The polyps’ samples negative and positive classes of PolypGen dataset.

<p>The polyps’ samples negative and positive classes of PolypGen dataset.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Jun Tan (46388) (author)
مؤلفون آخرون:	Jiamin Yuan (10353958) (author), Xiaoyong Fu (482754) (author), Yilin Bai (13929663) (author)
منشور في:	2024
الموضوعات:	Biotechnology Cancer Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> among high death rate experimental results demonstrate scattering wavelet transform polyp classification technique correct classification rates visually categorizing polyps effectively classify polyps class polyp classification class experiment reached two public datasets scattering wavelet filters identify colorectal cancer end models based different lighting conditions commonly used cnns art cnn models proposed eswcnn method class classification wavelet filters proposed method colorectal cancer validation experiment six end designed based learnable filters classification accuracy video sequences various scales serrated polyps provide guidance previous works network architecture negative ). input channel hyperplastic polyps future research fold cross eswcnn ), efficacy compared common cancers best way average sensitivity 4 %,
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