Search Results for author: Chinedu Innocent Nwoye

Found 8 papers, 6 papers with code

Dissecting Self-Supervised Learning Methods for Surgical Computer Vision

1 code implementation1 Jul 2022 Sanat Ramesh, Vinkle Srivastav, Deepak Alapatt, Tong Yu, Aditya Murali, Luca Sestini, Chinedu Innocent Nwoye, Idris Hamoud, Antoine Fleurentin, Georgios Exarchakis, Alexandros Karargyris, Nicolas Padoy

Correct transfer of these methods to surgery, as described and conducted in this work, leads to substantial performance gains over generic uses of SSL - up to 7% on phase recognition and 20% on tool presence detection - as well as state-of-the-art semi-supervised phase recognition approaches by up to 14%.

Self-Supervised Learning

Rendezvous: Attention Mechanisms for the Recognition of Surgical Action Triplets in Endoscopic Videos

5 code implementations7 Sep 2021 Chinedu Innocent Nwoye, Tong Yu, Cristians Gonzalez, Barbara Seeliger, Pietro Mascagni, Didier Mutter, Jacques Marescaux, Nicolas Padoy

To achieve this task, we introduce our new model, the Rendezvous (RDV), which recognizes triplets directly from surgical videos by leveraging attention at two different levels.

Action Triplet Recognition

Weakly Supervised Convolutional LSTM Approach for Tool Tracking in Laparoscopic Videos

1 code implementation4 Dec 2018 Chinedu Innocent Nwoye, Didier Mutter, Jacques Marescaux, Nicolas Padoy

Results: We build a baseline tracker on top of the CNN model and demonstrate that our approach based on the ConvLSTM outperforms the baseline in tool presence detection, spatial localization, and motion tracking by over 5. 0%, 13. 9%, and 12. 6%, respectively.

Instrument Recognition Surgical tool detection +2

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