Exploring Multiple Instance Learning (MIL): A brief survey
Abstract Multiple Instance Learning (MIL) is a learning paradigm, where training instances
are arranged in sets, called bags, and only bag-level labels are available during training …
are arranged in sets, called bags, and only bag-level labels are available during training …
Dual-perspective multi-instance embedding learning with adaptive density distribution mining
Multi-instance learning (MIL) is a potent framework for solving weakly supervised problems,
with bags containing multiple instances. Various embedding methods convert each bag into …
with bags containing multiple instances. Various embedding methods convert each bag into …
Deep transfer learning for kidney cancer diagnosis
Y Habchi, H Kheddar, Y Himeur, A Boukabou… - arXiv preprint arXiv …, 2024 - arxiv.org
Many incurable diseases prevalent across global societies stem from various influences,
including lifestyle choices, economic conditions, social factors, and genetics. Research …
including lifestyle choices, economic conditions, social factors, and genetics. Research …
Transformer based multiple superpixel-instance learning for weakly supervised segmenting lesions of interstitial lung disease
Automatic and accurate segmentation of lesions from high-resolution computed tomography
(HRCT) images play a critical role in diagnosis of interstitial lung disease (ILD). Fully …
(HRCT) images play a critical role in diagnosis of interstitial lung disease (ILD). Fully …
Dictionary-based multi-instance learning method with universum information
F Cao, B Liu, K Wang, Y Xiao, J He, J Xu - Information Sciences, 2024 - Elsevier
Multi-instance learning (MIL) is a generalized form of supervised learning that attempts to
extract useful information from sets of instances, known as bags. In practice, besides positive …
extract useful information from sets of instances, known as bags. In practice, besides positive …