Výsledky vyhľadávania - Multiple-Instance Learning Algorithms

A robust and lightweight deep attention multiple instance learning algorithm for predicting genetic alterations Autor Guo, Bangwei, Li, Xingyu, Yang, Miaomiao, Zhang, Hong, Xu, Xu Steven

“… This paper presents a novel, lightweight Attention-based Multiple Instance Mutation Learning (AMIML…”
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Robust objectness tracking with weighted multiple instance learning algorithm Autor Yang, Honghong, Qu, Shiru, Zhu, Fumin, Zheng, Zunxin

“…A novel improved online weighted multiple instance learning algorithm(IWMIL) for visual tracking is proposed…”
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Fast Bundle Algorithm for Multiple-Instance Learning Autor Bergeron, C., Moore, G., Zaretzki, J., Breneman, C. M., Bennett, K. P.

“…We present a bundle algorithm for multiple-instance classification and ranking. These frameworks yield improved models on many problems possessing special structure…”
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Multiple-Instance Learning Algorithms for Computer-Aided Detection Autor Dundar, M. Murat, Fung, Glenn, Krishnapuram, Balaji, Rao, R. Bharat

“… Existing MIL algorithms are much too computationally expensive for these datasets. We describe CH, a framework for learning a convex hull representation of multiple instances that is significantly faster than existing MIL algorithms…”
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CAMIL: channel attention-based multiple instance learning for whole slide image classification Autor Mao, Jinyang, Xu, Junlin, Tang, Xianfang, Liu, Yongjin, Zhao, Heaven, Tian, Geng, Yang, Jialiang

“… Multiple instance learning (MIL) provides a robust framework for analyzing whole slide images with slide-level labels at gigapixel resolution…”
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The KMeansGraphMIL Model: A Weakly Supervised Multiple Instance Learning Model for Predicting Colorectal Cancer Tumor Mutational Burden Autor Chen, Linghao, Xiao, Huiling, Jiang, Jiale, Li, Bing, Liu, Weixiang, Huang, Wensheng

“… To provide an economical and rapid way to predict patients' TMB, the KMeansGraphMIL model was proposed based on weakly supervised multiple-instance learning…”
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mi-DS: Multiple-Instance Learning Algorithm Autor Nguyen, Dat T., Nguyen, Cao D., Hargraves, Rosalyn, Kurgan, Lukasz A., Cios, Krzysztof J.

“…Multiple-instance learning (MIL) is a supervised learning technique that addresses the problem of classifying bags of instances instead of single instances…”
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Beyond accuracy: Quantifying the reliability of multiple instance learning for whole slide image classification Autor Keshvarikhojasteh, Hassan, Aubreville, Marc, Bertram, Christof A, Pluim, Josien P W, Veta, Mitko

“… Multiple Instance Learning (MIL) models designed for Whole Slide Image (WSI) classification in computational pathology are rarely evaluated in terms of reliability…”
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Disentangled Pseudo-Bag Augmentation for Whole Slide Image Multiple Instance Learning Autor Dong, Jiuyang, Jiang, Junjun, Jiang, Kui, Li, Jiahan, Cai, Linghan, Zhang, Yongbing

“…As the predominant approach for pathological whole slide image (WSI) classification, multiple instance learning (MIL…”
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Patch Based Multiple Instance Learning Algorithm for Object Tracking Autor Wang, Zhenjie, Zhang, Hua, Wang, Li Jia

“…To deal with the problems of illumination changes or pose variations and serious partial occlusion, patch based multiple instance learning (P-MIL…”
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FR-MIL: Distribution Re-Calibration-Based Multiple Instance Learning With Transformer for Whole Slide Image Classification Autor Chikontwe, Philip, Kim, Meejeong, Jeong, Jaehoon, Jung Sung, Hyun, Go, Heounjeong, Jeong Nam, Soo, Park, Sang Hyun

