Artykuły w czasopismach na temat „BREAKHIS DATASET”
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Joshi, Shubhangi A., Anupkumar M. Bongale, P. Olof Olsson, Siddhaling Urolagin, Deepak Dharrao i Arunkumar Bongale. "Enhanced Pre-Trained Xception Model Transfer Learned for Breast Cancer Detection". Computation 11, nr 3 (13.03.2023): 59. http://dx.doi.org/10.3390/computation11030059.
Pełny tekst źródłaXu, Xuebin, Meijuan An, Jiada Zhang, Wei Liu i 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 (14.05.2022): 1–14. http://dx.doi.org/10.1155/2022/8585036.
Pełny tekst źródłaOgundokun, Roseline Oluwaseun, Sanjay Misra, Akinyemi Omololu Akinrotimi i Hasan Ogul. "MobileNet-SVM: A Lightweight Deep Transfer Learning Model to Diagnose BCH Scans for IoMT-Based Imaging Sensors". Sensors 23, nr 2 (6.01.2023): 656. http://dx.doi.org/10.3390/s23020656.
Pełny tekst źródłaUkwuoma, Chiagoziem C., Md Altab Hossain, Jehoiada K. Jackson, Grace U. Nneji, Happy N. Monday i Zhiguang Qin. "Multi-Classification of Breast Cancer Lesions in Histopathological Images Using DEEP_Pachi: Multiple Self-Attention Head". Diagnostics 12, nr 5 (5.05.2022): 1152. http://dx.doi.org/10.3390/diagnostics12051152.
Pełny tekst źródłaMohanakurup, Vinodkumar, Syam Machinathu Parambil Gangadharan, Pallavi Goel, Devvret Verma, Sameer Alshehri, Ramgopal Kashyap i Baitullah Malakhil. "Breast Cancer Detection on Histopathological Images Using a Composite Dilated Backbone Network". Computational Intelligence and Neuroscience 2022 (6.07.2022): 1–10. http://dx.doi.org/10.1155/2022/8517706.
Pełny tekst źródłaNahid, Abdullah-Al, Mohamad Ali Mehrabi i 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.
Pełny tekst źródłaSun, Yixin, Lei Wu, Peng Chen, Feng Zhang i Lifeng Xu. "Using deep learning in pathology image analysis: A novel active learning strategy based on latent representation". Electronic Research Archive 31, nr 9 (2023): 5340–61. http://dx.doi.org/10.3934/era.2023271.
Pełny tekst źródłaIstighosah, Maie, Andi Sunyoto i Tonny Hidayat. "Breast Cancer Detection in Histopathology Images using ResNet101 Architecture". sinkron 8, nr 4 (1.10.2023): 2138–49. http://dx.doi.org/10.33395/sinkron.v8i4.12948.
Pełny tekst źródłaLi, Lingxiao, Niantao Xie i Sha Yuan. "A Federated Learning Framework for Breast Cancer Histopathological Image Classification". Electronics 11, nr 22 (16.11.2022): 3767. http://dx.doi.org/10.3390/electronics11223767.
Pełny tekst źródłaBurrai, Giovanni P., Andrea Gabrieli, Marta Polinas, Claudio Murgia, Maria Paola Becchere, Pierfranco Demontis i Elisabetta Antuofermo. "Canine Mammary Tumor Histopathological Image Classification via Computer-Aided Pathology: An Available Dataset for Imaging Analysis". Animals 13, nr 9 (6.05.2023): 1563. http://dx.doi.org/10.3390/ani13091563.
Pełny tekst źródłaMinarno, Agus Eko, Lulita Ria Wandani i 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, nr 8 (2.08.2022): 70–77. http://dx.doi.org/10.46338/ijetae0822_09.
Pełny tekst źródłaAgbley, Bless Lord Y., Jianping Li, Md Altab Hossin, Grace Ugochi Nneji, Jehoiada Jackson, Happy Nkanta Monday i Edidiong Christopher James. "Federated Learning-Based Detection of Invasive Carcinoma of No Special Type with Histopathological Images". Diagnostics 12, nr 7 (9.07.2022): 1669. http://dx.doi.org/10.3390/diagnostics12071669.
Pełny tekst źródłaMewada, Hiren K., Amit V. Patel, Mahmoud Hassaballah, Monagi H. Alkinani i Keyur Mahant. "Spectral–Spatial Features Integrated Convolution Neural Network for Breast Cancer Classification". Sensors 20, nr 17 (22.08.2020): 4747. http://dx.doi.org/10.3390/s20174747.
