Artículos de revistas sobre el tema "BREAKHIS DATASET"
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Joshi, Shubhangi A., Anupkumar M. Bongale, P. Olof Olsson, Siddhaling Urolagin, Deepak Dharrao y Arunkumar Bongale. "Enhanced Pre-Trained Xception Model Transfer Learned for Breast Cancer Detection". Computation 11, n.º 3 (13 de marzo de 2023): 59. http://dx.doi.org/10.3390/computation11030059.
Texto completoXu, Xuebin, Meijuan An, Jiada Zhang, Wei Liu y Longbin Lu. "A High-Precision Classification Method of Mammary Cancer Based on Improved DenseNet Driven by an Attention Mechanism". Computational and Mathematical Methods in Medicine 2022 (14 de mayo de 2022): 1–14. http://dx.doi.org/10.1155/2022/8585036.
Texto completoOgundokun, Roseline Oluwaseun, Sanjay Misra, Akinyemi Omololu Akinrotimi y Hasan Ogul. "MobileNet-SVM: A Lightweight Deep Transfer Learning Model to Diagnose BCH Scans for IoMT-Based Imaging Sensors". Sensors 23, n.º 2 (6 de enero de 2023): 656. http://dx.doi.org/10.3390/s23020656.
Texto completoUkwuoma, Chiagoziem C., Md Altab Hossain, Jehoiada K. Jackson, Grace U. Nneji, Happy N. Monday y Zhiguang Qin. "Multi-Classification of Breast Cancer Lesions in Histopathological Images Using DEEP_Pachi: Multiple Self-Attention Head". Diagnostics 12, n.º 5 (5 de mayo de 2022): 1152. http://dx.doi.org/10.3390/diagnostics12051152.
Texto completoMohanakurup, Vinodkumar, Syam Machinathu Parambil Gangadharan, Pallavi Goel, Devvret Verma, Sameer Alshehri, Ramgopal Kashyap y Baitullah Malakhil. "Breast Cancer Detection on Histopathological Images Using a Composite Dilated Backbone Network". Computational Intelligence and Neuroscience 2022 (6 de julio de 2022): 1–10. http://dx.doi.org/10.1155/2022/8517706.
Texto completoNahid, Abdullah-Al, Mohamad Ali Mehrabi y Yinan Kong. "Histopathological Breast Cancer Image Classification by Deep Neural Network Techniques Guided by Local Clustering". BioMed Research International 2018 (2018): 1–20. http://dx.doi.org/10.1155/2018/2362108.
Texto completoSun, Yixin, Lei Wu, Peng Chen, Feng Zhang y Lifeng Xu. "Using deep learning in pathology image analysis: A novel active learning strategy based on latent representation". Electronic Research Archive 31, n.º 9 (2023): 5340–61. http://dx.doi.org/10.3934/era.2023271.
Texto completoIstighosah, Maie, Andi Sunyoto y Tonny Hidayat. "Breast Cancer Detection in Histopathology Images using ResNet101 Architecture". sinkron 8, n.º 4 (1 de octubre de 2023): 2138–49. http://dx.doi.org/10.33395/sinkron.v8i4.12948.
Texto completoLi, Lingxiao, Niantao Xie y Sha Yuan. "A Federated Learning Framework for Breast Cancer Histopathological Image Classification". Electronics 11, n.º 22 (16 de noviembre de 2022): 3767. http://dx.doi.org/10.3390/electronics11223767.
Texto completoBurrai, Giovanni P., Andrea Gabrieli, Marta Polinas, Claudio Murgia, Maria Paola Becchere, Pierfranco Demontis y Elisabetta Antuofermo. "Canine Mammary Tumor Histopathological Image Classification via Computer-Aided Pathology: An Available Dataset for Imaging Analysis". Animals 13, n.º 9 (6 de mayo de 2023): 1563. http://dx.doi.org/10.3390/ani13091563.
Texto completoMinarno, Agus Eko, Lulita Ria Wandani y Yufis Azhar. "Classification of Breast Cancer Based on Histopathological Image Using EfficientNet-B0 on Convolutional Neural Network". International Journal of Emerging Technology and Advanced Engineering 12, n.º 8 (2 de agosto de 2022): 70–77. http://dx.doi.org/10.46338/ijetae0822_09.
Texto completoAgbley, Bless Lord Y., Jianping Li, Md Altab Hossin, Grace Ugochi Nneji, Jehoiada Jackson, Happy Nkanta Monday y Edidiong Christopher James. "Federated Learning-Based Detection of Invasive Carcinoma of No Special Type with Histopathological Images". Diagnostics 12, n.º 7 (9 de julio de 2022): 1669. http://dx.doi.org/10.3390/diagnostics12071669.
