Results 251 to 260 of about 342,749 (263)

Robust semi-automatic vessel tracing in the human retinal image by an instance segmentation neural network. [PDF]

Sci Adv
Chen S, Hoang L, Kashani AH, Yi J.
europepmc   +1 more source

Leaf area estimation in small-seeded broccoli using a lightweight instance segmentation framework based on improved YOLOv11-AreaNet. [PDF]

Front Plant Sci
Zhang Y, Li Y, Cao X, Wang Z, Chen J, Li Y, Zhong Z, Bai R, Yang P, Pan F, Fu X.   +10 more
europepmc   +1 more source

Nuclear instance segmentation and tracking for preimplantation mouse embryos.

Development
Nunley H, Shao B, Denberg D, Grover P, Singh J, Avdeeva M, Joyce B, Kim-Yip R, Kohrman A, Biswas A, Watters A, Gal Z, Kickuth A, Chalifoux M, Shvartsman SY, Brown LM, Posfai E.   +16 more
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Human Instance Segmentation

2021
Currently, the more popular instance segmentation frameworks are based on powerful object detection methods, such as Faster R-CNN, Mask R-CNN, etc. Although they use different methods and different structures, these methods are roughly similar: first generating multiple regions proposal in the image, and then using the non-maximum suppression algorithm
Chengguo Ju, Guodong Wang
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Attentive neural cell instance segmentation

Medical Image Analysis, 2019
Neural cell instance segmentation, which aims at joint detection and segmentation of every neural cell in a microscopic image, is essential to many neuroscience applications. The challenge of this task involves cell adhesion, cell distortion, unclear cell contours, low-contrast cell protrusion structures, and background impurities.
Jingru Yi, Pengxiang Wu, Menglin Jiang, Qiaoying Huang, Daniel J. Hoeppner, Dimitris N. Metaxas   +5 more
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Single-stage Instance Segmentation

ACM Transactions on Multimedia Computing, Communications, and Applications, 2020
Albeit the highest accuracy of object detection is generally acquired by multi-stage detectors, like R-CNN and its extension approaches, the single-stage object detectors also achieve remarkable performance with faster execution and higher scalability.
Feng Lin, Bin Li, Wengang Zhou, Houqiang Li, Yan Lu   +4 more
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Efficient Instance Segmentation Network

2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS), 2020
We present an efficient, flexible, fast and accurate framework for real-time instance segmentation. We call it Efficient Instance Segmentation Network, denoted as EISNET. Our method is motivated by the Mask R-CNN and YOLACT. Mask R-CNN enables instance segmentation by adding an extra branch at the Faster R-CNN framework to produce mask for each object.
Chenquan Huang, Weiping Wu, Zhihua Lei
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Portrait Instance Segmentation for Mobile Devices

2019 IEEE International Conference on Multimedia and Expo (ICME), 2019
Accurate and efficient portrait instance segmentation has become a crucial enabler for many multimedia applications on mobile devices. We present a novel convolutional neural network (CNN) architecture to explicitly address the long standing problems in portrait segmentation, i.e., semantic coherence and boundary localization.
Lingyu Zhu, Tinghuai Wang, Emre Aksu, Joni-Kristian Kamarainen   +3 more
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Multi-Stage Instance Segmentation

2022 13th International Conference on Information and Communication Technology Convergence (ICTC), 2022
Guohua Zhu, Suk Chan Kim
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Instance Segmentation with BoundaryNet

2023
Teodor Boyadzhiev, Krassimira Ivanova
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