Advanced deep learning methods

This article introduces an advanced method in the field of facial recognition, using a unique technique that combines Convolutional Neural Networks (CNN) and Multilayer Perceptron (MLP) to integrate different perspectives.

9p viambani 18-06-2024 5 1   Download

Minerals, with their intricate chemical compositions and crystalline structures, play a pivotal role in diverse chemical processes, applications, and research. Traditionally, their classification was achieved through observational and chemical techniques. However, with increasing sample sizes, these methods often proved time-consuming. Recent advances in Artificial Intelligence (AI) and Deep Learning (DL) promise transformative improvements in the speed and accuracy of mineral classification.

14p vigojek 02-02-2024 4 1   Download

Truss analysis has been well investigated by researchers and engineers with a large number of structural analysis software that can quickly and reliably provide analysis results. However, these methods require either expensive commercial software or self-developed in-house codes based on structural expertise along with advanced programming skills.

11p viberkshire 09-08-2023 6 3   Download

Recent technological advances have enabled DNA methylation to be assayed at single-cell resolution. However, current protocols are limited by incomplete CpG coverage and hence methods to predict missing methylation states are critical to enable genome-wide analyses. We report DeepCpG, a computational approach based on deep neural networks to predict methylation states in single cells.

13p vialfrednobel 29-01-2022 20 0   Download

With the developments of DNA sequencing technology, large amounts of sequencing data have been produced that provides unprecedented opportunities for advanced association studies between somatic mutations and cancer types/subtypes which further contributes to more accurate somatic mutation based cancer typing (SMCT). In existing SMCT methods however, the absence of high-level feature extraction is a major obstacle in improving the classification performance.

8p vitzuyu2711 29-09-2021 9 1   Download

Automatic segmentation and localization of lesions in mammogram (MG) images are challenging even with employing advanced methods such as deep learning (DL) methods. We developed a new model based on the architecture of the semantic segmentation U-Net model to precisely segment mass lesions in MG images.

19p viwyoming2711 16-12-2020 11 1   Download

The resulting model is a Document Retriever, called QASA, which is then integrated with a machine reader to form a complete open-domain QA system. Our system is thoroughly evaluated using QUASAR-T dataset and shows surpassing results compared to other state-of-the-art methods.

67p tamynhan1 13-06-2020 18 3   Download

In the present study, Deep Learning (DL) algorithm or Deep Neural Networks (DNN), one of the most powerful techniques in Machine Learning (ML), is employed for estimation of ultimate load factor of nonlinear inelastic steel truss. Datasets consisting of training and test data are created based on advanced analysis. In datasets, input data are the member cross-sections of the truss members and output data is the ultimate load factor of the whole structure. An example of a planar 39-bar steel truss is studied to demonstrate the efficiency and accuracy of the DL method.

11p elandorr 05-12-2019 20 0   Download