Identification of Surgical Forceps Using YOLACT++
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-32439-0_15
Reference16 articles.
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2. Miura, S., et al.: Virtual shadow drawing system using augmented reality for laparoscopic surgery. Adv. Biomed. Eng. 11, 87–97 (2022). https://doi.org/10.14326/abe.11.87
3. Sarikaya, D., Corso, J.J., Guru, K.A.: Detection and localization of robotic tools in robot-assisted surgery videos using deep neural networks for region proposal and detection. IEEE Trans. Med. Imaging 36(7), 1542–1549 (2017). https://doi.org/10.1109/TMI.2017.2665671
4. Zhang, B., Wang, S., Dong, L., Chen, P.: Surgical tools detection based on modulated anchoring network in laparoscopic videos. IEEE Access 8, 23748–23758 (2020). https://doi.org/10.1109/ACCESS.2020.2969885
5. Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. Total Perform. Scorec. 159–183 (2020). https://doi.org/10.4324/9780080519340-12
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