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52 ta ish

Ish: Comparative Study of Cell Nuclei Segmentation Based on Computational and Handcrafted Features Using Machine Learning Algorithms

  1. Utilizing Convolutional Neural Networks for the Effective Classification of Rice Leaf Diseases Through a Deep Learning Approach

    Salma Akter, Rashadul Islam Sumon, Haider Ali +1

    Maqola20243 iqtibos
    ABI

  2. Region Segmentation of Whole-Slide Images for Analyzing Histological Differentiation of Prostate Adenocarcinoma Using Ensemble EfficientNetB2 U-Net with Transfer Learning Mechanism

    Kobiljon Ikromjanov, Subrata Bhattacharjee, Rashadul Islam Sumon +7

    Maqola20232 iqtibos
    ABI

  3. Densely Convolutional Spatial Attention Network for nuclei segmentation of histological images for computational pathology

    Rashadul Islam Sumon, Subrata Bhattacharjee, Yeong-Byn Hwang +6

    Maqola20232 iqtibos
    ABI

  4. Enhanced Nuclei Segmentation in Histopathology Image Leveraging RGB Channels through Triple-Encoder and Single-Decoder Architectures

    Rashadul Islam Sumon, Md Ariful Islam Mazumdar, Shah Muhammad Imtiyaj Uddin +2

    Maqola20232 iqtibos
    ABI

  5. A Deep Learning-Based Approach for Precise Emotion Recognition in Domestic Animals Using EfficientNetB5 Architecture

    Rashadul Islam Sumon, Haider Ali, Salma Akter +3

    Maqola20252 iqtibos
    ABI

  6. Innovative Deep Learning Strategies for Early Detection of Brain Tumours in MRI Scans with a Modified ResNet50V2 Approach

    Rashadul Islam Sumon, Md Ariful Islam Mazumder, Salma Akter +2

    Maqola20252 iqtibos
    ABI

  7. Statistical and structural approaches to texture

    R.M. Haralick

    Maqola19792 iqtibos
    ABI

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