Pełny tekst źródłaLi, Xin, HongBo Li, WenSheng Cui, ZhaoHui Cai i MeiJuan Jia. "Classification on Digital Pathological Images of Breast Cancer Based on Deep Features of Different Levels". Mathematical Problems in Engineering 2021 (30.12.2021): 1–13. http://dx.doi.org/10.1155/2021/8403025.
Pełny tekst źródłaAmato, Domenico, Salvatore Calderaro, Giosué Lo Bosco, Riccardo Rizzo i Filippo Vella. "Metric Learning in Histopathological Image Classification: Opening the Black Box". Sensors 23, nr 13 (28.06.2023): 6003. http://dx.doi.org/10.3390/s23136003.
Pełny tekst źródłaLiu, Min, Yu He, Minghu Wu i Chunyan Zeng. "Breast Histopathological Image Classification Method Based on Autoencoder and Siamese Framework". Information 13, nr 3 (24.02.2022): 107. http://dx.doi.org/10.3390/info13030107.
Pełny tekst źródłaUmer, Muhammad Junaid, Muhammad Sharif, Seifedine Kadry i Abdullah Alharbi. "Multi-Class Classification of Breast Cancer Using 6B-Net with Deep Feature Fusion and Selection Method". Journal of Personalized Medicine 12, nr 5 (26.04.2022): 683. http://dx.doi.org/10.3390/jpm12050683.
Pełny tekst źródłaUmer, Muhammad Junaid, Muhammad Sharif, Seifedine Kadry i Abdullah Alharbi. "Multi-Class Classification of Breast Cancer Using 6B-Net with Deep Feature Fusion and Selection Method". Journal of Personalized Medicine 12, nr 5 (26.04.2022): 683. http://dx.doi.org/10.3390/jpm12050683.
Pełny tekst źródłaSarker, Md Mostafa Kamal, Farhan Akram, Mohammad Alsharid, Vivek Kumar Singh, Robail Yasrab i Eyad Elyan. "Efficient Breast Cancer Classification Network with Dual Squeeze and Excitation in Histopathological Images". Diagnostics 13, nr 1 (29.12.2022): 103. http://dx.doi.org/10.3390/diagnostics13010103.
Pełny tekst źródłaChandranegara, Didih Rizki, Faras Haidar Pratama, Sidiq Fajrianur, Moch Rizky Eka Putra i 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, nr 3 (3.07.2023): 455–68. http://dx.doi.org/10.30812/matrik.v22i3.2803.
Pełny tekst źródłaWakili, Musa Adamu, Harisu Abdullahi Shehu, Md Haidar Sharif, Md Haris Uddin Sharif, Abubakar Umar, Huseyin Kusetogullari, Ibrahim Furkan Ince i Sahin Uyaver. "Classification of Breast Cancer Histopathological Images Using DenseNet and Transfer Learning". Computational Intelligence and Neuroscience 2022 (10.10.2022): 1–31. http://dx.doi.org/10.1155/2022/8904768.
Pełny tekst źródłaAlirezazadeh, Pendar, Fadi Dornaika i Abdelmalik Moujahid. "Chasing a Better Decision Margin for Discriminative Histopathological Breast Cancer Image Classification". Electronics 12, nr 20 (20.10.2023): 4356. http://dx.doi.org/10.3390/electronics12204356.
Pełny tekst źródłaZaalouk, Ahmed M., Gamal A. Ebrahim, Hoda K. Mohamed, Hoda Mamdouh Hassan i Mohamed M. A. Zaalouk. "A Deep Learning Computer-Aided Diagnosis Approach for Breast Cancer". Bioengineering 9, nr 8 (15.08.2022): 391. http://dx.doi.org/10.3390/bioengineering9080391.
Pełny tekst źródłaLi, Jia, Jingwen Shi, Hexing Su i Le Gao. "Breast Cancer Histopathological Image Recognition Based on Pyramid Gray Level Co-Occurrence Matrix and Incremental Broad Learning". Electronics 11, nr 15 (26.07.2022): 2322. http://dx.doi.org/10.3390/electronics11152322.
Pełny tekst źródłaJae Lim, Myung, Da Eun Kim, Dong Kun Chung, Hoon Lim i Young Man Kwon. "Deep Convolution Neural Networks for Medical Image Analysis". International Journal of Engineering & Technology 7, nr 3.33 (29.08.2018): 115. http://dx.doi.org/10.14419/ijet.v7i3.33.18588.
