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Published in 2019 at "International Journal of Automation and Computing"
DOI: 10.1007/s11633-019-1177-8
Abstract: Fine-grained image classification, which aims to distinguish images with subtle distinctions, is a challenging task for two main reasons: lack of sufficient training data for every class and difficulty in learning discriminative features for representation.…
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Keywords:
classification;
fine grained;
zero shot;
shot fine ... See more keywords
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Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3175798
Abstract: Few-shot fine-grained image classification aims to solve the learning problem with few limited labeled examples. The existing methods use data augmentation to randomly transform the original examples to get new examples, and then use the…
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Keywords:
view;
shot fine;
view metric;
classification ... See more keywords
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Published in 2025 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2024.3495533
Abstract: In few-shot fine-grained recognition (FS-FGR) tasks, the main challenge is to distinguish novel categories with high intra-class variations and low inter-class differences given scarce training data. Existing studies explore discriminative features through a compact network…
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Keywords:
recognition;
fine grained;
grained recognition;
visual descriptions ... See more keywords
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Published in 2025 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2024.3499937
Abstract: The main challenge for Few-Shot Fine-Grained (FSFG) image classification is to learn discriminative feature representations with few labeled samples. In response to this challenge, task-aware few-shot learning methods have been introduced. However, existing approaches focus…
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Keywords:
task;
shot;
fine grained;
task aware ... See more keywords
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Published in 2024 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2024.3411474
Abstract: Recent research on few-shot fine-grained image classification (FSFG) has predominantly focused on extracting discriminative features. The limited attention paid to the role of loss functions has resulted in weaker preservation of similarity relationships between query…
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Keywords:
fine grained;
loss;
grained image;
shot fine ... See more keywords
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Published in 2022 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2022.3167112
Abstract: One-shot fine-grained visual recognition often suffers from the problem of training data scarcity for new fine-grained classes. To alleviate this problem, off-the-shelf image generation techniques based on Generative Adversarial Networks (GANs) can potentially create additional…
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Keywords:
shot fine;
generated images;
one shot;
fine grained ... See more keywords