Texto completoMewada, Hiren K., Amit V. Patel, Mahmoud Hassaballah, Monagi H. Alkinani y Keyur Mahant. "Spectral–Spatial Features Integrated Convolution Neural Network for Breast Cancer Classification". Sensors 20, n.º 17 (22 de agosto de 2020): 4747. http://dx.doi.org/10.3390/s20174747.
Texto completoLi, Xin, HongBo Li, WenSheng Cui, ZhaoHui Cai y MeiJuan Jia. "Classification on Digital Pathological Images of Breast Cancer Based on Deep Features of Different Levels". Mathematical Problems in Engineering 2021 (30 de diciembre de 2021): 1–13. http://dx.doi.org/10.1155/2021/8403025.
Texto completoAmato, Domenico, Salvatore Calderaro, Giosué Lo Bosco, Riccardo Rizzo y Filippo Vella. "Metric Learning in Histopathological Image Classification: Opening the Black Box". Sensors 23, n.º 13 (28 de junio de 2023): 6003. http://dx.doi.org/10.3390/s23136003.
Texto completoLiu, Min, Yu He, Minghu Wu y Chunyan Zeng. "Breast Histopathological Image Classification Method Based on Autoencoder and Siamese Framework". Information 13, n.º 3 (24 de febrero de 2022): 107. http://dx.doi.org/10.3390/info13030107.
Texto completoUmer, Muhammad Junaid, Muhammad Sharif, Seifedine Kadry y Abdullah Alharbi. "Multi-Class Classification of Breast Cancer Using 6B-Net with Deep Feature Fusion and Selection Method". Journal of Personalized Medicine 12, n.º 5 (26 de abril de 2022): 683. http://dx.doi.org/10.3390/jpm12050683.
Texto completoUmer, Muhammad Junaid, Muhammad Sharif, Seifedine Kadry y Abdullah Alharbi. "Multi-Class Classification of Breast Cancer Using 6B-Net with Deep Feature Fusion and Selection Method". Journal of Personalized Medicine 12, n.º 5 (26 de abril de 2022): 683. http://dx.doi.org/10.3390/jpm12050683.
Texto completoSarker, Md Mostafa Kamal, Farhan Akram, Mohammad Alsharid, Vivek Kumar Singh, Robail Yasrab y Eyad Elyan. "Efficient Breast Cancer Classification Network with Dual Squeeze and Excitation in Histopathological Images". Diagnostics 13, n.º 1 (29 de diciembre de 2022): 103. http://dx.doi.org/10.3390/diagnostics13010103.
Texto completoChandranegara, Didih Rizki, Faras Haidar Pratama, Sidiq Fajrianur, Moch Rizky Eka Putra y Zamah Sari. "Automated Detection of Breast Cancer Histopathology Image Using Convolutional Neural Network and Transfer Learning". MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer 22, n.º 3 (3 de julio de 2023): 455–68. http://dx.doi.org/10.30812/matrik.v22i3.2803.
Texto completoWakili, Musa Adamu, Harisu Abdullahi Shehu, Md Haidar Sharif, Md Haris Uddin Sharif, Abubakar Umar, Huseyin Kusetogullari, Ibrahim Furkan Ince y Sahin Uyaver. "Classification of Breast Cancer Histopathological Images Using DenseNet and Transfer Learning". Computational Intelligence and Neuroscience 2022 (10 de octubre de 2022): 1–31. http://dx.doi.org/10.1155/2022/8904768.
Texto completoAlirezazadeh, Pendar, Fadi Dornaika y Abdelmalik Moujahid. "Chasing a Better Decision Margin for Discriminative Histopathological Breast Cancer Image Classification". Electronics 12, n.º 20 (20 de octubre de 2023): 4356. http://dx.doi.org/10.3390/electronics12204356.
Texto completoZaalouk, Ahmed M., Gamal A. Ebrahim, Hoda K. Mohamed, Hoda Mamdouh Hassan y Mohamed M. A. Zaalouk. "A Deep Learning Computer-Aided Diagnosis Approach for Breast Cancer". Bioengineering 9, n.º 8 (15 de agosto de 2022): 391. http://dx.doi.org/10.3390/bioengineering9080391.
Texto completoLi, Jia, Jingwen Shi, Hexing Su y Le Gao. "Breast Cancer Histopathological Image Recognition Based on Pyramid Gray Level Co-Occurrence Matrix and Incremental Broad Learning". Electronics 11, n.º 15 (26 de julio de 2022): 2322. http://dx.doi.org/10.3390/electronics11152322.
