Deep neural network structure
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In this article, we propose a generative model based on the adversarial network structure to enhance images for the RAD-DAR multi-target dataset. The results of comparisons and evaluations indicate that the images generated by the proposed method exhibit a high degree of similarity to the original images.
7p visergeyne 18-06-2024 2 0 Download
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Text categorization aims to automatically assign given text passages or documents to predetermined categories or subjects. Despite the wide array of techniques employed in classifying English text, there remains a dearth of research on Vietnamese text classification. This paper introduces a novel approach utilizing a Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) with a deep network structure for Vietnamese text classification.
10p viambani 18-06-2024 3 1 Download
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The taxonomic structure of microbial community sample is highly habitat-specific, making source tracking possible, allowing identification of the niches where samples originate. However, current methods face challenges when source tracking is scaled up.
17p viellison 28-03-2024 2 2 Download
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In this paper, a damage detection methodology for steel frame structures under fire load using time-history acceleration and machine learning (ML) is proposed. A randomly created dataset by finite element analysis (FEA) is utilized to develop deep neural networks (DNNs).
5p vicwell 06-03-2024 7 3 Download
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In this paper, a novel algorithm is proposed for the recognition of human faces and temperature using deep learning methods and thermal face images. The search-based method is developed for selection of an optimal structure and parameters of the convolutional neural network using the thermal images as the input.
6p viannee 02-08-2023 5 3 Download
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In this paper, an analysis of nearly 400 students’ records across 7 semesters of the same major in Hanoi University of Science and Technology is presented. Because of the university privacy policy, it is impossible to obtain students information other than their academic results.
5p vifalcon 18-05-2023 5 2 Download
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In this paper, the CNN-based model was developed to identify crack/non-crack images collected on the surface of a concrete structure. The CNN model was adapted from the pre-trained, open-sourced model developed by Google and distributed through TensorFlow.
4p vifalcon 16-05-2023 10 4 Download
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This project proposes two new methods of deep neural networks and handcrafted features for damage detection. The first method uses a convolution neural network (CNN) to extract deep features in time series and Long Short Term Memory (LSTM) network to find a statistically significant correlation of each lagged feature in time series data.
6p billyelliot 11-11-2021 27 1 Download
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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
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Circular RNAs (circRNAs) are special noncoding RNA molecules with closed loop structures. Compared with the traditional linear RNA, circRNA is more stable and not easily degraded.
18p vikentucky2711 24-11-2020 14 1 Download
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Cryo-electron microscopy (Cryo-EM) is widely used in the determination of the three-dimensional (3D) structures of macromolecules. Particle picking from 2D micrographs remains a challenging early step in the Cryo-EM pipeline due to the diversity of particle shapes and the extremely low signal-to-noise ratio of micrographs.
38p vikentucky2711 24-11-2020 11 2 Download
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Profiling gene expression in brain structures at various spatial and temporal scales is essential to understanding how genes regulate the development of brain structures. The Allen Developing Mouse Brain Atlas provides high-resolution 3-D in situ hybridization (ISH) gene expression patterns in multiple developing stages of the mouse brain.
10p vikentucky2711 24-11-2020 13 1 Download
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Single-particle cryo-electron microscopy (cryo-EM) has become a mainstream tool for the structural determination of biological macromolecular complexes. However, high-resolution cryo-EM reconstruction often requires hundreds of thousands of single-particle images.
10p viflorida2711 30-10-2020 11 1 Download
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Deep learning is one of the most powerful machine learning methods that has achieved the state-ofthe-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition.
13p viflorida2711 30-10-2020 11 2 Download
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Central to protein biology is the understanding of how structural elements give rise to observed function. The surfeit of protein structural data enables development of computational methods to systematically derive rules governing structural-functional relationships.
23p viflorida2711 30-10-2020 40 1 Download
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Direct prediction of the three-dimensional (3D) structures of proteins from one-dimensional (1D) sequences is a challenging problem. Significant structural characteristics such as solvent accessibility and contact number are essential for deriving restrains in modeling protein folding and protein 3D structure.
10p viconnecticut2711 29-10-2020 11 1 Download
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Protein structure can be described by backbone torsion angles: rotational angles about the N-Cα bond (φ) and the Cα-C bond (ψ) or the angle between Cαi-1-Cαi -Cαi+1 (θ) and the rotational angle about the Cαi -Cαi+1 bond (τ). Thus, their accurate prediction is useful for structure prediction and model refinement.
8p viconnecticut2711 28-10-2020 8 0 Download
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Cryo-electron microscopy (cryo-EM) has become a widely used tool for determining the structures of proteins and macromolecular complexes. To acquire the input for single-particle cryo-EM reconstruction, researchers must select hundreds of thousands of particles from micrographs.
14p vicoachella2711 27-10-2020 8 0 Download
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Ligand-binding proteins play key roles in many biological processes. Identification of protein-ligand binding residues is important in understanding the biological functions of proteins. Existing computational methods can be roughly categorized as sequence-based or 3D-structure-based methods.
12p vicoachella2711 27-10-2020 9 0 Download
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Protein secondary structure (PSS) is critical to further predict the tertiary structure, understand protein function and design drugs. However, experimental techniques of PSS are time consuming and expensive, and thus it’s very urgent to develop efficient computational approaches for predicting PSS based on sequence information alone.
12p vijisoo2711 27-10-2020 11 0 Download