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20202023
most citedAssessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge

19 citations · 48 across the 15 of their papers we have counts for

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Showing 2021Show all

7 papers · 1 filter

cs.LG2021★ 1 cited

Value Activation for Bias Alleviation: Generalized-activated Deep Double Deterministic Policy Gradients

Jiafei Lyu, Yu Yang, Jiangpeng Yan +1

It is vital to accurately estimate the value function in Deep Reinforcement Learning (DRL) such that the agent could execute proper actions instead of suboptimal ones. However, exi…

cs.CV2021

Implicit Feature Refinement for Instance Segmentation

Lufan Ma, Tiancai Wang, Bin Dong +3

We propose a novel implicit feature refinement module for high-quality instance segmentation. Existing image/video instance segmentation methods rely on explicitly stacked convolut…

eess.IV2021

All-Around Real Label Supervision: Cyclic Prototype Consistency Learning for Semi-supervised Medical Image Segmentation

Zhe Xu, Yixin Wang, Donghuan Lu +6

Semi-supervised learning has substantially advanced medical image segmentation since it alleviates the heavy burden of acquiring the costly expert-examined annotations. Especially,…

cs.CV2021

Double-Uncertainty Guided Spatial and Temporal Consistency Regularization Weighting for Learning-based Abdominal Registration

Zhe Xu, Jie Luo, Donghuan Lu +7

In order to tackle the difficulty associated with the ill-posed nature of the image registration problem, regularization is often used to constrain the solution space. For most lea…

cs.CV2021

A Coarse-to-Fine Instance Segmentation Network with Learning Boundary Representation

Feng Luo, Bin-Bin Gao, Jiangpeng Yan +1

Boundary-based instance segmentation has drawn much attention since of its attractive efficiency. However, existing methods suffer from the difficulty in long-distance regression.…

cs.LG2021

Efficient Continuous Control with Double Actors and Regularized Critics

Jiafei Lyu, Xiaoteng Ma, Jiangpeng Yan +1

How to obtain good value estimation is one of the key problems in Reinforcement Learning (RL). Current value estimation methods, such as DDPG and TD3, suffer from unnecessary over-…