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Facial Image Augmentation from Sparse Line Features Using Small Training Data
Data collection is expensive in many research fields. Data augmentation from a very small dataset, such as synthesising realistic images from limited...
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EEG-Based Depression Detection with a Synthesis-Based Data Augmentation Strategy
Recently, Electroencephalography (EEG) is wildly used in depression detection. Researchers have successfully used machine learning methods to build...
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Advanced backward planning with custom-milled individual allogeneic block augmentation for maxillary full-arch osteoplasty and dental implantation:a 3-year follow-up
In the case of maxillary involution, augmentation is necessary for implant-supported prosthetics. The use of bone grafts is standard; customized...
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Grape leaf disease identification with sparse data via generative adversarial networks and convolutional neural networks
The main challenge in deep learning related to the identification of grape leaf diseases is how to achieve good performance in the case of available...
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Comparison of methods for deriving phenotypes from incomplete observation data with an application to age at puberty in dairy cattle
BackgroundMany phenotypes in animal breeding are derived from incomplete measures, especially if they are challenging or expensive to measure...
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FreeHi-C simulates high-fidelity Hi-C data for benchmarking and data augmentation
The ability to simulate high-throughput chromatin conformation (Hi-C) data is foundational for benchmarking Hi-C data analysis methods. Here we...
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Real-Time Data Augmentation Based Transfer Learning Model for Breast Cancer Diagnosis Using Histopathological Images
The Real-time automated medical image diagnosis system could assist pathologist for speed-up diagnosis process for confirming the findings. In this...
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scFSNN: a feature selection method based on neural network for single-cell RNA-seq data
While single-cell RNA sequencing (scRNA-seq) allows researchers to analyze gene expression in individual cells, its unique characteristics like...
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RNA contact prediction by data efficient deep learning
On the path to full understanding of the structure-function relationship or even design of RNA, structure prediction would offer an intriguing...
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scCoRR: A Data-Driven Self-correction Framework for Labeled scRNA-Seq Data
Single-cell RNA sequencing (scRNA-seq) data serves as the foundation for many studies investigating cellular heterogeneity. Numerous methodologies...
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EvoAug: improving generalization and interpretability of genomic deep neural networks with evolution-inspired data augmentations
Deep neural networks (DNNs) hold promise for functional genomics prediction, but their generalization capability may be limited by the amount of...
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Data-driven regularization lowers the size barrier of cryo-EM structure determination
Macromolecular structure determination by electron cryo-microscopy (cryo-EM) is limited by the alignment of noisy images of individual particles....
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Genetic diversity dissection and population structure analysis for augmentation of bread wheat (Triticum aestivum L.) germplasm using morpho-molecular markers
For wheat improvement, knowledge of diversity patterns and evolutionary relationships among the germplasm is essential for the sustainable...
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InClust+: the deep generative framework with mask modules for multimodal data integration, imputation, and cross-modal generation
BackgroundWith the development of single-cell technology, many cell traits can be measured. Furthermore, the multi-omics profiling technology could...
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Multispectral-derived genotypic similarities from budget cameras allow grain yield prediction and genomic selection augmentation in single and multi-environment scenarios in spring wheat
With abundant available genomic data, genomic selection has become routine in many plant breeding programs. Multispectral data captured by UAVs...
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DeepAEG: a model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies
MotivationThe prediction of cancer drug response is a challenging subject in modern personalized cancer therapy due to the uncertainty of drug...
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TomoTwin: generalized 3D localization of macromolecules in cryo-electron tomograms with structural data mining
Cryogenic-electron tomography enables the visualization of cellular environments in extreme detail, however, tools to analyze the full amount of...
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Genome-Wide Association Studies in Arabidopsis thaliana: Statistical Analysis and Network-Based Augmentation of Signals
Genome-wide association studies (GWAS) have proven effective at identifying genetic variants and genes that are associated with phenotypes in humans,...
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Augmentation in fragrant agarwood oil quality by fermentation with a microbial consortium of bacterium (Microbacterium oxydans) and fungus (Penicillium aethiopicum)
Agarwood oil is considered to be one of the costliest essential oils, produced by hydro-distillation of agarwood chips from resin impregnated wood...
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Contrastive Masked Graph Autoencoders for Spatial Transcriptomics Data Analysis
Spatial transcriptomics is an emerging genomics technology aimed at revealing the spatial distribution of gene expression at the tissue or cellular...