Shuai Wang1, Xianyi Chen2, *
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2065-2077, 2020, DOI:10.32604/cmc.2020.09857
- 16 September 2020
Abstract With the rapid development of computer technology, millions of images are
produced everyday by different sources. How to efficiently process these images and
accurately discern the scene in them becomes an important but tough task. In this paper,
we propose a novel supervised learning framework based on proposed adaptive binary
coding for scene classification. Specifically, we first extract some high-level features of
images under consideration based on available models trained on public datasets. Then,
we further design a binary encoding method called one-hot encoding to make the feature
representation more efficient. Benefiting from the proposed More >
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