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Can Synthetic Images Improve CNN Performance in Wound Image Classification?

, , , , , , , , , , , , , , and . MIE, volume 302 of Studies in Health Technology and Informatics, page 927-931. IOS Press, (2023)

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Receptive Field Refinement for Convolutional Neural Networks Reliably Improves Predictive Performance., and . CoRR, (2022)Continual Pre-Training of Large Language Models: How to (re)warm your model?, , , , , , , and . CoRR, (2023)Simple and Scalable Strategies to Continually Pre-train Large Language Models., , , , , , , and . CoRR, (2024)Towards efficient convolutional neural architecture design: exploring the properties of neural architectures using spectral decomposition and logistic regression probes.. University of Osnabrück, Germany, (2022)Feature Space Saturation during Training., , , , and . BMVC, page 17. BMVA Press, (2021)Spectral Analysis of Latent Representations., , , and . CoRR, (2019)Automatic Wound Type Classification with Convolutional Neural Networks., , , , , , , , , and 3 other author(s). ICIMTH, volume 295 of Studies in Health Technology and Informatics, page 281-284. IOS Press, (2022)Should You Go Deeper? Optimizing Convolutional Neural Network Architectures without Training by Receptive Field Analysis., , and . CoRR, (2021)An Image Based Object Recognition System for Wound Detection and Classification of Diabetic Foot and Venous Leg Ulcers., , , , , , , , , and 5 other author(s). MIE, volume 294 of Studies in Health Technology and Informatics, page 63-67. IOS Press, (2022)(Input) Size Matters for CNN Classifiers., , , , , and . ICANN (2), volume 12892 of Lecture Notes in Computer Science, page 133-144. Springer, (2021)