2021
DOI: 10.1007/s00521-021-05772-7
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Classification of thermal image of clinical burn based on incremental reinforcement learning

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Cited by 4 publications
(1 citation statement)
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“…Xiao and Zhao [18] simulated a perceptive network with 100 nodes deployed randomly. Huang et al [19] constructed a classification model of clinical burn thermal images based on machine learning algorithms. Gao et al [20] proposed a multi-granularity feature extraction (MGFE) method based on the gray-level co-occurrence matrix (GLCM) and random forest (RF).…”
mentioning
confidence: 99%
“…Xiao and Zhao [18] simulated a perceptive network with 100 nodes deployed randomly. Huang et al [19] constructed a classification model of clinical burn thermal images based on machine learning algorithms. Gao et al [20] proposed a multi-granularity feature extraction (MGFE) method based on the gray-level co-occurrence matrix (GLCM) and random forest (RF).…”
mentioning
confidence: 99%