Combining deep-wavelet neural networks and support-vector machines to classify breast lesions in thermography images

Author:

de Santana Maíra Araújo,de Freitas Barbosa Valter Augusto,de Cássia Fernandes de Lima Rita,dos Santos Wellington PinheiroORCID

Funder

Fundação de Amparo á Ciência e Tecnologia do Estado de Pernambuco

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

Springer Science and Business Media LLC

Subject

Biomedical Engineering,Applied Microbiology and Biotechnology,Bioengineering,Biotechnology

Reference55 articles.

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2. Shrivastava SR, Shrivastava PS, Jegadeesh R, et al. Ensuring early detection of cancer in low-and middle-income nations: World Health Organization. Arch Med Health Sci. 2017;5(1):141.

3. Gonçalves JG, Siqueira ADSE, de Almeira Rocha IG, de Lima EFF, da Silva Alves L, da Silva BO, de Mendonça PEX, Merhy EE, Land MGP. Evolução histórica das políticas para o controle do câncer de mama no Brasil. DIVERSITATES International Journal 2016;8(1).

4. Maitra IK, Bandyopadhyay SK. Identification of abnormal masses in digital mammogram using statistical decision making. Hybrid Intelligence for Image Analysis and Understanding. 2017. p 339–68.

5. Bandyopadhyay SK. Survey on segmentation methods for locating masses in a mammogram image. Int J Comput Appl. 2010;9(11):25–8.

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1. A Review of Feature Selection and HyperparameterOptimization Techniques for Breast Cancer Detection on thermograms Images;2023 IEEE 6th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech);2023-11-21

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