Pełny tekst źródłaKode, Hepseeba, i Buket D. Barkana. "Deep Learning- and Expert Knowledge-Based Feature Extraction and Performance Evaluation in Breast Histopathology Images". Cancers 15, nr 12 (6.06.2023): 3075. http://dx.doi.org/10.3390/cancers15123075.
Pełny tekst źródłaLeow, Jia Rong, Wee How Khoh, Ying Han Pang i Hui Yen Yap. "Breast cancer classification with histopathological image based on machine learning". International Journal of Electrical and Computer Engineering (IJECE) 13, nr 5 (1.10.2023): 5885. http://dx.doi.org/10.11591/ijece.v13i5.pp5885-5897.
Pełny tekst źródłaTummala, Sudhakar, Jungeun Kim i Seifedine Kadry. "BreaST-Net: Multi-Class Classification of Breast Cancer from Histopathological Images Using Ensemble of Swin Transformers". Mathematics 10, nr 21 (4.11.2022): 4109. http://dx.doi.org/10.3390/math10214109.
Pełny tekst źródłaKaplun, Dmitry, Alexander Krasichkov, Petr Chetyrbok, Nikolay Oleinikov, Anupam Garg i 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, nr 20 (17.10.2021): 2616. http://dx.doi.org/10.3390/math9202616.
Pełny tekst źródłaChopra, Pooja, N. Junath, Sitesh Kumar Singh, Shakir Khan, R. Sugumar i Mithun Bhowmick. "Cyclic GAN Model to Classify Breast Cancer Data for Pathological Healthcare Task". BioMed Research International 2022 (21.07.2022): 1–12. http://dx.doi.org/10.1155/2022/6336700.
Pełny tekst źródłaElshafey, Mohamed Abdelmoneim, i Tarek Elsaid Ghoniemy. "A hybrid ensemble deep learning approach for reliable breast cancer detection". International Journal of Advances in Intelligent Informatics 7, nr 2 (19.04.2021): 112. http://dx.doi.org/10.26555/ijain.v7i2.615.
Pełny tekst źródłaYang, Yunfeng, i Chen Guan. "Classification of histopathological images of breast cancer using an improved convolutional neural network model". Journal of X-Ray Science and Technology 30, nr 1 (22.01.2022): 33–44. http://dx.doi.org/10.3233/xst-210982.
Pełny tekst źródłaSaha, Priya, Puja Das, Niharika Nath i Mrinal Kanti Bhowmik. "Estimation of Abnormal Cell Growth and MCG-Based Discriminative Feature Analysis of Histopathological Breast Images". International Journal of Intelligent Systems 2023 (30.06.2023): 1–12. http://dx.doi.org/10.1155/2023/6318127.
Pełny tekst źródłaHao, Yan, Li Zhang, Shichang Qiao, Yanping Bai, Rong Cheng, Hongxin Xue, Yuchao Hou, Wendong Zhang i Guojun Zhang. "Breast cancer histopathological images classification based on deep semantic features and gray level co-occurrence matrix". PLOS ONE 17, nr 5 (5.05.2022): e0267955. http://dx.doi.org/10.1371/journal.pone.0267955.
Pełny tekst źródłaLee, Jiann-Shu, i Wen-Kai Wu. "Breast Tumor Tissue Image Classification Using DIU-Net". Sensors 22, nr 24 (14.12.2022): 9838. http://dx.doi.org/10.3390/s22249838.
Pełny tekst źródłaAshurov, Asadulla, Samia Allaoua Chelloug, Alexey Tselykh, Mohammed Saleh Ali Muthanna, Ammar Muthanna i Mehdhar S. A. M. Al-Gaashani. "Improved Breast Cancer Classification through Combining Transfer Learning and Attention Mechanism". Life 13, nr 9 (21.09.2023): 1945. http://dx.doi.org/10.3390/life13091945.
Pełny tekst źródłaAlqahtani, Yahya, Umakant Mandawkar, Aditi Sharma, Mohammad Najmus Saquib Hasan, Mrunalini Harish Kulkarni i R. Sugumar. "Breast Cancer Pathological Image Classification Based on the Multiscale CNN Squeeze Model". Computational Intelligence and Neuroscience 2022 (29.08.2022): 1–11. http://dx.doi.org/10.1155/2022/7075408.
