Classification of Histopathological Breast Cancer Images using Convolutional Neural Networks
Article Properties
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DOI (url)
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Publication Date2019/09/27
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Indian UGC (journal)
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Refrences26
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Citations4
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Muhammed TALO MUNZUR ÜNİVERSİTESİ ORCID
Abstract
Cite
TALO, Muhammed. “Classification of Histopathological Breast Cancer Images Using Convolutional Neural Networks”. Fırat Üniversitesi Mühendislik Bilimleri Dergisi, vol. 31, no. 2, 2019, pp. 391-8, https://doi.org/10.35234/fumbd.517939.
TALO, M. (2019). Classification of Histopathological Breast Cancer Images using Convolutional Neural Networks. Fırat Üniversitesi Mühendislik Bilimleri Dergisi, 31(2), 391-398. https://doi.org/10.35234/fumbd.517939
TALO M. Classification of Histopathological Breast Cancer Images using Convolutional Neural Networks. Fırat Üniversitesi Mühendislik Bilimleri Dergisi. 2019;31(2):391-8.
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| One-class kernel subspace ensemble for medical image classification | EURASIP Journal on Advances in Signal Processing |
| 45 | 2014 |
| Breast cancer diagnosis from biopsy images with highly reliable random subspace classifier ensembles | Machine Vision and Applications |
| 37 | 2012 |
| Arrhythmia detection using deep convolutional neural network with long duration ECG signals | Computers in Biology and Medicine |
| 403 | 2018 |
| A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification | Computers in Biology and Medicine |
| 396 | 2018 |
| An efficient compression of ECG signals using deep convolutional autoencoders | Cognitive Systems Research | 111 | 2018 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Deep learning based classification of time series of chaotic systems over graphic images | Multimedia Tools and Applications |
| 2023 | |
Classification of breast cancer with deep learning from noisy images using wavelet transform | Biomedical Engineering / Biomedizinische Technik |
| 5 | 2022 |
Classification of Environmental Sounds With Deep Learning | Advances in Artificial Intelligence Research | 1 | 2022 | |
Diagnostic Classification of Cervical Cell Images from Pap Smear Slides | Academic Perspective Procedia | 3 | 2019 |
Citations Analysis
The category
Science: Science (General): Cybernetics: Information theory 1
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Diagnostic Classification of Cervical Cell Images from Pap Smear Slides and was published in 2019. The most recent citation comes from a 2023 study titled Deep learning based classification of time series of chaotic systems over graphic images. This article reached its peak citation in 2022, with 2 citations. It has been cited in 4 different journals. Among related journals, the Multimedia Tools and Applications cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.