Building extraction of remote sensing images is very important for urban planning. In the field of deep learning, in order to extract more detailed building features, more complex convolution operations and larger network models are usually used to s...
We have developed a novel algorithm for sEMG feature extraction and classification. It is based on a hybrid network composed of spiking and artificial neurons. The spiking neuron layer with mutual inhibition was assigned as feature extractor. We demo...
Feature extraction is essential for classifying different motor imagery (MI) tasks in a brain–computer interface (BCI). Although the methods of brain network analysis have been widely studied in the BCI field, these methods are limited by diffe...
Because the existing methods extract the signal characteristics of electronic communication networks, there is a problem of poor extraction. In this paper, a feature extraction method based on symmetric algorithm for transmission signals in electroni...
Hyperspectral image (HSI) classification accuracy has been greatly improved by employing deep learning. The current research mainly focuses on how to build a deep network to improve the accuracy. However, these networks tend to be more complex and ha...
In the realm of image classification, the capsule network is a network topology that packs the extracted features into many capsules, performs sophisticated capsule screening using a dynamic routing mechanism, and finally recognizes that each capsule...
The method of acoustic radiation signal detection not only enables contactless measurement but also provides comprehensive state information during equipment operation. This paper proposes an enhanced feature extraction network (EFEN) for fault diagn...
Single-image super-resolution (SISR) seeks to elucidate the mapping relationships between low-resolution and high-resolution images. However, high-performance network models often entail a significant number of parameters and computations, presenting...
To better process irregular sample images for their image feature extraction and recognition, this essay proposes asymmetric adaptive neural network (AACNN) structures, including dual structures of an adaptive image feature extraction network (AT-CNN...
The extraction of water stream based on synthetic aperture radar (SAR) is of great significance in surface water monitoring, flood monitoring, and the management of water resources. However, in recent years, the research mainly uses the backscatterin...
The task to extract relations tries to identify relationships between two named entities in a sentence. Because a sentence usually contains several named entities, capturing structural information of a sentence is important to support this task. Curr...
Due to the rapid development of deep learning and artificial intelligence techniques, denoising via neural networks has drawn great attention due to their flexibility and excellent performances. However, for most convolutional network denoising metho...
To cope with the challenges of autonomous driving in complex road environments, the need for collaborative multi-tasking has been proposed. This research direction explores new solutions at the application level and has become a hot topic of great in...
The emergence of deep learning-based classification methods has led to considerable advancements and remarkable performance in image recognition. This study introduces the Multiscale Feature Convolutional Neural Network (MSFCNN) for the extraction of...
The Rare Earth Extraction Process (REEP) model is difficult to accurately establish via the extraction mechanism method due to its high complexity. This paper proposes a multi-branch deep feature fusion network with SAE (SAE-MBDFFN) for modeling REEP...
With the growing diversity of cyberattacks in recent years, anomaly-based intrusion detection systems that can detect unknown attacks have attracted significant attention. Furthermore, a wide range of studies on anomaly detection using machine learni...
A flame’s structural feature is a crucial parameter required to comprehensively understand the interaction between turbulence and flames. The generation and evolution processes of the structure feature have rarely been investigated in lean blow...
Most of the current complex network studies about epilepsy used the electroencephalogram (EEG) to directly construct the static complex network for analysis and discarded the dynamic characteristics. This study constructed the dynamic complex network...
Automatic music transcription (AMT) aims to convert raw audio signals into symbolic music. This is a highly challenging task in the fields of signal processing and artificial intelligence, and it holds significant application value in music informati...
Accurate maps of regional surface water features are integral for advancing ecologic, atmospheric and land development studies. The only comprehensive surface water feature map of Alaska is the National Hydrography Dataset (NHD). NHD features are oft...
Traditional transmission line fault diagnosis approaches ignore local structure feature information during feature extraction and cannot concentrate more attention on fault samples, which are difficult to diagnose. To figure out these issues, an enha...
Automatic building extraction has been applied in many domains. It is also a challenging problem because of the complex scenes and multiscale. Deep learning algorithms, especially fully convolutional neural networks (FCNs), have shown robust feature...
In recent years, numerous single-image dehazing algorithms have made significant progress; however, dehazing still presents a challenge, particularly in complex real-world scenarios. In fact, single-image dehazing is an inherently ill-posed problem,...
The shrubland ecosystems in arid areas are highly sensitive to global climate change and human activities. Accurate extraction of shrubs using computer vision techniques plays an essential role in monitoring ecological balance and desertification. Ho...
The challenging issues in infrared and visible image fusion (IVIF) are extracting and fusing as much useful information as possible contained in the source images, namely, the rich textures in visible images and the significant contrast in infrared i...
