بدائل البحث:
process optimization » model optimization (توسيع البحث)
wolf optimization » whale optimization (توسيع البحث), swarm optimization (توسيع البحث), _ optimization (توسيع البحث)
model process » modeling process (توسيع البحث), model proposes (توسيع البحث), model proteins (توسيع البحث)
binary edge » binary image (توسيع البحث)
tiny » ting (توسيع البحث), tina (توسيع البحث), tony (توسيع البحث)
process optimization » model optimization (توسيع البحث)
wolf optimization » whale optimization (توسيع البحث), swarm optimization (توسيع البحث), _ optimization (توسيع البحث)
model process » modeling process (توسيع البحث), model proposes (توسيع البحث), model proteins (توسيع البحث)
binary edge » binary image (توسيع البحث)
tiny » ting (توسيع البحث), tina (توسيع البحث), tony (توسيع البحث)
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1
Differences between models of different scales.
منشور في 2024"…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …"
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2
LC-FPN structure.
منشور في 2024"…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …"
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3
Labeling information of the VisDrone dataset.
منشور في 2024"…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …"
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4
LFERELAN structure.
منشور في 2024"…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …"
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5
The experimental environment.
منشور في 2024"…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …"
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6
LCFF-Net network structure.
منشور في 2024"…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …"
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7
LDSCD-Head structure.
منشور في 2024"…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …"
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8
Ablation experiment result on VisDrone-val.
منشور في 2024"…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …"
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9
The key parameter configurations.
منشور في 2024"…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …"
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10
LR-NET structure.
منشور في 2024"…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …"
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11
Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf
منشور في 2024"…Next, a hybrid feature extraction approach is presented leveraging transfer learning from selected deep neural network models, InceptionV3 and DenseNet201, to extract comprehensive feature sets. To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …"