Results 51 to 60 of about 8,510,788 (298)
Emerging experimental and computational methods for studying redox‐regulated structural transitions
FEBS Letters, EarlyView.Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass +2 more
wiley +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingSemantic change detection (SCD) aims to find out where and what changes between a pair of co-registered remote sensing images. Compared to binary change detection, which only predicts the location of changes, SCD provides detailed from-to change ...
Yifei Si, Jie Jiang
doaj +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Recent long spells of high temperatures and drought-hit summers have fostered the conditions for an unprecedented outbreak of bark beetles in Europe.
Giuseppina Andresini +2 more
doaj +1 more source
Self-Trained LMT for Semisupervised Learning [PDF]
Computational Intelligence and Neuroscience, 2016 The most important asset of semisupervised classification methods is the use of available unlabeled data combined with a clearly smaller set of labeled examples, so as to increase the classification accuracy compared with the default procedure of supervised methods, which on the other hand use only the labeled data during the training phase.
Nikos Fazakis +3 more
openaire +3 more sources
FEBS Letters, EarlyView.Encapsulins are protein nanocompartments that play an important role in iron storage. In the Myxococcus xanthus encapsulin system, two cargo proteins called EncB and EncC contribute to iron mineralization. Here, we show that EncB and EncC generate iron‐containing minerals with distinct chemical compositions, suggesting that the composition of stored ...
Harry B. McDowell +2 more
wiley +1 more source
IEEE AccessMachine learning algorithms that assist in decision-making are becoming crucial in several areas, such as healthcare, finance, marketing, etc. Algorithms exposed to a larger and more relevant amount of training data tend to perform better.
Jose L. M. Perez +2 more
doaj +1 more source
IEEE Access, 2022 Multi-source Unsupervised Domain Adaptation (MUDA) is an approach aiming to transfer the knowledge obtained from multiple labeled source domains to an unlabeled target domain.
So Jeong Park +5 more
doaj +1 more source
Self Training with Ensemble of Teacher Models
CoRR, 2021 In order to train robust deep learning models, large amounts of labelled data is required. However, in the absence of such large repositories of labelled data, unlabeled data can be exploited for the same. Semi-Supervised learning aims to utilize such unlabeled data for training classification models.
Soumyadeep Ghosh +3 more
openaire +3 more sources
Molecular Oncology, EarlyView.This review summarizes the transcription factors, repressive chromatin‐modifying complexes, and epigenetic mechanisms that control fetal hemoglobin repression. Notably, many regulators of γ‐globin silencing also function in transcriptional and epigenetic networks that drive cancer, highlighting opportunities to translate advances in hemoglobinopathy ...
Meigen Yu +3 more
wiley +1 more source
Semi-Supervised Dim and Small Infrared Ship Detection Network Based on Haar Wavelet
IEEE Access, 2021 Traditional deep learning detection network has poor effect on the detection of infrared dim and small targets on the sea in the case of interference or bad weather.
Zizhuang Song +4 more
doaj +1 more source