608 Results Found

Accurate and reliable runoff forecasting is of great significance for hydropower station operation and watershed water resource allocation. However, various complex factors, such as climate conditions and human activities, constantly affect the forma...

Focusing on the identification of dynamic system stability, a hybrid neural network model is proposed in this research for the rotating stall phenomenon in an axial compressor. Based on the data fusion of the amplitude of the spatial mode, the nonlin...

Background: Current fMRI (functional magnetic resonance imaging)-driven brain information decoding for visual image reconstruction techniques faces issues such as poor structural fidelity, inadequate model generalization, and unnatural visual image r...

Along with the fourth industrial revolution, the use of unmanned aerial vehicles (UAV) has grown very rapidly over the past decade. With this rapid growth, studies using UAVs are underway in various areas. UAVs are more economical and effective when...

With the widespread adoption of 3D scanning technology, depth view-driven 3D reconstruction has become crucial for applications such as SLAM, virtual reality, and autonomous vehicles. However, due to the effects of self-occlusion and environmental oc...

The generation of High-Dynamic-Range (HDR) images is essential for capturing details at various brightness levels, but current reconstruction methods, using deep learning techniques, often require significant computational resources, limiting their a...

Coded Aperture Snapshot Spectral Imaging (CASSI) is a rapid hyperspectral imaging technique with broad application prospects. Due to limitations in three-dimensional compressed data acquisition modes and hardware constraints, the compressed measureme...

An event of sensor faults in sensor networks deployed in structures might result in the degradation of the structural health monitoring system and lead to difficulties in structural condition assessment. Reconstruction techniques of the data for miss...

This study considers a method for reconstructing a high dynamic range (HDR) original image from a single saturated low dynamic range (LDR) image of metallic objects. A deep neural network approach was adopted for the direct mapping of an 8-bit LDR im...

With the availability of high-throughput gene expression data in the post-genomic era, reconstruction of gene regulatory networks has become a hot topic. Regulatory networks have been intensively studied over the last decade and many software tools a...

Inference of the interactive network structure of the physical world that is captured by nonlinear dynamic systems is a long-standing goal for machine learning. Existing inference methods have shown limited incorporation of physical system informatio...

Coastal cities often face typhoons and urban water logs, which can cause power outages and significant economic losses. Therefore, it is necessary to study the impact of these disasters on urban distribution networks and improve their flexibility. Th...

Voice transformation, for example, from a male speaker to a female speaker, is achieved here using a two-level dynamic warping algorithm in conjunction with an artificial neural network. An outer warping process which temporally aligns blocks of spee...

The primary purpose of task allocation is to build each equipment platform and quickly complete integration planning at the actual combat speed to achieve efficient management of the entire task. In this process, higher requirements are put forward f...

Reconstructing the three-dimensional thermal structure of the ocean under typhoon conditions presents significant challenges due to the scarcity of observational data, particularly in subsurface regions, and the limitations of existing observation me...

The hippocampus is a key structure involved in the early pathological progression of Alzheimer’s disease. Accurate segmentation of this region is vital for the quantitative assessment of brain atrophy and the support of diagnostic decision-maki...

Inferring time-varying gene regulatory networks from time-series single-cell RNA sequencing (scRNA-seq) data remains a challenging task. The existing methods have notable limitations as most are either designed for reconstructing time-varying network...

In the dynamic optimization problem of the distribution network, a dynamic reconstruction method based on a stochastic probability model and optimized beetle antennae search is proposed. By implementing dynamic reconstruction of distributed energy di...

Security assessment of ironmaking plants is one of the crucial means to promote their sustainable development. However, the disparate nature of subsystems within these plants, along with network inconsistencies and isolated data, obstruct a thorough...

Deep neural networks have enabled the reconstruction of optical soliton molecules with more complex structures using the real-time spectral interferences obtained by photonic time-stretch dispersive Fourier transformation (TS-DFT) technology. In this...

Traditional two-dimensional dynamic fault detection methods describe nonlinear dynamics by constructing a two-dimensional sliding window in the batch and time directions. However, determining the shape of a two-dimensional sliding window for differen...

To fully leverage the application potential of distributed energy storage systems (DESS) and network reconfiguration, a coordinated optimization method is proposed to enhance the economic efficiency of distribution networks under normal conditions an...

State-of-the-art hydrogeological investigations use transient calibrated numerical flow and transport models for multiple scenario analyses. However, the transient calibration of numerical flow and transport models still requires consistent long-term...

High Dynamic Range (HDR) image reconstruction has gained prominence in a wide range of fields; not only is it implemented in computer vision, but industries such as entertainment and medicine also benefit considerably from this technology due to its...

The 3DGS (3D Gaussian Splatting) series of works has achieved significant success in novel view synthesis, but further research is needed for dynamic scene reconstruction tasks. In this paper, we propose a new framework based on 3DGS for handling dyn...