Texto completoJae Lim, Myung, Da Eun Kim, Dong Kun Chung, Hoon Lim y Young Man Kwon. "Deep Convolution Neural Networks for Medical Image Analysis". International Journal of Engineering & Technology 7, n.º 3.33 (29 de agosto de 2018): 115. http://dx.doi.org/10.14419/ijet.v7i3.33.18588.
Texto completoKode, Hepseeba y Buket D. Barkana. "Deep Learning- and Expert Knowledge-Based Feature Extraction and Performance Evaluation in Breast Histopathology Images". Cancers 15, n.º 12 (6 de junio de 2023): 3075. http://dx.doi.org/10.3390/cancers15123075.
Texto completoLeow, Jia Rong, Wee How Khoh, Ying Han Pang y Hui Yen Yap. "Breast cancer classification with histopathological image based on machine learning". International Journal of Electrical and Computer Engineering (IJECE) 13, n.º 5 (1 de octubre de 2023): 5885. http://dx.doi.org/10.11591/ijece.v13i5.pp5885-5897.
Texto completoTummala, Sudhakar, Jungeun Kim y Seifedine Kadry. "BreaST-Net: Multi-Class Classification of Breast Cancer from Histopathological Images Using Ensemble of Swin Transformers". Mathematics 10, n.º 21 (4 de noviembre de 2022): 4109. http://dx.doi.org/10.3390/math10214109.
Texto completoKaplun, Dmitry, Alexander Krasichkov, Petr Chetyrbok, Nikolay Oleinikov, Anupam Garg y Husanbir Singh Pannu. "Cancer Cell Profiling Using Image Moments and Neural Networks with Model Agnostic Explainability: A Case Study of Breast Cancer Histopathological (BreakHis) Database". Mathematics 9, n.º 20 (17 de octubre de 2021): 2616. http://dx.doi.org/10.3390/math9202616.
Texto completoChopra, Pooja, N. Junath, Sitesh Kumar Singh, Shakir Khan, R. Sugumar y Mithun Bhowmick. "Cyclic GAN Model to Classify Breast Cancer Data for Pathological Healthcare Task". BioMed Research International 2022 (21 de julio de 2022): 1–12. http://dx.doi.org/10.1155/2022/6336700.
Texto completoElshafey, Mohamed Abdelmoneim y Tarek Elsaid Ghoniemy. "A hybrid ensemble deep learning approach for reliable breast cancer detection". International Journal of Advances in Intelligent Informatics 7, n.º 2 (19 de abril de 2021): 112. http://dx.doi.org/10.26555/ijain.v7i2.615.
Texto completoYang, Yunfeng y Chen Guan. "Classification of histopathological images of breast cancer using an improved convolutional neural network model". Journal of X-Ray Science and Technology 30, n.º 1 (22 de enero de 2022): 33–44. http://dx.doi.org/10.3233/xst-210982.
Texto completoSaha, Priya, Puja Das, Niharika Nath y Mrinal Kanti Bhowmik. "Estimation of Abnormal Cell Growth and MCG-Based Discriminative Feature Analysis of Histopathological Breast Images". International Journal of Intelligent Systems 2023 (30 de junio de 2023): 1–12. http://dx.doi.org/10.1155/2023/6318127.
Texto completoHao, Yan, Li Zhang, Shichang Qiao, Yanping Bai, Rong Cheng, Hongxin Xue, Yuchao Hou, Wendong Zhang y Guojun Zhang. "Breast cancer histopathological images classification based on deep semantic features and gray level co-occurrence matrix". PLOS ONE 17, n.º 5 (5 de mayo de 2022): e0267955. http://dx.doi.org/10.1371/journal.pone.0267955.
Texto completoLee, Jiann-Shu y Wen-Kai Wu. "Breast Tumor Tissue Image Classification Using DIU-Net". Sensors 22, n.º 24 (14 de diciembre de 2022): 9838. http://dx.doi.org/10.3390/s22249838.
Texto completoAshurov, Asadulla, Samia Allaoua Chelloug, Alexey Tselykh, Mohammed Saleh Ali Muthanna, Ammar Muthanna y Mehdhar S. A. M. Al-Gaashani. "Improved Breast Cancer Classification through Combining Transfer Learning and Attention Mechanism". Life 13, n.º 9 (21 de septiembre de 2023): 1945. http://dx.doi.org/10.3390/life13091945.
Texto completoAlqahtani, Yahya, Umakant Mandawkar, Aditi Sharma, Mohammad Najmus Saquib Hasan, Mrunalini Harish Kulkarni y R. Sugumar. "Breast Cancer Pathological Image Classification Based on the Multiscale CNN Squeeze Model". Computational Intelligence and Neuroscience 2022 (29 de agosto de 2022): 1–11. http://dx.doi.org/10.1155/2022/7075408.