“… WSI classification is generally addressed using multiple instance learning (MIL), alleviating the challenge of processing billions of pixels and curating rich annotations…”
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Comparison of an Attention-Based Multiple Instance Learning (MIL) With a Visual Transformer Model: Two Weakly Supervised Deep Learning (DL) Algorithms for the Detection of Histopathologic Lesions in the Rat Liver to Distinguish Normal From Abnormal Autor Funk, Juergen, Clement, Gregoire, Togninalli, Matteo, Cohen, Yaniv, Albrecht, Tom, Sullivan, Ruth, Pous, Josep Arus, Tecilla, Marco, Romero-Palomo, Fernando, Abramowski, Amadeusz, D'Annunzio, Angelo, Li, Yun Yvonna, Nguyen, Trung, Hu, Fangyao, Schumacher, Vanessa

“… Multiple instance learning (MIL) approaches, including a transformer variant, were tested to predict lesions within a weakly supervised framework…”
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Acoustic COVID-19 Detection Using Multiple Instance Learning Autor Reiter, Michael, Pernkopf, Franz

“… Subsequently, a Multiple Instance Learning (MIL) model based on self-attention is incorporated to make collective predictions for multiple time segments within each audio recording, taking advantage of longer durations…”
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Optimized multiple instance learning for brain tumor classification using weakly supervised contrastive learning Autor Lu, Kaoyan, Lin, Shiyu, Xue, Kaiwen, Huang, Duoxi, Ji, Yanghong

“… Multi-instance learning (MIL) has become the mainstream method for analyzing whole-slide images (WSIs…”
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When multiple instance learning meets foundation models: Advancing histological whole slide image analysis Autor Xu, Hongming, Wang, Mingkang, Shi, Duanbo, Qin, Huamin, Zhang, Yunpeng, Liu, Zaiyi, Madabhushi, Anant, Gao, Peng, Cong, Fengyu, Lu, Cheng

“…Deep multiple instance learning (MIL) pipelines are the mainstream weakly supervised learning methodologies for whole slide image (WSI) classification…”
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CoD-MIL: Chain-of-Diagnosis Prompting Multiple Instance Learning for Whole Slide Image Classification Autor Shi, Jiangbo, Li, Chen, Gong, Tieliang, Wang, Chunbao, Fu, Huazhu

“…Multiple instance learning (MIL) has emerged as a prominent paradigm for processing the whole slide image with pyramid structure and giga-pixel size in digital pathology…”
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EpicPred: predicting phenotypes driven by epitope-binding TCRs using attention-based multiple instance learning Autor Jeon, Jaemin, Yu, Suwan, Lee, Sangam, Kim, Sang Cheol, Jo, Hye-Yeong, Jung, Inuk, Kim, Kwangsoo

“…–epitope interactions to reduce false positives using the Open-set Recognition (OSR). Subsequently, multiple instance learning was used to identify TCR…”
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AttriMIL: Revisiting attention-based multiple instance learning for whole-slide pathological image classification from a perspective of instance attributes Autor Cai, Linghan, Huang, Shenjin, Zhang, Ye, Lu, Jinpeng, Zhang, Yongbing

“…Multiple instance learning (MIL) is a powerful approach for whole-slide pathological image (WSI…”
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Incorporating hierarchical information into multiple instance learning for patient phenotype prediction with single-cell RNA-sequencing data Autor Do, Chau, Lähdesmäki, Harri

“…Multiple instance learning (MIL) provides a structured approach to patient phenotype prediction with single-cell RNA-sequencing (scRNA-seq) data…”
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DepressionMIGNN: A Multiple-Instance Learning-Based Depression Detection Model with Graph Neural Networks Autor Zhao, Shiwen, Zhang, Yunze, Su, Yikai, Su, Kaifeng, Liu, Jiemin, Wang, Tao, Yu, Shiqi

“…The global prevalence of depression necessitates the application of technological solutions, particularly sensor-based systems, to augment scarce resources for…”
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