The quantity and quality of cropland are the key to ensuring the sustainable development of national agriculture. Remote sensing technology can accurately and timely detect the surface information, and objectively reflect the state and changes of the...
Road extraction from remote sensing images is significant for urban planning, intelligent transportation, and vehicle navigation. However, it is challenging to automatically extract roads from remote sensing images because the scale difference of roa...
Machinery degradation assessment can offer meaningful prognosis and health management information. Although numerous machine prediction models based on artificial intelligence have emerged in recent years, they still face a series of challenges: (1)...
If the layer of soil surrounding a pile is not taken into account during the engineering detection process, the velocity-time curve might show asymptotic diameter shrinkage or diameter expanding features, which would alter the interpretation of the t...
The reliable forecasting of river flow plays a key role in reducing the risk of floods. Regarding nonlinear and variable characteristics of hydraulic processes, the use of data-driven and hybrid methods has become more noticeable. Thus, this paper pr...
In general, reliable PV generation prediction is required to increase complete control quality and avoid potential damage. Accurate forecasting of direct solar radiation trends in PV power production could limit the influence of uncertainties on phot...
Antarctic true-color imagery synthesized using multispectral remote sensing data is effective in reflecting sea ice conditions, which is crucial for monitoring. Deep learning has been explored for sea ice extraction, but traditional convolutional neu...
This paper presents a real-time remote water level monitoring system based on dense wavelength division multiplexing (DWDM)-passive optical fiber sensor (OFS) network for the application of the Internet of Things (IoT). This network employs a broadba...
Human activity recognition (HAR) is crucial to infer the activities of human beings, and to provide support in various aspects such as monitoring, alerting, and security. Distinct activities may possess similar movements that need to be further disti...
The application of remote sensing technology in water body detection has become increasingly widespread, offering significant value for environmental monitoring, hydrological research, and disaster early warning. However, the existing methods face ch...
Feature extraction is essential for chemical property estimation of molecules using machine learning. Recently, graph neural networks have attracted attention for feature extraction from molecules. However, existing methods focus only on specific str...
Extraction of traffic features constitutes a key research direction in traffic safety planning. In previous traffic tasks, road network features are extracted manually. In contrast, Network Representation Learning aims to automatically learn low-dime...
To achieve effective deep fusion features for improving the classification accuracy of hyperspectral remote sensing images (HRSIs), a pixel frequency spectrum feature is presented and introduced to convolutional neural networks (CNNs). Firstly, the f...
Spatial cognition, a critical component of human cognitive function, can be enhanced through targeted training, such as virtual reality (VR)-based interventions. Recent advances in electroencephalography (EEG)-based functional connectivity analysis h...
Automatically extracting 2D buildings from high-resolution remote sensing images is among the most popular research directions in the area of remote sensing information extraction. Semantic segmentation based on a CNN or transformer has greatly impro...
Next-generation mobile communications networks will have to cope with an extraordinary amount and variety of network performance indicators, causing an increase in the storage needs of the network databases and the degradation of the management funct...
Feature extraction is a key part of the electronic tongue system. Almost all of the existing features extraction methods are “hand-crafted”, which are difficult in features selection and poor in stability. The lack of automatic, efficient...
This research compares the facial expression recognition accuracy achieved using image features extracted (a) manually through handcrafted methods and (b) automatically through convolutional neural networks (CNNs) from different depths, with and with...
How to acquire useful information intelligently in the age of information explosion has become an important issue. In this context, sentiment analysis emerges with the growth of the need of information extraction. One of the most important tasks of s...
Semantic segmentation is one of the most active research topics in computer vision with the goal to assign dense semantic labels for all pixels in a given image. In this paper, we introduce HFEN (Hierarchical Feature Extraction Network), a lightweigh...
The major challenges for medical image segmentation tasks are complex backgrounds and fuzzy boundaries. In order to reduce their negative impacts on medical image segmentation tasks, we propose an enhanced feature extraction network (EFEN), which is...
This paper aims to locate damaged rods in a three-dimensional (3D) steel truss and reveals some internal working mechanisms of the convolutional neural network (CNN), which is based on the first-order modal parameters and CNN. The CNN training sample...
Black soil is a precious soil resource, yet it is severely affected by gully erosion, which is one of the most serious manifestations of land degradation. The determination of the location and shape of gullies is crucial for the work of gully erosion...
Leakage detection is an important task to ensure the operational safety of water distribution networks. Leakage characteristic extraction based on high-frequency data has been widely used for leakage detection in experimental networks. However, the a...
Geometric feature extraction of 3D point clouds plays an important role in many 3D computer vision applications such as region labeling, 3D reconstruction, object segmentation, and recognition. However, hand-designed features on point clouds lack sem...
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