Sepsirisuk, Kasemsuk

Loading...
Thumbnail Image
Preferred name
Sepsirisuk, Kasemsuk
Main Affiliation
Email
kasemsuk.se@kmitl.ac.th

Settings

Now showing 1 - 2 of 2
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Banana Plant Nutrient Deficiencies Identification using Deep Learning
    (2023-01-01)
    Han, Kadipa Aung Myo
    ;
    Maneerat, Noppadol
    ;
    Sepsirisuk, Kasemsuk
    ;
    Hamamoto, Kazuhiko
    This paper presents nutrient deficiency multi-class classification in banana plant data sets using a deep convolutional neural network. In this paper, healthy and eight nutrient deficiency classes were studied. The performance was evaluated in different situations of two public data sets. The proposed method can provide sensitivity and specificity in Raw Images, Raw Images with combination, Augmented Images, and Augmented Images with the combination. Furthermore, nearly 88% of the F1-score was outperformed.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    A new correlation-based watermarking method using wavelet tree and mathematical morphology
    (2009-01-01)
    Sepsirisuk, Kasemsuk
    ;
    Hamamoto, Kazuhiko
    ;
    Atsuta, Kiyoaki
    ;
    Kondo, Shozo
    This paper proposes a new correlation-based watermarking method using the wavelet tree and the mathematical morphology. In this method a watermark is a two-dimensional pseudorandom array of {-1, 1} with the same size as a host image to be watermarked. The watermark is embedded into a Resilient Tree Structure (RTS) which is created by applying the mathematical morphology, the dilation operation, to the wavelet tree. The dilation operation improves the reliability of the proposed method by increasing the number of coefficients involved in watermarking. Furthermore an improved perceptual weighting function of the Human Visual System is used for preserving the image quality. In a watermark detection process the linear correlation between the watermark and the coefficients of the RTS of a tested image is computed to judge the presence of the watermark. The experimental results show that the proposed method outperforms current correlation-based watermarking methods. © 2009 The Institute of Electrical Engineers of Japan.