Results 51 to 60 of about 8,068,470 (297)

Semi-supervised learning in cancer diagnostics

Frontiers in Oncology, 2022
In cancer diagnostics, a considerable amount of data is acquired during routine work-up. Recently, machine learning has been used to build classifiers that are tasked with cancer detection and aid in clinical decision-making.
Jan-Niklas Eckardt, Jan-Niklas Eckardt, Martin Bornhäuser, Martin Bornhäuser, Martin Bornhäuser, Karsten Wendt, Karsten Wendt, Jan Moritz Middeke, Jan Moritz Middeke   +8 more
doaj   +1 more source

Semi-supervised few-shot learning approach for plant diseases recognition

Plant Methods, 2021
Background Learning from a few samples to automatically recognize the plant leaf diseases is an attractive and promising study to protect the agricultural yield and quality.
Yang Li, Xuewei Chao
doaj   +1 more source

A Survey On Semi-Supervised Learning Techniques [PDF]

International Journal of Computer Trends and Technology, 2014
5 Pages, 3 figures, Published with International Journal of Computer Trends and Technology (IJCTT)
V. Jothi Prakash, L. M. Nithya
openaire   +3 more sources

A semi-supervised spam mail detector [PDF]

, 2006
This document describes a novel semi-supervised approach to spam classification, which was successful at the ECML/PKDD 2006 spam classification challenge.
Pfahringer, Bernhard
core  

Pathways and pitfalls: a qualitative study of student experiences in biomedical science education

FEBS Open Bio, EarlyView.
Biomedical science students from underrepresented backgrounds face barriers including financial strain, disrupted laboratory access and cultural exclusion. Peer networks provide vital support when institutional systems are difficult to navigate. To create inclusive learning environments and achieve academic success, educators should blend active, hands‐
Olivia J. Russell, Cassy Ross, Panagiota S. Filippou, Bruno Silvester Lopes, Dominic Gilchrist, Paul Dean, Kamar Ameen‐Ali, Tora K. Smulders‐Srinivasan, Ahmad A. Khundakar   +8 more
wiley   +1 more source

Cardiac Imaging with Electrical Impedance Tomography (EIT) using Multilayer Perceptron Network

Jurnal Elektronika dan Telekomunikasi
This research explores the enhancement of Electrical Impedance Tomography (EIT) for cardiac imaging using Multilayer Perceptron (MLP) networks, focusing on supervised and semi-supervised learning approaches.
Amelia Putri Ristyawardani, Marlin Ramadhan Baidillah, Yudi Adityawarman, Pratondo Busono, Mochamad Adityo Rachmadi, Meta Yantidewi, Endah Rahmawati   +6 more
doaj   +1 more source

In-Context Semi-Supervised Learning

CoRR
There has been significant recent interest in understanding the capacity of Transformers for in-context learning (ICL), yet most theory focuses on supervised settings with explicitly labeled pairs. In practice, Transformers often perform well even when labels are sparse or absent, suggesting crucial structure within unlabeled contextual demonstrations.
Jiashuo Fan, Paul Rosu, Aaron T. Wang, Michael Li, Lawrence Carin, Xiang Cheng   +5 more
openaire   +3 more sources

Semi-supervised Learning with Bidirectional GANs [PDF]

, 2019
In this work we introduce a novel approach to train Bidirectional Generative Adversarial Model (BiGAN) in a semi-supervised manner. The presented method utilizes triplet loss function as an additional component of the objective function used to train discriminative data representation in the latent space of the BiGAN model.
Maciej Zamorski, Maciej Zieba
openaire   +2 more sources

Weakly Supervised Learning of Objects, Attributes and their Associations [PDF]

, 2014
. When humans describe images they tend to use combinations of nouns and adjectives, corresponding to objects and their associated attributes respectively.
Zhiyuan Shi, Yongxin Yang, Yang, Yongxin, Tao Xiang, Timothy M. Hospedales, Yang, Y, Hospedales, Timothy M, Xiang, Tao, Shi, Z, Xiang, T, Shi, Zhiyuan, Hospedales, TM   +11 more
core   +1 more source

Advancing Age Modulates Associations Between Cognitive Impairment and Brain Volumes in Early MS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Introduction Cognitive impairment is common in multiple sclerosis (MS), but manifestations following the first demyelinating event are relatively unexplored. We investigated cross‐sectional associations between magnetic resonance imaging (MRI)–derived brain volumes and the presence of cognitive impairment outcomes five years after the first ...
Piriyankan Ananthavarathan, Marco Pitteri, Michael Foster, Sara Collorone, Sara Salama, Elisa Colato, Ferran Prados, Baris Kanber, Marios Yiannakas, Claudia A. M. Gandini Wheeler‐Kingshott, Indran Davagnanam, Frederik Barkhof, Declan Chard, Olga Ciccarelli, Ahmed Toosy   +14 more
wiley   +1 more source