CryoNuSeg: A Dataset for Nuclei Instance Segmentation of Cryosectioned H&E-Stained Histological Images
Sign Up to like & getrecommendations! Published in 2021 at "Computers in biology and medicine"
DOI: 10.1016/j.compbiomed.2021.104349
Abstract: Nuclei instance segmentation plays an important role in the analysis of hematoxylin and eosin (H&E)-stained images. While supervised deep learning (DL)-based approaches represent the state-of-the-art in automatic nuclei instance segmentation, annotated datasets are required to… read more here.
Keywords: cryosectioned stained; segmentation; nuclei instance; dataset ... See more keywords
Learning Panoptic Segmentation Through Feature Discriminability
Sign Up to like & getrecommendations! Published in 2022 at "Pattern Recognition"
DOI: 10.1016/j.patcog.2021.108240
Abstract: Abstract Panoptic segmentation has attracted increasing attention as a joint task of semantic and instance segmentation. However, previous works have not noticed that the different requirements for semantic and instance segmentation can lead to conflict… read more here.
Keywords: feature discriminability; segmentation; instance segmentation; instance ... See more keywords
Synthetic-to-real: instance segmentation of clinical cluster cells with unlabeled synthetic training
Sign Up to like & getrecommendations! Published in 2022 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btac219
Abstract: Abstract Motivation The presence of tumor cell clusters in pleural effusion may be a signal of cancer metastasis. The instance segmentation of single cell from cell clusters plays a pivotal role in cluster cell analysis.… read more here.
Keywords: cell; instance segmentation; cluster; segmentation ... See more keywords
Weakly Supervised Instance Segmentation Based on Two-Stage Transfer Learning
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DOI: 10.1109/access.2020.2969480
Abstract: Weakly supervised instance segmentation, which could greatly decrease financial and time cost, is one of fundamental computer vision tasks. State-of-the-art methods mainly concentrate on improving the quality of generated pixel level labels, namely masks, using… read more here.
Keywords: transfer learning; instance segmentation; weakly supervised; segmentation ... See more keywords
FCENet: An Instance Segmentation Model for Extracting Figures and Captions From Material Documents
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DOI: 10.1109/access.2020.3046496
Abstract: A critical ideology of the existing Material Genome Project refers to the application of data and artificial intelligence to facilitate material innovation. The lack of data hinders the development of novel materials. The figures and… read more here.
Keywords: fcenet; instance segmentation; figures captions; captions material ... See more keywords
SIIS-SLAM: A Vision SLAM Based on Sequential Image Instance Segmentation
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DOI: 10.1109/access.2022.3187541
Abstract: Simultaneous localization and mapping (SLAM) is a fundamental function of intelligent robots. To reduce the influence of dynamic objects on SLAM in dynamic environments, this study pro-poses a visual SLAM based on sequential image segmentation,… read more here.
Keywords: siis slam; instance segmentation; slam; sequential image ... See more keywords
Combine Supervised Edge and Semantic Supplement for Instance Segmentation
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DOI: 10.1109/access.2022.3201345
Abstract: Two-stage instance segmentation method outperforms the one-stage counterpart on complex occasions. However, we found that the RoIAlign operation identifies the feature map to smaller size, and the convolution or up-sampling causes the loss of detailed… read more here.
Keywords: instance segmentation; supervised edge; combine supervised; segmentation ... See more keywords
Quantifying the Effects of Ground Truth Annotation Quality on Object Detection and Instance Segmentation Performance
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3256723
Abstract: Fully-supervised object detection and instance segmentation models have accomplished notable results on large-scale computer vision benchmark datasets. However, fully-supervised machine learning algorithms’ performances are immensely dependent on the quality of the training data. Preparing computer… read more here.
Keywords: instance segmentation; detection instance; object detection; instance ... See more keywords
A New Approach for Fundus Lesions Instance Segmentation Based on Mask R-CNN X101-FPN Pre-Trained Architecture
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DOI: 10.1109/access.2023.3271895
Abstract: Diabetic retinopathy is one of the main causes of vision loss, and it can be identified through ophthalmological examinations that aim to locate the presence of retinal lesions such as Microaneurysms, Hemorrhages, Soft Exudates, and… read more here.
Keywords: inline formula; approach; instance segmentation; tex math ... See more keywords
Edge-Assisted Real-Time Instance Segmentation for Resource-Limited IoT Devices
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3199921
Abstract: Instance segmentation exploits the potential of Internet of Things (IoT) devices to perceive environmental semantic information and achieve complex interactions with the physical world. However, IoT devices usually have limited computing and storage resources and… read more here.
Keywords: instance segmentation; resource limited; iot devices; instance ... See more keywords
Bounding Box-Free Instance Segmentation Using Semi-Supervised Iterative Learning for Vehicle Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2022.3169128
Abstract: Vehicle classification is a hot computer vision topic, with studies ranging from ground-view to top-view imagery. Top-view images allow understanding city patterns, traffic management, among others. However, there are some difficulties for pixel-wise classification: most… read more here.
Keywords: vehicle; iterative learning; segmentation; instance segmentation ... See more keywords