Texto completoBurçak, Kadir Can y Harun Uğuz. "A New Hybrid Breast Cancer Diagnosis Model Using Deep Learning Model and ReliefF". Traitement du Signal 39, n.º 2 (30 de abril de 2022): 521–29. http://dx.doi.org/10.18280/ts.390214.
Texto completoAsare, Sarpong Kwadwo, Fei You y Obed Tettey Nartey. "A Semisupervised Learning Scheme with Self-Paced Learning for Classifying Breast Cancer Histopathological Images". Computational Intelligence and Neuroscience 2020 (8 de diciembre de 2020): 1–16. http://dx.doi.org/10.1155/2020/8826568.
Texto completoTangsakul, Surasak y Sartra Wongthanavasu. "Deep Cellular Automata-Based Feature Extraction for Classification of the Breast Cancer Image". Applied Sciences 13, n.º 10 (15 de mayo de 2023): 6081. http://dx.doi.org/10.3390/app13106081.
Texto completoBoumaraf, Said, Xiabi Liu, Yuchai Wan, Zhongshu Zheng, Chokri Ferkous, Xiaohong Ma, Zhuo Li y Dalal Bardou. "Conventional Machine Learning versus Deep Learning for Magnification Dependent Histopathological Breast Cancer Image Classification: A Comparative Study with Visual Explanation". Diagnostics 11, n.º 3 (16 de marzo de 2021): 528. http://dx.doi.org/10.3390/diagnostics11030528.
Texto completoWang, Jiatong, Tiantian Zhu, Shan Liang, R. Karthiga, K. Narasimhan y V. Elamaran. "Binary and Multiclass Classification of Histopathological Images Using Machine Learning Techniques". Journal of Medical Imaging and Health Informatics 10, n.º 9 (1 de agosto de 2020): 2252–58. http://dx.doi.org/10.1166/jmihi.2020.3124.
Texto completoJakkaladiki, Sudha Prathyusha y Filip Maly. "An efficient transfer learning based cross model classification (TLBCM) technique for the prediction of breast cancer". PeerJ Computer Science 9 (21 de marzo de 2023): e1281. http://dx.doi.org/10.7717/peerj-cs.1281.
Texto completoClement, David, Emmanuel Agu, Muhammad A. Suleiman, John Obayemi, Steve Adeshina y Wole Soboyejo. "Multi-Class Breast Cancer Histopathological Image Classification Using Multi-Scale Pooled Image Feature Representation (MPIFR) and One-Versus-One Support Vector Machines". Applied Sciences 13, n.º 1 (22 de diciembre de 2022): 156. http://dx.doi.org/10.3390/app13010156.
Texto completoClement, David, Emmanuel Agu, John Obayemi, Steve Adeshina y Wole Soboyejo. "Breast Cancer Tumor Classification Using a Bag of Deep Multi-Resolution Convolutional Features". Informatics 9, n.º 4 (28 de octubre de 2022): 91. http://dx.doi.org/10.3390/informatics9040091.
Texto completoLu, Shida, Kai Huang, Talha Meraj y Hafiz Tayyab Rauf. "A novel CAPTCHA solver framework using deep skipping Convolutional Neural Networks". PeerJ Computer Science 8 (6 de abril de 2022): e879. http://dx.doi.org/10.7717/peerj-cs.879.
Texto completoTao, Ran, Zhaoya Gong, Qiwei Ma y Jean-Claude Thill. "Boosting Computational Effectiveness in Big Spatial Flow Data Analysis with Intelligent Data Reduction". ISPRS International Journal of Geo-Information 9, n.º 5 (6 de mayo de 2020): 299. http://dx.doi.org/10.3390/ijgi9050299.
Texto completoTang, Yansong, Xingyu Liu, Xumin Yu, Danyang Zhang, Jiwen Lu y Jie Zhou. "Learning from Temporal Spatial Cubism for Cross-Dataset Skeleton-based Action Recognition". ACM Transactions on Multimedia Computing, Communications, and Applications 18, n.º 2 (31 de mayo de 2022): 1–24. http://dx.doi.org/10.1145/3472722.
Texto completoIsthigosah, Maie, Andi Sunyoto y Tonny Hidayat. "Image Augmentation for BreaKHis Medical Data using Convolutional Neural Networks". sinkron 8, n.º 4 (1 de octubre de 2023): 2381–92. http://dx.doi.org/10.33395/sinkron.v8i4.12878.
Texto completoLaporte, Matias, Martin Gjoreski y Marc Langheinrich. "LAUREATE". Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 7, n.º 3 (27 de septiembre de 2023): 1–41. http://dx.doi.org/10.1145/3610892.
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