Aiming at the problem of Transformers lack of local spatial receptive field and discontinuous boundary loss in rotating object detection, in this paper, we propose a Transformer-based high-precision rotating object detection model (RODFormer). Firstl...
Cranes are pivotal heavy equipment used in the construction of transmission line scenarios. Accurately identifying these cranes and monitoring their status is pressing. The rapid development of computer vision brings new ideas to solve these challeng...
Rotated object detection in aerial images is still challenging due to arbitrary orientations, large scale and aspect ratio variations, and extreme density of objects. Existing state-of-the-art rotated object detection methods mainly rely on angle-bas...
Rotated object detection is a challenging task due to the difficulties of locating the rotated objects and separating them effectively from the background. For rotated object prediction, researchers have explored numerous regression-based and classif...
Rotated object detection aims to achieve precise localization by strictly aligning bounding boxes with object orientations, thereby minimizing background interference. Existing methods predominantly focus on extracting intra-object features within ro...
Rotated object detection in remote sensing imagery requires both semantic understanding and accurate geometric reasoning. Existing geometry-aware detectors commonly introduce geometric information through oriented proposals or decoder queries, making...
Oriented object detection in aerial imagery presents unique challenges due to the arbitrary orientations, diverse scales, and limited availability of labeled data. In response to these issues, we propose RASST—a lightweight Rotationally Aware S...
Remote sensing objects often exhibit significant scale variations, high aspect ratios, and diverse orientations. The anisotropic spatial distribution of such objects’ features leads to the conflict between feature representation and boundary re...
Single-object tracking (SOT) in satellite videos (SVs) is a promising and challenging task in the remote sensing community. In terms of the object itself and the tracking algorithm, the rotation of small-sized objects and tracking drift are common pr...
Rotated object detection is an extension of object detection that uses an oriented bounding box instead of a general horizontal bounding box to define the object position. It is widely used in remote sensing images, scene text, and license plate reco...
In measuring object rotational velocity using vortex beam, the incident light on a tilted object causes spectral broadening, which significantly interferes with the identification of the true rotational Doppler shift (RDS) peak. We employed a velocit...
Video satellites provide high-temporal-resolution remote sensing images that enable continuous monitoring of the ground for applications such as target tracking and airport traffic detection. In this paper, we address the problems of object occlusion...
Local patch-based methods of object detection and pose estimation are promising. However, to the best of the authors’ knowledge, traditional red-green-blue and depth (RGB-D) patches contain scene interference (foreground occlusion and backgroun...
In the domain of intelligent inspection, the precise recognition of pointer meter readings is of paramount importance for monitoring equipment conditions. To address the challenges of insufficient robustness and diminished detection accuracy encounte...
Object detection in remote sensing imagery plays a pivotal role in various applications, including aerial surveillance and urban planning. Despite its significance, the task remains challenging due to cluttered backgrounds, the arbitrary orientations...
Rotated object detection in remote sensing imagery is a core task of intelligent interpretation, used in urban management, resource surveys, and national defense. Remote sensing targets have large scale gaps, arbitrary orientations, and rotational sy...
Oriented remote sensing object detection (ORSOD) remains challenging because objects usually appear at arbitrary rotations, with large aspect-ratio variations and dense spatial layouts. Although recent detectors have achieved notable progress, most s...
Remote sensing of rotated objects often encounters numerous small and dense objects. To tackle small-object neglect and inaccurate angle predictions in elongated objects, we propose SA3Det, a novel method employing Pixel-Level Attention and Adaptive...
Oriented object detection in remote sensing images (RSIs) is a significant yet challenging Earth Vision task, as the objects in RSIs usually emerge with complicated backgrounds, arbitrary orientations, multi-scale distributions, and dramatic aspect r...
A set of sufficient conditions for the well posedness and the convergence of the finite element approximation of three-dimensional time-harmonic electromagnetic boundary value problems involving non-conducting rotating objects with stationary boundar...
Existing rotated object detection methods usually use angular parameters to represent the object orientation. However, due to the symmetry and periodicity of these angular parameters, a well-known boundary discontinuity problem often results. More sp...
At present, fish farming still uses manual identification methods. With the rapid development of deep learning, the application of computer vision in agriculture and farming to achieve agricultural intelligence has become a current research hotspot....
Geospatial object detection is a fundamental but challenging problem in the remote sensing community. Although deep learning has shown its power in extracting discriminative features, there is still room for improvement in its detection performance,...
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 recent years, object detection has shown excellent results on a large number of annotated data, but when there is a discrepancy between the annotated data and the real test data, the performance of the trained object detection model is often degra...
Rotation search and point cloud registration are two fundamental problems in robotics, geometric vision, and remote sensing, which aim to estimate the rotation and transformation between the 3D vector sets and point clouds, respectively. Due to the p...
