Autism Spectrum Disorder (ASD) is a neurological disorder that affects a person's behavior and social interaction. Integrating machine learning algorithms with neuroimages a diagnosis method can be...doi:10.1007/978-3-030-46165-2_4Sakib Mostafa...
However, these methods are mostly supervised. In practical applications, annotating large amounts of data is a very time-consuming and laborious task. Furthermore, efficiently using a large amount of unlabeled data for hash learning is challenging. In this paper, we create a new autoencoder ...
Approximation methods, such as First Order Reliability Method (FORM), Second Order Reliability Method (SORM) [8] aim to improve computational efficiency by approximating the limit state equation through the utilization of Taylor expansion techniques. However, approximation methods may encounter challenges ...
When tested on real scRNA-seq datasets, AutoImpute performed competitively wrt., the existing single-cell imputation methods, on the grounds of expression recovery from subsampled data, cell-clustering accuracy, variance stabilization and cell-type separability....
is a significant advantage compared to most other deep learning (DL)-based CE methods, where perfect CSI during the training phase is a crucial prerequisite. Numerical simulations for hybrid and wideband systems demonstrate the excellent performance of the proposed methods compared to related estimators...
However, the lack of availability of the source training data and the cost of training a new model often prevents the use of known methods to solve user-specif i c domain shifts. Here, we ask whether we can design a model that, once distributed to users, can quickly adapt itself to ...
The curse of dimensionality is a central difficulty in many fields such as machine learning,pattern recognition and data mining etc.The dimensionality reduction method of characteristic data is one of the current research hotspots in data-driven calculation methods,which high-dimensional data is mapped...
such as Grad-CAM methods. This study investigated the use of a model that combined a VAE, which is well known for its good performance in image generation, and linear regression to more accurately represent the correlation between human aging and changes in the morphological features of teeth. ...
Despite their exciting performances, DNNs are not robust against adversarial attacks. They are specifically vulnerable to data poisoning attacks where attackers meddle with the initial training data, despite the multiple defensive methods available, such as defensive distillation. However, defensive ...
When tested on real scRNA-seq datasets, AutoImpute performed competitively wrt., the existing single-cell imputation methods, on the grounds of expression recovery from subsampled data, cell-clustering accuracy, variance stabilization and cell-type separability. 展开 ...