Results 21 to 30 of about 14,193 (215)

Addressing Imbalance in Weakly Supervised Multi-Label Learning

IEEE Access, 2019
Multi-label learning has been widely used in many fields to solve the problem of assigning multiple related categories to an instance. Nevertheless, the label for each training example is assumed complete in most of the current multi-label learning ...
Fang-Fang Luo, Wen-zhong Guo, Guo-Long Chen   +2 more
doaj   +1 more source

Reducing Label Dependency in Human Activity Recognition with Wearables: From Supervised Learning to Novel Weakly Self-Supervised Approaches

Sensors
Human activity recognition (HAR) using wearable sensors has advanced through various machine learning paradigms, each with inherent trade-offs between performance and labeling requirements.
Taoran Sheng, Manfred Huber
doaj   +1 more source

Hybrid weakly supervised learning with deep learning technique for detection of fake news from cyber propaganda

Array, 2023
Due to the emergence of social networking sites and social media platforms, there is faster information dissemination to the public. Unverified information is widely disseminated across social media platforms without any apprehension about the accuracy ...
Liyakathunisa Syed, Abdullah Alsaeedi, Lina A. Alhuri, Hutaf R. Aljohani   +3 more
doaj   +1 more source

Medical image segmentation using deep learning: A survey

IET Image Processing, 2022
Deep learning has been widely used for medical image segmentation and a large number of papers has been presented recording the success of deep learning in the field.
Risheng Wang, Tao Lei, Ruixia Cui, Bingtao Zhang, Hongying Meng, Asoke K. Nandi   +5 more
doaj   +1 more source

Learning Consistency From High-Confidence Pseudo-Labels for Weakly Supervised Object Localization

IEEE Access, 2023
Weakly supervised object localization (WSOL) tasks aim to classify and locate a single object under the supervision of only image-level labels. Pseudo-supervised learning methods have been shown to be effective for WSOL.
Kangbo Sun, Jie Zhu
doaj   +1 more source

Weakly supervised learning of semantic colour terms

IET Computer Vision, 2014
Recognition of visual attributes in images allows an image's information content to be expressed textually. This has benefits for web search and image archiving, especially since visual attributes transcend language barriers.
David Hanwell, Majid Mirmehdi
doaj   +1 more source

Instance-Aware Plant Disease Detection by Utilizing Saliency Map and Self-Supervised Pre-Training

Agriculture, 2022
Plant disease detection is essential for optimizing agricultural productivity and crop quality. With the recent advent of deep learning and large-scale plant disease datasets, many studies have shown high performance of supervised learning-based plant ...
Taejoo Kim, Hyeongjun Kim, Kyeonghoon Baik, Yukyung Choi   +3 more
doaj   +1 more source

Partial FAK suppression promotes tumor growth, an effect reversed by macrophage p110δ PI3K inactivation

Molecular Oncology, EarlyView.
Partial inhibition of focal adhesion kinase (FAK) can paradoxically promote tumor growth, rather than simply producing a weaker antitumor effect than that observed with strong FAK suppression. In breast cancer and melanoma models, targeting p110δ PI3K, particularly in macrophages, counteracted these tumor‐promoting effects, highlighting the importance ...
Lydia Xenou, Niki Tzenaki, Anna Tsapara, Maria Tzardi, Evangelia A. Papakonstanti   +4 more
wiley   +1 more source

A Weakly Supervised and Self-Supervised Learning Approach for Semantic Segmentation of Land Cover in Satellite Images with National Forest Inventory Data

Remote Sensing
National Forest Inventories (NFIs) provide valuable land cover (LC) information but often lack spatial continuity and an adequate update frequency. Satellite-based remote sensing offers a viable alternative, employing machine learning to extract thematic
Daniel Moraes, Manuel L. Campagnolo, Mário Caetano   +2 more
doaj   +1 more source

Point-Based Weakly Supervised Learning for Object Detection in High Spatial Resolution Remote Sensing Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Object detection is challenging in high spatial resolution (HSR) remote sensing images that have a complex background and irregular object locations.
Youyou Li, Binbin He, Farid Melgani, Teng Long   +3 more
doaj   +1 more source