The literature in mathematics education identifies a traditional formal mechanistic-type paradigm in Integral Calculus teaching which is focused on the content to be taught but not on how to teach it. Resorting to the history of the genesis of knowle...
Making sense of complex objects is difficult, and typically requires the use of external representations to support cognitive demands while reasoning about the objects. Visualizations are one type of external representation that can be used to suppor...
Oriented object detection in high-resolution remote sensing images remains vulnerable to object–background confusion in complex scenes, where visually similar background structures can produce high-confidence false positives. To address this pr...
Within the scope of this article, the problem of the formalization of physical processes in adaptive training complexes is considered on the example of virtual objects burning. Despite a fairly complete study of this process, the existing mathematica...
This paper presents an autonomous grasping approach for complex-shaped objects using an anthropomorphic robotic hand. Although human-like robotic hands have a number of distinctive advantages, most of the current autonomous robotic pickup systems sti...
The current study aims to investigate the effects of 3D virtual object complexity on visual working memory capacity in mobile augmented reality (MAR) interfaces. With the popularity of augmented reality technology in mobile applications, 3D virtual e...
As autonomous-driving scenarios become increasingly complex, object detection in road environments remains challenging, especially for small-scale, visually ambiguous, and partially occluded targets. These difficulties are closely related to the loss...
Nowadays, with the emergence of sophisticated electronic devices, human daily activities are becoming more and more complex. On the other hand, research has begun on the use of reliable, cost-effective sensors, patient monitoring systems, and other s...
Complex water networks face prominent contradictions among flood control, water supply, and ecological protection, and traditional scheduling models struggle to address multi-dimensional water security challenges. To solve this problem, this study pr...
In order to address the problems of various interference factors and small sample acquisition in surface floating object detection, an object detection algorithm combining spatial and frequency domains is proposed. Firstly, a rough texture detection...
Marine object tracking is critical for search and rescue activities in the complex marine environment. However, the complex marine environment poses a huge challenge to the effect of tracking, such as the variability of light, the impact of sea waves...
The key to successful maneuvering complex extended object tracking (MCEOT) using range extent measurements provided by high resolution sensors lies in accurate and effective modeling of both the extension dynamics and the centroid kinematics. During...
Semi-supervised object detection helps to monitor and manage maritime transportation effectively, saving labeling costs. Currently, many semi-supervised object detection methods use a combination of data augmentation and pseudo-label to improve model...
Objects in images captured by unmanned aerial vehicles (UAVs) are often small in scale, weak in texture, and frequently occluded. Meanwhile, complex backgrounds can produce local responses similar to those of real targets, increasing the risk of miss...
Detection of tiny object in complex environments is a matter of urgency, not only because of the high real-world demand, but also the high deployment and real-time requirements. Although many current single-stage algorithms have good detection perfor...
Community structure is a very interesting attribute and feature in complex networks, which has attracted scholars’ attention and research on community detection. Many single-objective optimization algorithms have been migrated and modified to s...
Many compartments are prone to pose safety hazards such as loose fasteners or object intrusion due to their confined space, making manual inspection challenging. To address the challenges of complex inspection environments, diverse target categories,...
Network robustness is of paramount importance. Although great progress has been achieved in robustness optimization using single measures, such networks may still be vulnerable to many attack scenarios. Consequently, multi-objective network robustnes...
To address insufficient detail representation, inadequate cross-modal fusion, and limited localization accuracy in object detection under low-light and complex background conditions, this study proposes an improved CenterNet-based multimodal object d...
Small object detection in traffic sign applications often faces challenges like complex backgrounds, blurry samples, and multi-scale variations. Existing solutions tend to complicate the algorithms. In this study, we designed an efficient and simple...
Addressing the high-dimensional, strongly constrained multi-objective optimization problem of air–ground collaborative jamming scheduling in complex terrain, existing methods are often limited by incomplete modeling and low optimization efficie...
Currently, small moving object detection remains a highly challenging problem, primarily attributable to four critical factors: limited pixel coverage, blurred texture features, indistinguishability from small-object-like background features (i.e., f...
In the realm of autonomous driving, practical driving scenarios are fraught with numerous complexities, including inclement weather conditions, nighttime blurriness, and ambient light sources that significantly hinder drivers’ ability to discer...
Community detection is a crucial research direction in the analysis of complex networks and has been shown to be an NP-hard problem (a problem that is at least as hard as the hardest problems in nondeterministic polynomial time). Multi-objective evol...
With the emergence of various types of indoor positioning technologies (e.g., radio-frequency identification, Wi-Fi, and iBeacon), how to rapidly retrieve indoor cells and moving objects has become a key factor that limits those indoor applications....
