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Deep Learning Approaches Based on Transformer Architectures for Image Captioning Tasks

https://doi.org/10.1109/access.2022.3161428
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-89941-7_13openalex-snapshot
Hyperparameter Tuning over an Attention Model for Image Captioning
inferredcites →https://doi.org/10.1007/978-3-319-10602-1_48openalex-snapshot
Microsoft COCO: Common Objects in Context
inferredcites →https://doi.org/10.1016/j.eswa.2020.113967openalex-snapshot
Analysis of factors that influence the performance of biometric systems based on EEG signals
inferredcites →https://doi.org/10.1016/j.proeng.2015.01.404openalex-snapshot
Industrial Image Processing Using Fuzzy-logic
inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvpr.2015.7298878openalex-snapshot
Long-term recurrent convolutional networks for visual recognition and description
inferredcites →https://doi.org/10.1109/cvpr.2015.7298935openalex-snapshot
Show and tell: A neural image caption generator
inferredcites →https://doi.org/10.1109/cvpr.2016.503openalex-snapshot
Image Captioning with Semantic Attention
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.131openalex-snapshot
Self-Critical Sequence Training for Image Captioning
inferredcites →https://doi.org/10.1109/lcomm.2020.2982887openalex-snapshot
Machine Learning to Improve Multi-Hop Searching and Extended Wireless Reachability in V2X
inferredcites →https://doi.org/10.1109/spin.2015.7095350openalex-snapshot
Leaf disease detection and grading using computer vision technology & fuzzy logic
inferredcites →https://doi.org/10.1109/tpami.2012.162openalex-snapshot
BabyTalk: Understanding and Generating Simple Image Descriptions
inferredcites →https://doi.org/10.1145/3422668openalex-snapshot
Chinese Image Captioning via Fuzzy Attention-based DenseNet-BiLSTM
inferredcites →https://doi.org/10.1162/neco.1997.9.8.1735openalex-snapshot
Long Short-Term Memory
inferredcites →https://doi.org/10.1609/aaai.v34i07.7005openalex-snapshot
Unified Vision-Language Pre-Training for Image Captioning and VQA
inferredcites →https://doi.org/10.3390/sym12121939openalex-snapshot
Applying a Hybrid Sequential Model to Chinese Sentence Correction
inferredcites →https://doi.org/10.4230/lipics.cosit.2022.18openalex-snapshot
AI-Assisted Pipeline for Dynamic Generation of Trustworthy Health Supplement Content at Scale
inferredcites →https://doi.org/10.48550/arxiv.1412.6632openalex-snapshot
Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN)
inferredcites →https://doi.org/10.48550/arxiv.1412.7755openalex-snapshot
Multiple Object Recognition with Visual Attention
inferredcites →https://doi.org/10.48550/arxiv.1909.02279openalex-snapshot
Accelerating Transformer Decoding via a Hybrid of Self-attention and Recurrent Neural Network
inferredcites →https://doi.org/10.48550/arxiv.2101.10804openalex-snapshot
CPTR: Full Transformer Network for Image Captioning
inferredcites →https://doi.org/10.5772/4960openalex-snapshot
An Overview of Advances of Pattern Recognition Systems in Computer Vision

What points at this work

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Image Captioning for Nantong Blue Calico Through Stacked Local-Global Channel Attention Network
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VGGIN-Net–Transformer: Multimodal Encoder-Decoder Framework for Semantic Image Captioning
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Bridging Visual Understanding and Language Generation: A Deep Learning Approach to Image Captioning
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ViT-BART: A Vision-Text Fusion Model for Image Caption Generation
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Synergizing VGG16 Convolutional Features with LSTM Architectures for Image Captioning Mastery
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Fusion of Computer Vision and Natural Language Processing: Automated Image Caption Generation
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