Работы, на которые ссылается эта работа

Работ: 35

Работа: A framework utilizing deep learning techniques for the detection and classification of breast cancerous cells in mammographic images

Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren +1
Статья2016Цитирований: 61
ABI
ImageNet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton
Статья2017Цитирований: 23
ABI
Improvement of Image Enhancement Technique for Mammography Images
Shavkat Fazilov, Kh.S. Abdiyeva, O.R. Yusupov
СтатьяAdvanced Scientific Research Methods2023Цитирований: 21
ABI
Patch-based lesion detection using deep learning method on small mammography dataset
Shavkat Fazilov, Kh.S. Abdieva, O.R. Yusupov
Глава2023Цитирований: 18
ABI
MobileNetV2: Inverted Residuals and Linear Bottlenecks
Mark Sandler, Andrew Howard, Menglong Zhu +2
Препринт2018Цитирований: 17
ABI
An Algorithm for Evaluating the Parameters Characterizing the Quality of the Image Field of the Iris by the Principal component analysis method
Shavkat Fazilov, O.R. Yusupov, Kh.S. Abdiyeva
СтатьяBiometric Identification and Security2022Цитирований: 17
ABI
Improvement of the Daugman Method for Nonreference Assessment of Image Quality in Iris Biometric Technology
Shavkat Fazilov, O.R. Yusupov
СтатьяBiometric Identification and Security2021Цитирований: 16
ABI
Rethinking the Inception Architecture for Computer Vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe +2
Статья2016Цитирований: 14
ABI
Algorithm for Extraction of the Iris Region in an Eye Image
Shavkat Fazilov, O.R. Yusupov
СтатьяBiometric Identification and Security2019Цитирований: 14
ABI
Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia +6
Статья2015Цитирований: 11
ABI
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Christian Szegedy, Sergey Ioffe, Sergey Ioffe +2
Статья2017Цитирований: 8
ABI
A Survey on Transfer Learning
Sinno Jialin Pan, Qiang Yang
Статья2009Цитирований: 5
ABI
A review on image-based approaches for breast cancer detection, segmentation, and classification
Zahra Rezaei
Обзорная статья2021Цитирований: 3
ABI
Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?
Nima Tajbakhsh, J. Shin, Suryakanth Gurudu +4
Статья2016Цитирований: 3
ABI
A curated mammography data set for use in computer-aided detection and diagnosis research
Rebecca Sawyer Lee, Francisco Javier Giménez Fuentes‐Guerra, Assaf Hoogi +3
Статья2017Цитирований: 3
ABI
Breast Cancer Diagnosis in Digital Breast Tomosynthesis: Effects of Training Sample Size on Multi-Stage Transfer Learning Using Deep Neural Nets
Ravi K. Samala, Heang‐Ping Chan, Lubomir M. Hadjiiski +3
Статья2018Цитирований: 3
ABI
THE DIGITAL DATABASE FOR SCREENING MAMMOGRAPHY
Michael D. Heath, Kevin W. Bowyer, D B Kopans +1
Статья2007Цитирований: 2
ABI
INbreast
Inês Moreira, Igor Amaral, Inês Domingues +3
Статья2011Цитирований: 2
ABI
The Mammographic Image Analysis Society digital mammogram database
John Suckling, James Parker, Susan Astley +9
Статья1994Цитирований: 2
ABI
Deep learning in medical imaging and radiation therapy
Berkman Sahiner, Aria Pezeshk, Lubomir M. Hadjiiski +5
Обзорная статья2018Цитирований: 2
ABI
Towards a Better Understanding of Transfer Learning for Medical Imaging: A Case Study
Laith Alzubaidi, Mohammed A. Fadhel, Omran Al-Shamma +4
Статья2020Цитирований: 2
ABI
A Novel Deep-Learning Model for Automatic Detection and Classification of Breast Cancer Using the Transfer-Learning Technique
Abeer Saber, Mohamed Sakr, Osama M. Abo-Seida +2
Статья2021Цитирований: 2
ABI
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ДругоеЦитирований: 1
ABI
Без названия
ДругоеЦитирований: 1
ABI
Без названия
ДругоеЦитирований: 1
ABI