Long noncoding RNA (lncRNA) plays a crucial role in many critical biological processes and participates in complex human diseases through interaction with proteins. Considering that identifying lncRNA–protein interactions through experimental methods...
Partial orders are the natural mathematical structure for comparing multivariate data that, like colours, lack a natural order. We introduce a novel, general approach to defining rank features in colour spaces based on partial orders, and show that i...
This paper investigates a rapid and accurate detection system for spoilage in meat. We use unsupervised feature learning techniques (stacked restricted Boltzmann machines and auto-encoders) that consider only the transient response from undoped zinc...
Machine vision technology has dramatically improved the efficiency, speed, and quality of fruit-picking robots in complex environments. Target recognition technology for fruit is an integral part of the recognition systems of picking robots. The trad...
For aquaculture resource evaluation and ecological environment monitoring, the automatic detection and identification of marine organisms is critical; however, due to the low quality of underwater images and the characteristics of underwater biologic...
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...
The traditional algorithms for recognizing handwritten alphanumeric characters are dependent on hand-designed features. In recent days, deep learning techniques have brought about new breakthrough technology for pattern recognition applications, espe...
With the rapid development of the Internet, malware traffic is seriously endangering the security of cyberspace. Convolutional neural networks (CNNs)-based malware traffic classification can automatically learn features from raw traffic, avoiding the...
Although widely used in many applications, accurate and efficient human action recognition remains a challenging area of research in the field of computer vision. Most recent surveys have focused on narrow problems such as human action recognition me...
Tool wear monitoring is necessary for cost reduction and productivity improvement in the machining industry. Machine learning has been proven to be an effective means of tool wear monitoring. Feature engineering is the core of the machining learning...
Traffic classification is the first step in network anomaly detection and is essential to network security. However, existing malicious traffic classification methods have several limitations; for example, statistical-based methods are vulnerable to...
The majority of modern object detectors rely on a set of pre-defined anchor boxes, which enhances detection performance dramatically. Nevertheless, the pre-defined anchor strategy suffers some drawbacks, especially the complex hyper-parameters of anc...
Both single infrared and visible images have respective limitations. Fusion technology has been developed to conquer these restrictions. It is designed to generate a fused image with infrared information and texture details. Most traditional fusion m...
The human body contains identity information that can be used for the person recognition (verification/recognition) problem. In this paper, we propose a person recognition method using the information extracted from body images. Our research is novel...
The Modular Multilevel Converter-High Voltage Direct Current (MMC-HVDC) system is recognized worldwide as a highly efficient strategy for transporting renewable energy across regions. As most of the MMC-HVDC system electronics are weak against overcu...
Differentiable Neural Architecture Search has emerged as a powerful paradigm for automated network design, yet it suffers from a fundamental optimization inconsistency problem: Architectures optimized under continuous relaxation often fail to maintai...
A novel optimal power and energy management (OPEM) for centralized hybrid energy storage systems (HESS) in microgrids is presented in this paper. The proposed OPEM aims at providing multiple grid services by suitably exploiting the different power/en...
Nonrigid multimodal image registration remains a challenging task in medical image processing and analysis. The structural representation (SR)-based registration methods have attracted much attention recently. However, the existing SR methods cannot...
As one of the most important active remote sensing technologies, synthetic aperture radar (SAR) provides advanced advantages of all-day, all-weather, and strong penetration capabilities. Due to its unique electromagnetic spectrum and imaging mechanis...
Image deblurring has been a challenging ill-posed problem in computer vision. Gaussian blur is a common model for image and signal degradation. The deep learning-based deblurring methods have attracted much attention due to their advantages over the...
Recommendation attack attempts to bias the recommendation results of collaborative recommender systems by injecting malicious ratings into the rating database. A lot of methods have been proposed for detecting such attacks. Among these works, the dee...
Resource-limited settings continue to face challenges in the identification of COVID-19, bacterial pneumonia, viral pneumonia, and normal lung conditions because of the overlap of CT appearance and inter-observer variability. We justify a hybrid arch...
Forest fires have continually endangered personal safety and social property. To reduce the occurrences of forest fires, it is essential to detect forest fire smoke accurately and quickly. Traditional forest fire smoke detection based on convolutiona...
Hand–object occlusion poses a significant challenge in 3D pose estimation. During hand–object interactions, parts of the hand or object are frequently occluded by the other, making it difficult to extract discriminative features for accur...
In recent decades, extensive attention has been paid to the study and development of robotic devices specifically designed for hand rehabilitation. Accordingly, a many concepts concerning rigid, soft, and hybrid types have emerged in the literature,...
