Results 11 to 20 of about 479,142 (270)
Learning with Limited Annotations: A Survey on Deep Semi-Supervised Learning for Medical Image Segmentation [PDF]
Comput. Biol. Medicine, 2022 Medical image segmentation is a fundamental and critical step in many image-guided clinical approaches. Recent success of deep learning-based segmentation methods usually relies on a large amount of labeled data, which is particularly difficult and ...
Rushi Jiao +4 more
semanticscholar +1 more source
Dealing with Disagreements: Looking Beyond the Majority Vote in Subjective Annotations [PDF]
Transactions of the Association for Computational Linguistics, 2021 Majority voting and averaging are common approaches used to resolve annotator disagreements and derive single ground truth labels from multiple annotations.
A. Davani +2 more
semanticscholar +1 more source
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations [PDF]
International Journal of Computer Vision, 2016 Despite progress in perceptual tasks such as image classification, computers still perform poorly on cognitive tasks such as image description and question answering.
Ranjay Krishna +11 more
semanticscholar +1 more source
DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations [PDF]
Neural Information Processing Systems, 2022 Solving multi-label recognition (MLR) for images in the low-label regime is a challenging task with many real-world applications. Recent work learns an alignment between textual and visual spaces to compensate for insufficient image labels, but loses ...
Ximeng Sun, Ping Hu, Kate Saenko
semanticscholar +1 more source
CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT [PDF]
Conference on Empirical Methods in Natural Language Processing, 2020 The extraction of labels from radiology text reports enables large-scale training of medical imaging models. Existing approaches to report labeling typically rely either on sophisticated feature engineering based on medical domain knowledge or manual ...
Akshay Smit +5 more
semanticscholar +1 more source
FreeSOLO: Learning to Segment Objects without Annotations [PDF]
Computer Vision and Pattern Recognition, 2022 Instance segmentation is a fundamental vision task that aims to recognize and segment each object in an image. However, it requires costly annotations such as bounding boxes and segmentation masks for learning.
Xinlong Wang +6 more
semanticscholar +1 more source
Nucleic Acids Res., 2020 The mammalian mitochondrial proteome is under dual genomic control, with 99% of proteins encoded by the nuclear genome and 13 originating from the mitochondrial DNA (mtDNA).
S. Rath +31 more
semanticscholar +1 more source
Weakly-Supervised Camouflaged Object Detection with Scribble Annotations [PDF]
AAAI Conference on Artificial Intelligence, 2022 Existing camouflaged object detection (COD) methods rely heavily on large-scale datasets with pixel-wise annotations. However, due to the ambiguous boundary, annotating camouflage objects pixel-wisely is very time-consuming and labor-intensive, taking ...
Ruozhen He +3 more
semanticscholar +1 more source
VirTex: Learning Visual Representations from Textual Annotations [PDF]
Computer Vision and Pattern Recognition, 2020 The de-facto approach to many vision tasks is to start from pretrained visual representations, typically learned via supervised training on ImageNet. Recent methods have explored unsupervised pretraining to scale to vast quantities of unlabeled images ...
Karan Desai, Justin Johnson
semanticscholar +1 more source