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Found 7 papers, 1 papers with code
FuXi-S2S: An accurate machine learning model for global subseasonal forecasts
Skillful subseasonal forecasts beyond 2 weeks are crucial for a wide range of applications across various sectors of society.
Combinatorial optimization solving by coherent Ising machines based on spiking neural networks
Spiking neural network is a kind of neuromorphic computing that is believed to improve the level of intelligence and provide advantages for quantum computing.
AutoLaparo: A New Dataset of Integrated Multi-tasks for Image-guided Surgical Automation in Laparoscopic Hysterectomy
In addition, we provide experimental results with state-of-the-art models as reference benchmarks for further model developments and evaluations on this dataset.
Stereo Dense Scene Reconstruction and Accurate Localization for Learning-Based Navigation of Laparoscope in Minimally Invasive Surgery
Then, we develop a dense visual reconstruction algorithm to represent the scene by surfels, estimate the laparoscope poses and fuse the depth maps into a unified reference coordinate for tissue reconstruction.
SurRoL: An Open-source Reinforcement Learning Centered and dVRK Compatible Platform for Surgical Robot Learning
Ten learning-based surgical tasks are built in the platform, which are common in the real autonomous surgical execution.
One to Many: Adaptive Instrument Segmentation via Meta Learning and Dynamic Online Adaptation in Robotic Surgical Video
To greatly increase the label efficiency, we explore a new problem, i. e., adaptive instrument segmentation, which is to effectively adapt one source model to new robotic surgical videos from multiple target domains, only given the annotated instruments in the first frame.
Relational Graph Learning on Visual and Kinematics Embeddings for Accurate Gesture Recognition in Robotic Surgery
Automatic surgical gesture recognition is fundamentally important to enable intelligent cognitive assistance in robotic surgery.
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Action Segmentation
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