Most robotic hands have been created at roughly the scale of the human hand, with rigid components forming the core structural elements of the fingers. This focus on the human hand has concentrated attention on operations within the human hand scale,...
The use of both hands is a common practice in everyday life. The capacity to interact with the environment is largely dependent on the ability to use both hands. A thorough review of the current state of the art reveals that commercially available pr...
Hand pose estimation from 3D data is a key challenge in computer vision as well as an essential step for human–computer interaction. A lot of deep learning-based hand pose estimation methods have made significant progress but give less consider...
Hand gesture recognition and hand pose estimation are two closely correlated tasks. In this paper, we propose a deep-learning based approach which jointly learns an intermediate level shared feature for these two tasks, so that the hand gesture recog...
Person re-identification (Re-ID) has attracted attention due to its wide range of applications. Most recent studies have focused on the extraction of deep features, while ignoring color features that can remain stable, even for illumination variation...
This study presents the design and evaluation of a dexterous prosthetic hand featuring five fingers, ten independently actuated joints, and four passively driven joints. The hand’s dexterity is enabled by a novel rigid–flexible coupled fi...
In the field of computer vision, hand pose estimation (HPE) has attracted significant attention from researchers, especially in the fields of human–computer interaction (HCI) and virtual reality (VR). Despite advancements in 2D HPE, challenges...
The objective of 3D hand pose estimation (HPE) based on depth images is to accurately locate and predict keypoints of the hand. However, this task remains challenging because of the variations in hand appearance from different viewpoints and severe o...
Hand pose estimation from RGB images has always been a difficult task, owing to the incompleteness of the depth information. Moon et al. improved the accuracy of hand pose estimation by using a new network, InterNet, through their unique design. Stil...
Fabric hand is defined as the human tactile sensory response towards fabric, which involves not only physical but also physiological, perceptional and social factors. Fabric hand is one of the most important characteristic of a fabric. This paper dis...
There is a disconnection between commercial architecture and environmental thinking, where green features can be included as part of a strategy for gaining approvals and marketing projects, but those features are not reviewed after completion and occ...
In 3D terrain analysis, topographical characteristics, such as mountains or valleys, and geo-spatial data characteristics, such as specific weather conditions or objects of interest, are important features. Visual representations of these features ar...
Research on Virtual Reality (VR) interfaces for distant object interaction has been carried out to improve user experience. Since hand-only interfaces and gaze-only interfaces have limitations such as physical fatigue or restricted usage, VR interact...
Recent technological advances have enabled the development of sophisticated prosthetic hands, which can help their users to compensate lost motor functions. While research and development has mostly addressed the functional requirements and needs of...
Virtual reality (VR) devices that integrate eye-tracking and hand-tracking technologies can capture users’ natural eye–hand data in real time within a three-dimensional virtual space, providing new opportunities to explore users’ at...
Explainability is essential for AI models, especially in clinical settings where understanding the model’s decisions is crucial. Despite their impressive performance, black-box AI models are unsuitable for clinical use if their operations canno...
Giving robot hands more powerful functions has always been one of the goals pursued by scholars in this field. In this paper, an electromagnetic switching multiple grasping modes robot hand (ESMGM hand) is proposed, which integrates three typical gra...
To address the inability of existing space grasping mechanisms to adapt to the varying shapes and sizes of space objects, we propose a novel three-fingered space robotic hand composed of an actuated palm and deployable fingers with the aim of success...
Vein recognition has been drawing more attention recently because it is highly secure and reliable for practical biometric applications. However, underlying issues such as uneven illumination, low contrast, and sparse patterns with high inter-class s...
In this paper, a new-brand feature-based detector via an improved concave hull classifier (FB-ICHC) is proposed to detect marine small targets. The dimension of feature space is suggested to be three, making a compromise between high detection accura...
Natural human–human communication consists of multiple modalities interacting together. When an intelligent robot or wheelchair is being developed, it is important to consider this aspect. One of the most common modality pairs in multimodal hum...
The dialing-type authentication as a common PIN code input system has gained popularity due to the simple and intuitive design. However, this type of system has the security risk of “shoulder surfing attack”, so that attackers can physica...
Gesture recognition has been studied for decades and still remains an open problem. One important reason is that the features representing those gestures are not sufficient, which may lead to poor performance and weak robustness. Therefore, this work...
In this article, the design of a five-fingered anthropomorphic gripper is presented specifically designed for the manipulation of elastic objects. The manipulator features a hybrid design, being equipped with three fully actuated fingers for precise...
Infrared and visible image fusion integrates complementary information from different modalities into a single image, providing sufficient imaging information for scene interpretation and downstream target recognition tasks. However, existing fusion...
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