Fetal cardiac structure localization requires features that follow the size and orientation of individual anatomical targets. We present Geometry-guided Regional Interaction and Transformation for Oriented Bounding Box Detection (GRIT-OBB), an orient...
Three-dimensional object detection involves estimating the dimensions, orientations, and locations of 3D bounding boxes. Intersection of Union (IoU) loss measures the overlap between predicted 3D box and ground truth 3D bounding boxes. The localizati...
This paper proposes an AI-based diagnostic method using MRI images for rotator cuff injuries to assist in treatment by segmenting tear areas and assessing tear severity. A multi-model deep learning network based on Unet + FPN architecture was develop...
This study aims to evaluate whether safety nets on construction sites are correctly installed using an image processing and deep learning technique. The developed method performs data preprocessing, including horizontal flipping, rotation, and contra...
Oriented object detection has received extensive attention in recent years, especially for the task of detecting targets in aerial imagery. Traditional detectors locate objects by horizontal bounding boxes (HBBs), which may cause inaccuracies when de...
Synthetic Aperture Radar (SAR) has the advantage of continuous observation throughout the day and in all weather conditions, and is used in a wide range of military and civil applications. Among these, the detection of ships at sea is an important re...
In order to achieve the automated qualitative evaluation of Ephestia kuehniella eggs in mass industrialization and production, YOLOv10-CR is presented, with a modified circular representation based on YOLOv10. While existing methods like CircleNet st...
A novel concept of quaternionic fuzzy sets (QFSs) is presented in this paper. QFSs are a generalization of traditional fuzzy sets and complex fuzzy sets based on quaternions. The novelty of QFSs is that the range of the membership function is the set...
Canine hip dysplasia (CHD) screening relies on accurate positioning in the ventrodorsal hip extended (VDHE) view, as even mild pelvic rotation can affect CHD scoring and impact breeding decisions. This study aimed to assess the association between pe...
Background: Qualitative motion analysis revealed that the cervical spine moves according to a consistent pattern. This analysis calculates the relative rotation between vertebral segments to determine the sequence in which they contribute to extensio...
Accurate and efficient text detection in natural scenes is a fundamental yet challenging task in computer vision, especially when dealing with arbitrarily-oriented texts. Most contemporary text detection methods are designed to identify horizontal or...
Synthetic aperture radar (SAR) imagery plays a vital role in critical applications such as military reconnaissance and disaster monitoring. These applications require high detection accuracy. Therefore, rotated object detection has gained increasing...
In synthetic aperture radar (SAR) images, ships are often arbitrary-oriented and densely arranged in complex backgrounds, posing enormous challenges for ship detection. However, most existing methods detect ships with horizontal bounding boxes, which...
Oriented object detection in remote sensing images has achieved substantial progress, yet non-maximum suppression (NMS) remains vulnerable to angular variation when the overlap of high-aspect-ratio objects is measured with rotated bounding boxes. To...
The ability of deep learning models to maintain consistent performance under image transformations-termed invariances, is critical for reliable deployment across diverse computer vision applications. This study presents a comprehensive empirical eval...
Temporomandibular joint osteoarthritis (TMJ OA) is a degenerative condition of the TMJ led by a pathological tissue response of the joint under mechanical loading. It is characterized by the progressive destruction of the internal surfaces of the joi...
Background: The segmentation of individual teeth in three-dimensional (3D) dental models is a key step in orthodontic computer-aided design systems. Traditional methods lack robustness when handling challenging cases such as missing or misaligned tee...
Accurate teeth segmentation and orientation are fundamental in modern oral healthcare, enabling precise diagnosis, treatment planning, and dental implant design. In this study, we present a comprehensive approach to teeth segmentation and orientation...
In the field of machine vision defect detection for a micro workpiece, it is very important to make the neural network realize the integrity of the mask in analyte segmentation regions. In the process of the recognition of small workpieces, fatal def...
Remote sensing imagery poses significant challenges for object detection due to the presence of objects at multiple scales, dense target overlap, and the complexity of extracting features from small targets. This paper introduces an innovative Adapti...
For large-scale 3D building reconstruction, there have been several approaches to utilizing multi-view satellite imagery to produce a digital surface model (DSM) for height information and extracting building footprints for contour information. Howev...
Efficient and accurate semantic segmentation is the key technique for automatic remote sensing image analysis. While there have been many segmentation methods based on traditional hand-craft feature extractors, it is still challenging to process high...
Referring expression grounding in overhead imagery requires oriented bounding boxes rather than horizontal ones, since aerial objects appear at arbitrary orientations. Most grounding models emit box coordinates sequentially; Parallel Box Decoding (PB...
Accurately identifying fractures from X-ray images is crucial for timely and appropriate medical treatment. However, existing models suffer from problems of false localization and poor accuracy. Therefore, this research proposes a medical X-ray fract...
The introduction of noise during image acquisition and transmission is inevitable, leading to a significant reduction in the accuracy of image processing tasks, such as target classification, localization, and recognition. To address this issue, this...
