Results 1 to 10 of about 34,169 (117)

Domain-agnostic weakly supervised surgical instrument segmentation [PDF]

Scientific Reports
Recent advancements in visual foundation models open new avenues in the field of surgical instrument segmentation in medical images. Segmentation foundation models provide high segmentation accuracy for objects of interest that are selected via prompts ...
Rebekka Peter, Doan Xuan Viet Pham, Philipp Matten, Erik Wu, Jonas Nienhaus, Felix Meissen, Martin J. Menten, Eleonora Tagliabue, Franziska Mathis-Ullrich   +8 more
doaj   +2 more sources

SPMF-Net: Weakly Supervised Building Segmentation by Combining Superpixel Pooling and Multi-Scale Feature Fusion

Remote Sensing, 2020
The lack of pixel-level labeling limits the practicality of deep learning-based building semantic segmentation. Weakly supervised semantic segmentation based on image-level labeling results in incomplete object regions and missing boundary information ...
Jie Chen, Fen He, Yi Zhang, Geng Sun, Min Deng   +4 more
doaj   +3 more sources

Automatic identification of diagnosis from hospital discharge letters via weakly supervised Natural Language Processing [PDF]

Scientific Reports
Identifying patient diagnoses from hospital discharge letters is essential for large-scale cohort selection and epidemiological research, but traditional supervised approaches require extensive manual annotation, which is often impractical for large ...
Vittorio Torri, Elisa Barbieri, Anna Cantarutti, Carlo Giaquinto, Francesca Ieva   +4 more
doaj   +2 more sources

Semi-Supervised Learning Matting Algorithm Based on Semantic Consistency of Trimaps

Applied Sciences, 2023
Image matting methods based on deep learning have made tremendous success. However, the success of previous image matting methods typically relies on a massive amount of pixel-level labeled data, which are time-consuming and costly to obtain.
Yating Kong, Jide Li, Liangpeng Hu, Xiaoqiang Li   +3 more
doaj   +1 more source

Weakly supervised machine learning

CAAI Transactions on Intelligence Technology, 2023
Supervised learning aims to build a function or model that seeks as many mappings as possible between the training data and outputs, where each training data will predict as a label to match its corresponding ground‐truth value.
Zeyu Ren, Shuihua Wang, Yudong Zhang
doaj   +1 more source

Weakly-supervised deep learning for ultrasound diagnosis of breast cancer

Scientific Reports, 2021
Conventional deep learning (DL) algorithm requires full supervision of annotating the region of interest (ROI) that is laborious and often biased. We aimed to develop a weakly-supervised DL algorithm that diagnosis breast cancer at ultrasound without ...
Jaeil Kim, Hye Jung Kim, Chanho Kim, Jin Hwa Lee, Keum Won Kim, Young Mi Park, Hye Won Kim, So Yeon Ki, You Me Kim, Won Hwa Kim   +9 more
doaj   +1 more source

Weakly supervised salient object detection via double object proposals guidance

IET Image Processing, 2021
The weakly supervised methods for salient object detection are attractive, since they greatly release the burden of annotating time‐consuming pixel‐wise masks.
Zhiheng Zhou, Yongfan Guo, Ming Dai, Junchu Huang, Xiangwei Li   +4 more
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WSPointNet: A multi-branch weakly supervised learning network for semantic segmentation of large-scale mobile laser scanning point clouds

International Journal of Applied Earth Observations and Geoinformation, 2022
Semantic segmentation of large-scale mobile laser scanning (MLS) point clouds is essential for urban scene understanding. However, most of the existing semantic segmentation methods require a large quantity of labeled data, which are labor-intensive and ...
Xiangda Lei, Haiyan Guan, Lingfei Ma, Yongtao Yu, Zhen Dong, Kyle Gao, Mahmoud Reza Delavar, Jonathan Li   +7 more
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Supervised and Weakly Supervised Deep Learning for Segmentation and Counting of Cotton Bolls Using Proximal Imagery

Sensors, 2022
The total boll count from a plant is one of the most important phenotypic traits for cotton breeding and is also an important factor for growers to estimate the final yield.
Shrinidhi Adke, Changying Li, Khaled M. Rasheed, Frederick W. Maier   +3 more
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A Survey of Weakly-supervised Image Semantic Segmentation Based on Image-level Labels

Taiyuan Ligong Daxue xuebao, 2021
According to the different ways of image-level label location inference, the weakly-supervised image semantic segmentation methods with image-level labels were divided into superpixel-based methods and classification-network-prior based methods.
Xinlin XIE, Dongxu YIN, Xinying XU, Xiaofang LIU, Chenyan LUO, Gang XIE   +5 more
doaj   +1 more source