Pełny tekst źródłaBurçak, Kadir Can, i Harun Uğuz. "A New Hybrid Breast Cancer Diagnosis Model Using Deep Learning Model and ReliefF". Traitement du Signal 39, nr 2 (30.04.2022): 521–29. http://dx.doi.org/10.18280/ts.390214.
Pełny tekst źródłaAsare, Sarpong Kwadwo, Fei You i Obed Tettey Nartey. "A Semisupervised Learning Scheme with Self-Paced Learning for Classifying Breast Cancer Histopathological Images". Computational Intelligence and Neuroscience 2020 (8.12.2020): 1–16. http://dx.doi.org/10.1155/2020/8826568.
Pełny tekst źródłaTangsakul, Surasak, i Sartra Wongthanavasu. "Deep Cellular Automata-Based Feature Extraction for Classification of the Breast Cancer Image". Applied Sciences 13, nr 10 (15.05.2023): 6081. http://dx.doi.org/10.3390/app13106081.
Pełny tekst źródłaBoumaraf, Said, Xiabi Liu, Yuchai Wan, Zhongshu Zheng, Chokri Ferkous, Xiaohong Ma, Zhuo Li i Dalal Bardou. "Conventional Machine Learning versus Deep Learning for Magnification Dependent Histopathological Breast Cancer Image Classification: A Comparative Study with Visual Explanation". Diagnostics 11, nr 3 (16.03.2021): 528. http://dx.doi.org/10.3390/diagnostics11030528.
Pełny tekst źródłaWang, Jiatong, Tiantian Zhu, Shan Liang, R. Karthiga, K. Narasimhan i V. Elamaran. "Binary and Multiclass Classification of Histopathological Images Using Machine Learning Techniques". Journal of Medical Imaging and Health Informatics 10, nr 9 (1.08.2020): 2252–58. http://dx.doi.org/10.1166/jmihi.2020.3124.
Pełny tekst źródłaJakkaladiki, Sudha Prathyusha, i Filip Maly. "An efficient transfer learning based cross model classification (TLBCM) technique for the prediction of breast cancer". PeerJ Computer Science 9 (21.03.2023): e1281. http://dx.doi.org/10.7717/peerj-cs.1281.
Pełny tekst źródłaClement, David, Emmanuel Agu, Muhammad A. Suleiman, John Obayemi, Steve Adeshina i 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, nr 1 (22.12.2022): 156. http://dx.doi.org/10.3390/app13010156.
Pełny tekst źródłaClement, David, Emmanuel Agu, John Obayemi, Steve Adeshina i Wole Soboyejo. "Breast Cancer Tumor Classification Using a Bag of Deep Multi-Resolution Convolutional Features". Informatics 9, nr 4 (28.10.2022): 91. http://dx.doi.org/10.3390/informatics9040091.
Pełny tekst źródłaLu, Shida, Kai Huang, Talha Meraj i Hafiz Tayyab Rauf. "A novel CAPTCHA solver framework using deep skipping Convolutional Neural Networks". PeerJ Computer Science 8 (6.04.2022): e879. http://dx.doi.org/10.7717/peerj-cs.879.
Pełny tekst źródłaTao, Ran, Zhaoya Gong, Qiwei Ma i Jean-Claude Thill. "Boosting Computational Effectiveness in Big Spatial Flow Data Analysis with Intelligent Data Reduction". ISPRS International Journal of Geo-Information 9, nr 5 (6.05.2020): 299. http://dx.doi.org/10.3390/ijgi9050299.
Pełny tekst źródłaTang, Yansong, Xingyu Liu, Xumin Yu, Danyang Zhang, Jiwen Lu i Jie Zhou. "Learning from Temporal Spatial Cubism for Cross-Dataset Skeleton-based Action Recognition". ACM Transactions on Multimedia Computing, Communications, and Applications 18, nr 2 (31.05.2022): 1–24. http://dx.doi.org/10.1145/3472722.
Pełny tekst źródłaIsthigosah, Maie, Andi Sunyoto i Tonny Hidayat. "Image Augmentation for BreaKHis Medical Data using Convolutional Neural Networks". sinkron 8, nr 4 (1.10.2023): 2381–92. http://dx.doi.org/10.33395/sinkron.v8i4.12878.
Pełny tekst źródłaLaporte, Matias, Martin Gjoreski i Marc Langheinrich. "LAUREATE". Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 7, nr 3 (27.09.2023): 1–41. http://dx.doi.org/10.1145/3610892.
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