs in Python with Keras, Step-by-Step. Caption generation is a challenging artificial intelligence problem where a textual description must be generated for a given photograph. It requires both methods from computer vision to understand the content of the image and a language model from the field of […]

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Phillip Island Penguin Parade

A Gentle Introduction to Channels-First and Channels-Last Image Formats

Color images have height, width, and color channel dimensions. When represented as three-dimensional arrays, the channel dimension for the image data is last by default, but may be moved to be the first dimension, often for performance-tuning reasons. The use of these two “channel ordering formats” and preparing data to meet a specific preferred channel […]

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Line Plot Learning Curves of Model Accuracy on Train and Test Dataset Over Each Training Epoch

How to Develop an Ensemble of Deep Learning Models in Keras

Deep learning neural network models are highly flexible nonlinear algorithms capable of learning a near infinite number of mapping functions. A frustration with this flexibility is the high variance in a final model. The same neural network model trained on the same dataset may find one of many different possible “good enough” solutions each time […]

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Scatter Plot of Circles Dataset with Color Showing the Class Value of Each Sample

How to Reduce Generalization Error With Activity Regularization in Keras

Activity regularization provides an approach to encourage a neural network to learn sparse features or internal representations of raw observations. It is common to seek sparse learned representations in autoencoders, called sparse autoencoders, and in encoder-decoder models, although the approach can also be used generally to reduce overfitting and improve a model’s ability to generalize […]

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Sliding Window Approach to Modeling Time Series

LSTM Model Architecture for Rare Event Time Series Forecasting

Time series forecasting with LSTMs directly has shown little success. This is surprising as neural networks are known to be able to learn complex non-linear relationships and the LSTM is perhaps the most successful type of recurrent neural network that is capable of directly supporting multivariate sequence prediction problems. A recent study performed at Uber […]

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Encoder-Decoder Models for Text Summarization in Keras

Encoder-Decoder Models for Text Summarization in Keras

Text summarization is a problem in natural language processing of creating a short, accurate, and fluent summary of a source document. The Encoder-Decoder recurrent neural network architecture developed for machine translation has proven effective when applied to the problem of text summarization. It can be difficult to apply this architecture in the Keras deep learning […]

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How to Use Small Experiments to Develop a Caption Generation Model in Keras

How to Use Small Experiments to Develop a Caption Generation Model in Keras

Caption generation is a challenging artificial intelligence problem where a textual description must be generated for a photograph. It requires both methods from computer vision to understand the content of the image and a language model from the field of natural language processing to turn the understanding of the image into words in the right […]

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Model 3 - Generate Word From Sequence

A Gentle Introduction to Deep Learning Caption Generation Models

Caption generation is the challenging artificial intelligence problem of generating a human-readable textual description given a photograph. It requires both image understanding from the domain of computer vision and a language model from the field of natural language processing. It is important to consider and test multiple ways to frame a given predictive modeling problem […]

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