{"list":"other","total":53,"rows":[{"id":"1412.6980","title":"Adam: A Method for Stochastic Optimization","created":"2014-12-22","cited_by_count":37240},{"id":"1505.04597","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","created":"2015-05-18","cited_by_count":19713},{"id":"1610.02391","title":"Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization","created":"2016-10-07","cited_by_count":6733},{"id":"1505.07818","title":"Domain-Adversarial Training of Neural Networks","created":"2015-05-28","cited_by_count":3044},{"id":"1409.7495","title":"Unsupervised Domain Adaptation by Backpropagation","created":"2014-09-26","cited_by_count":1917},{"id":"1606.06650","title":"3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation","created":"2016-06-21","cited_by_count":1476},{"id":"1502.02791","title":"Learning Transferable Features with Deep Adaptation Networks","created":"2015-02-10","cited_by_count":1329},{"id":"1702.05464","title":"Adversarial Discriminative Domain Adaptation","created":"2017-02-17","cited_by_count":1311},{"id":"1702.05747","title":"A Survey on Deep Learning in Medical Image Analysis","created":"2017-02-19","cited_by_count":1186},{"id":"1711.03213","title":"CyCADA: Cycle-Consistent Adversarial Domain Adaptation","created":"2017-11-08","cited_by_count":1082},{"id":"2002.08546","title":"Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation","created":"2020-02-20","cited_by_count":848},{"id":"1703.10593","title":"Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks","created":"2017-03-30","cited_by_count":707},{"id":"1811.12833","title":"ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation","created":"2018-11-30","cited_by_count":623},{"id":"1802.10349","title":"Learning to Adapt Structured Output Space for Semantic Segmentation","created":"2018-02-28","cited_by_count":584},{"id":"1904.10620","title":"Bidirectional Learning for Domain Adaptation of Semantic Segmentation","created":"2019-04-24","cited_by_count":308},{"id":"1809.09478","title":"Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation","created":"2018-09-25","cited_by_count":295},{"id":"2004.04393","title":"Universal Source-Free Domain Adaptation","created":"2020-04-09","cited_by_count":220},{"id":"1510.02192","title":"Simultaneous Deep Transfer Across Domains and Tasks","created":"2015-10-08","cited_by_count":206},{"id":"1704.01705","title":"Generate To Adapt: Aligning Domains using Generative Adversarial Networks","created":"2017-04-06","cited_by_count":183},{"id":"1804.06353","title":"Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis","created":"2018-04-17","cited_by_count":179},{"id":"2012.06166","title":"Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?","created":"2020-12-11","cited_by_count":135},{"id":"2002.02255","title":"Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation","created":"2020-02-06","cited_by_count":134},{"id":"1612.08894","title":"Unsupervised domain adaptation in brain lesion segmentation with adversarial networks","created":"2016-12-28","cited_by_count":125},{"id":"2007.02035","title":"Shape-aware Meta-learning for Generalizing Prostate MRI Segmentation to Unseen Domains","created":"2020-07-04","cited_by_count":124},{"id":"1803.09569","title":"On Regularized Losses for Weakly-supervised CNN Segmentation","created":"2018-03-26","cited_by_count":121},{"id":"1903.12212","title":"All about Structure: Adapting Structural Information across Domains for Boosting Semantic Segmentation","created":"2019-03-26","cited_by_count":104},{"id":"2004.04668","title":"Test-Time Adaptable Neural Networks for Robust Medical Image Segmentation","created":"2020-04-09","cited_by_count":102},{"id":"1902.07880","title":"Evaluation of Algorithms for Multi-Modality Whole Heart Segmentation: An Open-Access Grand Challenge","created":"2019-02-21","cited_by_count":100},{"id":"1904.06346","title":"Prior-aware Neural Network for Partially-Supervised Multi-Organ Segmentation","created":"2019-04-12","cited_by_count":88},{"id":"1605.07866","title":"DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networks","created":"2016-05-25","cited_by_count":79},{"id":"1804.08286","title":"Fully Convolutional Adaptation Networks for Semantic Segmentation","created":"2018-04-23","cited_by_count":75},{"id":"1711.10288","title":"Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation","created":"2017-11-28","cited_by_count":71},{"id":"1810.06498","title":"SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth","created":"2018-10-15","cited_by_count":68},{"id":"1805.04628","title":"Constrained-CNN losses for weakly supervised segmentation","created":"2018-05-12","cited_by_count":62},{"id":"2007.15176","title":"Domain Adaptive Semantic Segmentation Using Weak Labels","created":"2020-07-30","cited_by_count":56},{"id":"2005.03697","title":"Source-Relaxed Domain Adaptation for Image Segmentation","created":"2020-05-07","cited_by_count":52},{"id":"1701.00794","title":"Constrained Deep Weak Supervision for Histopathology Image Segmentation","created":"2017-01-03","cited_by_count":51},{"id":"1806.07201","title":"Task Driven Generative Modeling for Unsupervised Domain Adaptation: Application to X-ray Image Segmentation","created":"2018-06-11","cited_by_count":49},{"id":"1812.09953","title":"A Curriculum Domain Adaptation Approach to the Semantic Segmentation of Urban Scenes","created":"2018-12-24","cited_by_count":43},{"id":"2004.06816","title":"Bounding boxes for weakly supervised segmentation: Global constraints get close to full supervision","created":"2020-04-14","cited_by_count":40},{"id":"1810.04246","title":"Deep clustering: On the link between discriminative models and K-means","created":"2018-10-09","cited_by_count":37},{"id":"2010.01926","title":"Test-time Unsupervised Domain Adaptation","created":"2020-10-05","cited_by_count":37},{"id":"1806.06029","title":"One-Shot Unsupervised Cross Domain Translation","created":"2018-06-15","cited_by_count":35},{"id":"2003.01995","title":"A Learning Strategy for Contrast-agnostic MRI Segmentation","created":"2020-03-04","cited_by_count":35},{"id":"2007.03632","title":"Scribble-based Domain Adaptation via Co-segmentation","created":"2020-07-07","cited_by_count":34},{"id":"1712.07695","title":"Adversarial Synthesis Learning Enables Segmentation Without Target Modality Ground Truth","created":"2017-12-20","cited_by_count":30},{"id":"2011.08018","title":"High-level Prior-based Loss Functions for Medical Image Segmentation: A Survey","created":"2020-11-16","cited_by_count":28},{"id":"1904.05236","title":"Curriculum semi-supervised segmentation","created":"2019-04-10","cited_by_count":27},{"id":"2107.00583","title":"Inter Extreme Points Geodesics for End-to-End Weakly Supervised Image Segmentation","created":"2021-07-01","cited_by_count":21},{"id":"2104.02488","title":"Weakly supervised segmentation with cross-modality equivariant constraints","created":"2021-04-06","cited_by_count":18},{"id":"2007.03162","title":"Self domain adapted network","created":"2020-07-07","cited_by_count":17},{"id":"2002.01690","title":"Entropy Minimization vs. Diversity Maximization for Domain Adaptation","created":"2020-02-05","cited_by_count":8},{"id":"2105.00859","title":"Beyond pixel-wise supervision for segmentation: A few global shape descriptors might be surprisingly good!","created":"2021-05-03","cited_by_count":5}],"next_cursor":null}