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- W4320153977 abstract "A picture can represent thousands of words. This proverb is indeed true. What can’t be described in words can be conveyed by images almost effortlessly and effectively. This paper aims at providing a framework that can help generate descriptions of images. Automatically describing an image is a problem that falls under both the fields of computer vision and natural language processing. This problem applies to virtual assistants for indexing images, editing tools, and disabled people’s support. Its difficulties stem from the ambiguity and diversity of possible descriptions of a picture because people can describe an image from various angles. We used deep learning techniques like Convolutional Neural Network combined with long short-term memory (LSTM). We have trained the model using the dataset Flicker8K and then evaluated our model using standard metrics, which are the BLEU-1 metric. The experimental results provide comparable results to the standard." @default.
- W4320153977 created "2023-02-13" @default.
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- W4320153977 date "2022-01-01" @default.
- W4320153977 modified "2023-09-27" @default.
- W4320153977 title "Automatic Image Captioning Using Ensemble of Deep Learning Techniques" @default.
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- W4320153977 doi "https://doi.org/10.1007/978-3-031-23724-9_38" @default.
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