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                <text>Conference Papers</text>
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              <text>Brain Tumor Detection using Hyper Parameter Tuning and Transfer Learning</text>
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              <text>Brain Tumor; Deep Learning; EffcientNetB7; EfficientNetV2; MobileNetv3</text>
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              <text>Brain Tumor is the development of abnormal cells in our brain. There are cancerous and noncancerous brain tumors. Because they can press against healthy brain tissue or spread there, brain tumors are harmful. The early diagnosis of brain tumors is a highly challenging assignment for radiologists. The typical size of a brain tumor doubles in just twenty-five days due to its rapid growth. If not properly cared for, the patient's survival rate typically does not exceed six months. It may quickly result in death. For the purpose of early brain tumor identification, an automatic method is necessary. In this study, an automated strategy is suggested for quickly distinguishing between malignant and non-cancerous brain images. Most of the time, it can be treated if caught during the early stages. Hence the need for more and improved brain tumor detection. The most crucial part here is image processing. The medical images obtained during the test have to be appropriately analysed. Various methods such as MobileNet, EfficientNetB7, and EfficientNetV2 have been used and their efficiency has been analysed. Here we classify the dataset containing 300 images into two. The suggested system will offer improved clinical support for the field of medicine.   2023 IEEE.</text>
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              <text>Nasar N.; Thiruthuvanathan M.M.; Pauls A.</text>
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              <text>Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>2023-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1109/InC457730.2023.10263136" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/InC457730.2023.10263136&lt;/a&gt;
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              <text>ISBN: 979-835033577-4</text>
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              <text>Nasar N., CHRIST(Deemed to Be University), Computer Science and Engineering, Bengaluru, India; Thiruthuvanathan M.M., CHRIST(Deemed to Be University), Computer Science and Engineering, Bengaluru, India; Pauls A., CHRIST(Deemed to Be University), Computer Science and Engineering, Bengaluru, India</text>
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