Ship motion planning constitutes the most critical part in the autonomous navigation systems of marine autonomous surface ships (MASS). Weather and ocean conditions can significantly affect their navigation, but there are relatively few studies on th...
Foreign object detection during unmanned aerial vehicle (UAV) grid inspection suffers from severe visual degradation under adverse weather conditions, such as haze and heavy rain. Existing approaches often struggle to distinguish target textures from...
To address the compatibility challenges in selecting gas fire suppression systems for three typical complex protected environments—data centers, museum artifact storage rooms, and aircraft cargo holds—this paper establishes a multi-level...
In practical human–computer interaction, a hand gesture recognition method based on improved YOLOv5 is proposed to address the problem of low recognition accuracy and slow speed with complex backgrounds. By replacing the CSP1_x module in the YO...
The H.266/Versatile Video Coding (VVC) standard was developed to address the growing demand for compressing ultra-high-definition video content, supporting resolutions ranging from 4K to 8K and beyond. H.266/VVC improves coding efficiency by introduc...
Salient object detection aims to distinguish the most visually conspicuous regions, playing an important role in computer vision tasks. However, complex natural scenarios can challenge salient object detection, hindering accurate extraction of object...
In the development of highly automated driving systems (L3 and 4), much research has been done on the subject of driver takeover. Strong focus has been placed on the takeover quality. Previous research has shown that one of the main influencing facto...
Recently emerging data-driven citizen sciences need to harness an increasing amount of massive data with varying quality. This paper develops essential theoretical frameworks, example models, and a general definition of complexity measure, and examin...
This study presents a numerical framework for offline three-objective hole-sequence planning for an AC dual-rotary-head five-axis system. A double-curvature surface containing 48 staggered holes is used as a numerical case. For each hole, one represe...
In this paper, we propose an object-cooperated decision method for efficient ternary tree (TT) partitioning that reduces the encoding complexity of versatile video coding (VVC). In most previous studies, the VVC complexity was reduced using decision...
Object detection in images captured by unmanned aerial vehicles (UAVs) holds great potential in various domains, including civilian applications, urban planning, and disaster response. However, it faces several challenges, such as multi-scale variati...
Multi-object tracking (MOT) aims to detect objects in video sequences and associate them across frames. Currently, the mainstream research direction regarding MOT is the tracking-by-detection (TBD) framework. Tracking results are highly sensitive to...
Object Detection in Complex Indoor Scenes is designed to identify and categorize objects in indoor settings, with applications in areas such as smart homes, security surveillance, and home service robots. It forms the basis for advanced visual tasks...
The present study compared two sentence–picture-matching tests in Greek, namely the Syntactic Proficiency Test and the sentence comprehension subtest of the Diagnostic Verbal Intelligence Quotient (DVIQ) battery, to assess complex sentence comp...
Deep learning has been widely used in various fields because of its accuracy and efficiency. At present, the improvement of image semantic segmentation accuracy has become the area of most concern. In terms of increasing accuracy, improved semantic s...
With the development of remote sensing earth observation technology, object tracking has gained attention for its broad application prospects in computer vision. However, object tracking is challenging owing to the background clutter, occlusion, and...
This study uses UAV multi-spectral remote sensing images to carry out ground object classification research in complex wheat field scenes with diverse varieties. Compared with satellite remote sensing, the high spatial resolution remote sensing image...
The paper proposes a multi-objective approach for optimizing the structure of electric power generation amid tightening requirements for the energy efficiency and environmental safety of power systems. The study identifies relevant directions for imp...
Infrared small target detection is widely used in aerospace surveillance, maritime search and rescue, and military reconnaissance. However, the performance of detection algorithms is highly dependent on scene characteristics, and methods that perform...
This paper formulates beamforming synthesis as a multi-objective, multi-variable optimization problem to minimize the number of array elements while meeting constraints on half-power beamwidth, sidelobe level, and radiation attenuation in undesired d...
The efficient recognition and classification of personal protective equipment are essential for ensuring the safety of personnel in complex industrial settings. Using the existing methods, manually performing macro-level classification and identifica...
Unmanned Aerial Vehicle (UAV) inspection of transmission lines faces two primary challenges when detecting and analyzing components or defects in videos or images: poor performance in detecting small objects, and interference from complex backgrounds...
The underground coal mine environment is complex and dynamic, making the application of visual algorithms for object detection a crucial component of underground safety management as well as a key factor in ensuring the safe operation of workers. We...
Timely and accurate termite detection is essential for effective termite control. To address the challenges posed by the small size of termite individuals and the susceptibility of target features to background texture interference under complex back...
With the aim to solve issues of robot object recognition in complex scenes, this paper proposes an object recognition method based on scene text reading. The proposed method simulates human-like behavior and accurately identifies objects with texts t...
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