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Image Captioning using Multiple Transformers for Self-Attention Mechanism by Olimov, Farrukh; Dubey, Shikha; Shrestha, Labina; Tin, Tran Trung; Jeon, Moongu is a scholarly article available to read on EtoBox.

What is Image Captioning using Multiple Transformers for Self-Attention Mechanism about?

Real-time image captioning, along with adequate precision, is the main challenge of this research field. The present work, Multiple Transformers for Self-Attention Mechanism (MTSM), utilizes multiple transformers to address these problems. The proposed algorithm, MTSM, acquires region proposals using a transformer detector (DETR). Consequently, MTSM achieves the self-attention mechanism by transferring these region proposals and their visual and geometrical features through another transformer and learns the objects' local and global interconnections. The qualitative and quantitative results of the proposed algorithm, MTSM, are shown on the MSCOCO dataset.

Author

Olimov, Farrukh; Dubey, Shikha; Shrestha, Labina; Tin, Tran Trung; Jeon, Moongu

Published

2021

Language

EN