Перейти к основному содержанию
AkademIndex

Продукты

Для разработчиков

AkademBaseскороОткрытый API экосистемы
Латиница
Русский
← Назад к работе

Работы, на которые ссылается эта работа

Работ: 62

Работа: Brain Tumor Classification from MRI Using Image Enhancement and Convolutional Neural Network Techniques

  1. Deep Residual Learning for Image Recognition

    Kaiming He, Xiangyu Zhang, Shaoqing Ren +1

    Статья2016Цитирований: 61
    ABI
  2. MobileNetV2: Inverted Residuals and Linear Bottlenecks

    Mark Sandler, Andrew Howard, Menglong Zhu +2

    Препринт2018Цитирований: 17
    ABI
  3. Без названия

    ДругоеЦитирований: 17
    ABI
  4. Rethinking the Inception Architecture for Computer Vision

    Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe +2

    Статья2016Цитирований: 14
    ABI
  5. Very Deep Convolutional Networks for Large-Scale Image Recognition

    Karen Simonyan, Andrew Zisserman

    Статья2014Цитирований: 11
    ABI
  6. Dropout: a simple way to prevent neural networks from overfitting

    Nitish Srivastava, Geoffrey E. Hinton, Alex Krizhevsky +2

    Статья2014Цитирований: 10
    ABI
  7. Rectified Linear Units Improve Restricted Boltzmann Machines

    Vinod Nair, Geoffrey E. Hinton

    Статья2010Цитирований: 4
    ABI
  8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

    Sergey Ioffe, Christian Szegedy

    Препринт2015Цитирований: 4
    ABI
  9. Без названия

    ДругоеЦитирований: 4
    ABI
  10. Analysis and Design of Surgical Instrument Localization Algorithm

    Siyu Lu, Jun Yang, Bo Yang +4

    Статья2023Цитирований: 3
    ABI
  11. Без названия

    ДругоеЦитирований: 3
    ABI
  12. Understanding the difficulty of training deep feedforward neural networks

    Xavier Glorot, Yoshua Bengio

    Статья2010Цитирований: 2
    ABI
  13. Enhanced Performance of Brain Tumor Classification via Tumor Region Augmentation and Partition

    Jun Cheng, Wei Huang, Shuangliang Cao +5

    Статья2015Цитирований: 2
    ABI
  14. Deep Learning in Radiology

    Morgan P. McBee, Omer A. Awan, Andrew Colucci +5

    Обзорная статья2018Цитирований: 2
    ABI
  15. Brain tumor classification for MR images using transfer learning and fine-tuning

    Zar Nawab Khan Swati, Qinghua Zhao, Muhammad Kabir +4

    Статья2019Цитирований: 2
    ABI
  16. Brain tumor classification using modified local binary patterns (LBP) feature extraction methods

    Kaplan Kaplan, Yılmaz Kaya, Melih Kuncan +1

    Статья2020Цитирований: 2
    ABI
  17. Brain tumor classification based on hybrid approach

    Wadhah Ayadi, Imen Charfi, Wajdi Elhamzi +1

    Статья2020Цитирований: 2
    ABI
  18. Brain Tumor Classification Based on Fine-Tuned Models and the Ensemble Method

    Neelum Noreen, Sellapan Palaniappan, Abdul Qayyum +2

    Статья2021Цитирований: 2
    ABI
  19. Brain Tumor Classification of MRI Images Using Deep Convolutional Neural Network

    Swaraja Kuraparthi, Madhavi K. Reddy, C.N. Sujatha +5

    Статья2021Цитирований: 2
    ABI
  20. A Novel Hybrid Deep Learning Model for Metastatic Cancer Detection

    Shahab Ahmad, Tahir Ullah, Ijaz Ahmad +7

    Статья2022Цитирований: 2
    ABI
  21. An Effective WSSENet-Based Similarity Retrieval Method of Large Lung CT Image Databases

    Yi Zhuang, Shuai Chen, Nan Jiang +1

    Статья2022Цитирований: 2
    ABI
  22. Automated Classification of Brain Tumors from Magnetic Resonance Imaging Using Deep Learning

    Zahid Rasheed, Yong-Kui Ma, Inam Ullah +5

    Статья2023Цитирований: 2
    ABI