Published in: Conference: 2025 IEEE International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN)
Description: The model was evaluated using important measures like F1 score, accuracy, precision, recall, and sensitivity. Res-BRNet shows great accuracy, precision, and F1 scores in the experimental findings showing 98.83% in the classifying of gliomas, meningiomas, and pituitary tumors.
Year: 2025
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Published in: Under Review
Description: This study achieved state-of-the-art accuracy of 94% on a larger dataset with 5,817 labels from online and 99.37% on a self-collected smaller dataset with 68 labels and 1,564 augmented samples.
Year: NOT AVALAIBLE
Published in: NOT YET
Description: NOT YET
Year: NOT AVALAIBLE