1 code implementation • 6 Feb 2023 • Joao Cartucho, Alistair Weld, Samyakh Tukra, Haozheng Xu, Hiroki Matsuzaki, Taiyo Ishikawa, Minjun Kwon, Yong Eun Jang, Kwang-Ju Kim, Gwang Lee, Bizhe Bai, Lueder Kahrs, Lars Boecking, Simeon Allmendinger, Leopold Muller, Yitong Zhang, Yueming Jin, Sophia Bano, Francisco Vasconcelos, Wolfgang Reiter, Jonas Hajek, Bruno Silva, Estevao Lima, Joao L. Vilaca, Sandro Queiros, Stamatia Giannarou
This assessment uses benchmarking metrics that were purposely developed for this challenge, to verify the efficacy of unsupervised deep learning algorithms in tracking soft-tissue.
1 code implementation • CVPR 2023 • Samyakh Tukra, Frederick Hoffman, Ken Chatfield
We present an extension to masked autoencoders (MAE) which improves on the representations learnt by the model by explicitly encouraging the learning of higher scene-level features.
Ranked #2 on Self-Supervised Image Classification on ImageNet (finetuned) (using extra training data)
Representation Learning Self-Supervised Image Classification
no code implementations • 18 Dec 2019 • Tianhong Dai, Kai Arulkumaran, Tamara Gerbert, Samyakh Tukra, Feryal Behbahani, Anil Anthony Bharath
Furthermore, even with an improved saliency method introduced in this work, we show that qualitative studies may not always correspond with quantitative measures, necessitating the combination of inspection tools in order to provide sufficient insights into the behaviour of trained agents.