Green citrus detection in citrus orchards provides reliable support for production management chains, such as fruit thinning, sunburn prevention and yield estimation. In this paper, we proposed a lightweight object detection YOLOv5-CS (Citrus Sort) m...
Remote sensing technology has found extensive application in agriculture, providing critical data for analysis. The advancement of semantic segmentation models significantly enhances the utilization of point cloud data, offering innovative technical...
Regional Convolutional Neural Network (RCNN)−based detectors have played a crucial role in object detection in remote sensing images due to their exceptional detection capabilities. Some studies have shown that different stages should have diff...
The segmentation of jujube tree branches and the estimation of primary branch inclination angles (IAs) are crucial for achieving intelligent pruning. This study presents a primary branch IA estimation algorithm for jujube trees based on an improved P...
Object Detection (OD) in Remote Sensing Imagery (RSI) encounters significant challenges such as multi-scale variation, high aspect ratios, and densely distributed objects. These challenges often result in misalignments among Bounding Box (BBox) repre...
In complex inshore regions, ships are often densely berthed and arbitrarily oriented, while docks, shorelines, coastal facilities, and strong scatterers produce substantial background clutter and target-like scattering responses, leading to foregroun...
Accurate characterization of particle dynamics in complex swirling flows is essential for understanding flow behavior and transport mechanisms. However, extracting three-dimensional (3D) rotational motion parameters of particles from High-Speed Motio...
Background: Qualitative motion analysis revealed that the cervical spine moves according to a consistent pattern. Current data analysis methods are limited by the extensive time required to process the retrieved data. A previous study demonstrated th...
High-precision 3D building data are pivotal for smart city development, urban planning, and disaster management. However, large-scale building extraction from airborne LiDAR point clouds remains challenging due to semantic ambiguity, uneven point den...
In optical remote sensing image object detection, discontinuous boundaries often limit detection accuracy, particularly at high Intersection over Union (IoU) thresholds. This paper addresses this issue by proposing the Spatial Adaptive Angle-Aware (
Background and Objectives: The purpose of this study was to develop and evaluate a deep learning model capable of autonomously detecting and segmenting radiolucent lesions in the lower jaw by utilizing You Only Look Once (YOLO) v8. Materials and Meth...
Inspired by Connected-UNets, this study proposes a deep learning model, called Connected-SegNets, for breast tumor segmentation from X-ray images. In the proposed model, two SegNet architectures are connected with skip connections between their layer...
Point symbols on a scanned topographic map (STM) provide crucial geographic information. However, point symbol recognition entails high complexity and uncertainty owing to the stickiness of map elements and singularity of symbol structures. Therefore...
Ship instance segmentation in synthetic aperture radar (SAR) images is a hard and challenging task, which not only locates ships but also obtains their shapes with pixel-level masks. However, in ocean SAR images, because of the consistent reflective...
Rapid preliminary reconnaissance of Critical Transportation Hubs (CTHs) by UAV swarms is vital during post-disaster rescue operations. However, limited camera fields of view, large heading variances, and GNSS multipath errors near massive steel-concr...
The mining industry faces significant challenges in production costs, environmental protection, and worker safety, necessitating the development of autonomous systems. This study presents the design and implementation of a robust rock centroid locali...
Oriented objects in RSI (Remote Sensing Imagery) typically present arbitrary rotations, extreme aspect ratios, multi-scale variations, and complex backgrounds. These factors often result in feature misalignment, representational ambiguity, and regres...
Wave-dissipating blocks are the armor elements of breakwaters that protect beaches, ports, and harbors from erosion by waves. Monitoring the poses of individual wave-dissipating blocks benefits the accuracy of the block supplemental work plan, record...
Vehicle pose estimation is essential in autonomous vehicle (AV) perception technology. However, due to the different density distributions of the point cloud, it is challenging to achieve sensitive direction extraction based on 3D LiDAR by using the...
To effectively combat the re-infestation of boll weevils (Anthonomus grandis L.) in cotton fields, it is necessary to address the detection of volunteer cotton (VC) plants (Gossypium hirsutum L.) in rotation crops such as corn (Zea mays L.) and sorgh...
Building damage and collapse are the main sources of serious casualties and financial losses during earthquakes, which are among the most destructive natural disasters that endanger human life and property. Therefore, quick and precise post-earthquak...
Brain tumor segmentation from Magnetic Resonance Imaging (MRI) is an important task in tumor analysis, treatment planning, and disease monitoring. However, manual delineation of tumor regions is time-consuming, subjective, and prone to inter-observer...
Oriented ship detection in Synthetic Aperture Radar (SAR) images has broad applications in maritime surveillance and other fields. While deep learning advancements have significantly improved ship detection performance, persistent challenges remain f...
This study proposes a clinically driven hybrid segmentation framework for dense breast tissue analysis in mammographic images, addressing persistent challenges associated with intensity inhomogeneity, low-contrast, and complex tumor morphology. The f...
Accurately quantifying flora and their respective anatomical structures within natural ecosystems is paramount for both botanical breeders and agricultural cultivators. For breeders, precise plant enumeration during the flowering phase is instrumenta...