In order to monitor the variable-section wing deformation in real-time, this paper proposes a dynamic reconstruction algorithm based on the inverse finite element method and fuzzy network to sense the deformation of the variable-section beam structur...

The dynamics of network traffic are complex and nonlinear, and chaotic behaviors and their prediction, which play an important role in local area networks (LANs), are studied in detail, using the largest Lyapunov exponent. With the introduction of ph...

One of the most crucial aspects of 3D facial models is facial reconstruction. However, it is unclear if face shape distortion is caused by identity or expression when the 3D morphable model (3DMM) is fitted into largely expressive faces. In order to...

Imaging technologies based on vector optical fields hold significant potential in the biomedical field, particularly for non-invasive scattering imaging of anisotropic biological tissues. However, the dynamic and anisotropic nature of biological tiss...

Temporal network diffusion models play a crucial role in healthcare, information technology, and machine learning, enabling the analysis of dynamic event-based processes such as disease spread, information propagation, and behavioral diffusion. This...

With the successful application of the Shack–Hartmann wavefront sensor in measuring aberrations of the human eye, researchers found that, when the aberration is large, the local wavefront distortion is large, and it causes the spot correspondin...

Majority of current research focuses on a single static object reconstruction from a given pointcloud. However, the existing approaches are not applicable to real world applications such as dynamic and morphing scene reconstruction. To solve this, we...

In dynamic scattering media (such as rain, fog, biological tissues, etc.) environments, scattered light causes severe degradation of target images, directly leading to a sudden drop in the detection confidence of target detection models and a signifi...

As an important data source for historical geography research, toponyms reflect the human activities and natural landscapes within a certain area and time period. In this paper, a novel quantitative method of reconstructing historical river networks...

We develop a completely data-driven approach to reconstructing coupled neuronal networks that contain a small subset of chaotic neurons. Such chaotic elements can be the result of parameter shift in their individual dynamical systems and may lead to...

Video Snapshot Compressive Imaging (SCI) is a new imaging method based on compressive sensing. It encodes image sequences into a single snapshot measurement and then recovers the original high-speed video through reconstruction algorithms, which has...

Improving the three-dimensional reconstruction of underwater scenes is a challenging and hot topic in the field of underwater robot vision system research. High dynamic interference underwater has always been one of the key issues affecting the 3D re...

Image network design is a critical factor in image-based 3D shape reconstruction and data processing (especially in the application of combined SfM/MVS methods). This paper aims to present a new approach to designing and planning multi-view imaging n...

To address the issues of low survivability and communication efficiency in wireless sensor networks caused by frequent node movement or damage in highly dynamic and high-mobility battlefield environments, we propose a dynamic topology optimization me...

With the majority of research, in relation to 3D object reconstruction, focusing on single static synthetic object reconstruction, there is a need for a method capable of reconstructing morphing objects in dynamic scenes without external influence. H...

Neuronal cells are equipped with the function of a sensor that senses stimulation and elongates neurites to connect nearby neuronal cells in forming a neuronal network, as they are generally said to be hard to recover from physical damage, such as in...

High-dynamic-range (HDR) image reconstruction involves creating an HDR image from multiple low-dynamic-range images as input, providing a computational solution to enhance image quality. This task presents several challenges, such as frame misalignme...

Precision oncology is perceived as a way forward to treat individual cancer patients. However, knowing particular cancer mutations is not enough for optimal therapeutic treatment, because cancer genotype-phenotype relationships are nonlinear and dyna...

A large number of sensors are typically installed in industrial plants to collect real-time operational data. These sensors monitor data with time series correlation and spatial correlation over time. In previous studies, GNN has built many successfu...

Electrical capacitance volume tomography (ECVT) is an experimental technique capable of reconstructing 3D solid volume fraction distribution inside a sensing region. This technique has been used in fluidized beds as it allows for accessing data that...

The efficient coding hypothesis states that neural response should maximize its information about the external input. Theoretical studies focus on optimal response in single neuron and population code in networks with weak pairwise interactions. Howe...

The forecasting and reconstruction of oceanic dynamics is a crucial challenge. While model driven strategies are still the state-of-the-art approaches in the reconstruction of spatio-temporal dynamics. The ever increasing availability of data collect...

Floating nuclear power plants contain sensitive loads of nuclear reactors. After equipment faults, fast and efficient power supply recovery should be realized. To realize the unified analysis of system topology and power flow distribution, a power su...

Ghost imaging is a technique for indirectly reconstructing images by utilizing the second-order or higher-order correlation properties of the light field, which exhibits a robust ability to resist interference. On the premise of ensuring the quality...

It is a big challenge to detect and track small infrared marine targets in non-stationary and time-varying sea clutter because the signal is too strong to be estimated. Based on the phenomenon that sea clutter spreads not only in the temporal domain...