Zhaowei Qu1,*, Bingyu Cao1, Xiaoru Wang1, Fu Li2, Peirong Xu1, Luhan Zhang1
CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 575-589, 2019, DOI:10.32604/cmc.2019.05569
Abstract Images are complex multimedia data which contain rich semantic information. Most of current image description generator algorithms only generate plain description, with the lack of distinction between primary and secondary object, leading to insufficient high-level semantic and accuracy under public evaluation criteria. The major issue is the lack of effective network on high-level semantic sentences generation, which contains detailed description for motion and state of the principal object. To address the issue, this paper proposes the Attention-based Feedback Long Short-Term Memory Network (AFLN). Based on existing codec framework, there are two independent sub tasks in our method: attention-based feedback LSTM… More >
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