This paper proposes a novel lesion-localization convolution transformer (LLCT) method, which combines both convolution and self-attention to classify ophthalmic ...
Towards more efficient ophthalmic disease classification and lesion ...
pubmed.ncbi.nlm.nih.gov › ...
Apr 27, 2022 · This paper proposes a novel lesion-localization convolution transformer (LLCT) method, which combines both convolution and self-attention to classify ...
This paper proposes a novel lesion-localization convolution transformer (LLCT) method, which combines both convolution and self-attention to classify ophthalmic ...
Towards more efficient ophthalmic disease classification and lesion location via convolution transformer ... Authors: Huajie Wen; Jian Zhao; Shaohua Xiang; Lin ...
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Mar 3, 2023 · It combines both convolution and self-attention to classify ophthalmic diseases and localize the retinal lesions. This design takes advantage of ...
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Feb 23, 2024 · ... Towards more efficient ophthalmic disease classification and lesion location via convolution transformer Comput Methods Progr Biomed 2022 220 ...
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Towards more efficient ophthalmic disease classification and lesion location via convolution transformer. Computer Methods and Programs in Biomedicine, 220 ...
Jun 18, 2024 · We show that, by combining the strengths of Convolutional Neural Networks (CNNs) and Visual Transformers (ViTs), we can produce a more powerful ...