Rotated object detection is widely adopted in remote sensing to handle arbitrary object orientations and improve localization accuracy. However, existing methods still suffer from limited global context modeling, degraded feature representation under...
The Generalized Hough Transform (GHT) is a powerful method for rigid shape detection under rotation, scaling, translation, and partial occlusion conditions, but its four-dimensional accumulator incurs prohibitive computational and memory demands that...
A mathematical model for an electric field induced by an angularly oscillating magnetic dipole was proposed with magnetic vector potential to analyze the characteristics of the electric field induced by a rotating and angularly oscillating magnetic o...
Effectively leveraging multi-source unmanned aerial vehicle (UAV) observations for reliable object recognition is often compromised by environmental extremes (e.g., occlusion and low illumination) and the inherent physical discrepancies between modal...
Pavement in outdoor settings is an unstructured environment with sharp corners, varying widths, and pedestrian activity that poses navigation challenges while cleaning for autonomous systems. In this work, an approach towards navigating without colli...
The paper presents the result of a study that can be included in the broader field of research aimed at increasing the performance of automatic motion control systems. The main contribution of the article is the comparative study of three control met...
The diffractive deep neural network (D2NN) can efficiently accomplish 2D object recognition based on rapid optical manipulation. Moreover, the multiple-view D2NN array (MDA) possesses the obvious advantage of being able to effectively achieve 3D obje...
Compared with general object detection with horizontal bounding boxes in natural images, oriented object detection in remote sensing images is an active and challenging research topic as objects are usually displayed in arbitrary orientations. To mod...
In this paper, we propose a Bayesian Optimization (BO)-based strategy using the Gaussian Process (GP) for feature detection of a known but non-cooperative space object by a chaser with a monocular camera and a single-beam LIDAR in a close-proximity o...
Object detection can accurately identify and locate targets in images, serving basic industries such as agricultural monitoring and urban planning. However, targets in remote sensing images have random rotation angles, which hinders the accuracy of r...
Accurate detection of small, rotated objects in practical scenarios such as remote sensing imagery and autonomous driving remains a critical challenge. Existing methods often struggle to balance detection accuracy and real-time performance, and face...
The detection of arbitrarily rotated objects in aerial images is challenging due to the highly complex backgrounds and the multiple angles of objects. Existing detectors are not robust relative to the varying angle of objects because the CNNs do not...
Standard convolution sliding along a fixed direction in common convolutional neural networks (CNNs) is inconsistent with the direction of aerial targets, making it difficult to effectively extract features with high-aspect-ratio and arbitrary directi...
Arbitrarily oriented object detection has recently attracted increasing attention for its wide applications in remote sensing. However, it is still a challenge for detection algorithms because of complex scenes, small size, rotation, densely parked....
Objectivity is a fundamental requirement for vortex identification, ensuring that vortex structures observed remain invariant under changes in the reference frame. However, although most conventional vortex identification methods, including Liutex, a...
Detection of rotating targets in complex remote sensing scenarios often suffers from angular inconsistencies and boundary jitter, especially for small-to-medium objects with rapid pose changes or indistinct boundaries in dense environments. To addres...
Compared with a monoculture planting mode, the practice of crop rotations improves fertilizer efficiency and increases crop yield. Large-scale crop rotation monitoring relies on the results of crop classification using remote sensing technology. Howe...
Object detection is a challenging task in aerial images, where many objects have large aspect ratios and are densely arranged. Most anchor-based rotating detectors assign anchors for ground-truth objects by a fixed restriction of the rotation Interse...
Despite their versatility in treating irregular geometries, the raster methods have received limited attention in solving packing problems involving rotatable objects. In addition, raster approximation allows the use of unique performance metrics and...
Future climate change poses unprecedented challenges to agricultural production worldwide. Therefore, designing region-specific rotation patterns is crucial for achieving synergies among multiple objectives, including agricultural productivity and ec...
Fast and accurate acquisition of the outline of rural buildings on remote sensing images is an efficient method to monitor illegal rural buildings. The traditional object detection method produces useless background information when detecting rural b...
As one of the main pieces of equipment in coal transportation, the belt conveyor with its detection system is an important area of research for the development of intelligent mines. Occurrences of non-coal foreign objects making contact with belts ar...
Passive wireless surface acoustic wave (SAW) sensors are very useful for on-site monitoring of the working status of machines in complex environments, such as high-temperature rotating objects. For rotating parts, it is difficult to realize real-time...
Synthetic aperture radar (SAR) imagery is widely used for target detection in complex backgrounds and adverse weather conditions. However, high-precision detection of rotated small targets remains challenging due to severe speckle noise, significant...
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