In this paper, we present scalable multi-precision multiplication implementation and scalable multi-precision squaring implementation for 32-bit ARM Cortex-M4 microcontrollers. For efficient computation and scalable functionality, we present optimize...
On-chip memory is one of the core components of deep learning accelerators. In general, the area used by the on-chip memory accounts for around 30% of the total chip area. With the increasing complexity of deep learning algorithms, it will become a c...
Over recent years, significant improvements have been made in the understanding of (epi)genetics and neuropathophysiological mechanisms driving the different forms of multiple sclerosis (MS). For example, the role and importance of the bidirectional...
Non-contact heart rate estimation technology based on frequency-modulated continuous wave (FMCW) radar has garnered extensive attention in single-target scenarios, yet it remains underexplored in multi-target environments. Accurate discrimination of...
In multi-sensor fusion (MSF), the integration of multi-sensor observation data with different observation errors to achieve more accurate positioning of the target has always been a research focus. In this study, a modified ensemble Kalman filter (En...
Aiming at the problem that multi-ship target detection and tracking based on cameras is difficult to meet the accuracy and speed requirements at the same time in some complex scenes, an improved YOLOv4 algorithm is proposed, which simplified the netw...
Recently, Multi-Graph Learning was proposed as the extension of Multi-Instance Learning and has achieved some successes. However, to the best of our knowledge, currently, there is no study working on Multi-Graph Multi-Label Learning, where each objec...
Traditional 3D reconstruction models have consistently faced the challenge of balancing high recall of object edges with maintaining a high precision. In this paper, we introduce a post-processing method, the Multi-Head Attention Refiner (MA-R), desi...
With the advancement of computer vision and sensor technologies, many multi-camera systems are being developed for the control, planning, and other functionalities of unmanned systems or robots. The calibration of multi-camera systems determines the...
Achieving precise synchronization is critical for multi-camera systems in various applications. Traditional methods rely on hardware-triggered synchronization, necessitating significant manual effort to connect and adjust synchronization cables, espe...
The operation and test of a multi-spot digital sun sensor for precise sun-line determination is described. The image forming system consists of an opaque mask with multiple pinhole apertures producing multiple, simultaneous, spot-like images of the s...
This paper presents a fast and robust approach to evaluate the singular values of small (e.g.,
In the field of image detection, when focusing on multiple targets of interest with different depths, in addition to optimizing the focusing speed of a single target, a comprehensive consideration of the interrelationships among multiple targets can...
Precise Point Positioning (PPP) is a popular technology for precise applications based on the Global Navigation Satellite System (GNSS). Multi-GNSS combined PPP has become a hot topic in recent years with the development of multiple GNSSs. Meanwhile,...
Angle measurement is an essential component of precision measurement and serves as a crucial prerequisite for high-end manufacturing. It guides the implementation of precision manufacturing and assembly. The current angle measurement methods mainly f...
Registration is a critical step in multi-sensor dimensional measurement. As the accuracy of registration directly impacts the quality of final results, a reference sphere as a common standard is problematic in high-precision registration. In this pap...
The increasing complexity of plant disease manifestations, especially in cases of multiple simultaneous infections, poses significant challenges to sustainable agriculture. To address this issue, we introduce the Apple Leaf Mixed Disease Recognition...
Multi-cell cooperative control can be competent for the current increasingly complex biomedical experiments, greatly improving the efficiency of cell manipulation experiments. At present, this kind of multi-cell cooperative control algorithm is becom...
The latest development of multi-robot collaborative systems has put forward higher requirements for multi-sensor fusion localization. Current position methods mainly focus on the fusion of the carrier’s own sensor information, and how to fully...
Damage localization in GFRP (glass-fiber-reinforced polymer) composite plates is a crucial research area in marine engineering. This study introduces a feedback-based damage index (DI) combined with multi-label classification to enhance the accuracy...
To predict the multi-point vibration response in the frequency domain when the uncorrelated multi-source loads are unknown, a data-driven and multi-input multi-output least squares support vector regression (MIMO LS-SVR)-based method in the frequency...
The division of retrieval into multiple stages has evolved to balance efficiency and effectiveness among various ranking models. Faster but less accurate models are used to retrieve results from the entire corpus. Slower yet more precise models refin...
In this paper, a novel magnetic field-based sensing system employing statistically optimized concurrent multiple sensor outputs for precise field-position association and localization is presented. This method capitalizes on the independence between...
The assembly interface topography of precision machinery exhibits complex multi-scale geometric features, including roughness, waviness, and form error, which critically influence assembly accuracy and tolerance analysis. To address the lack of adapt...
Rapid advancements in remote sensing (RS) imaging technology have heightened the demand for the precise and efficient interpretation of large-scale, high-resolution RS images. Although segmentation algorithms based on convolutional neural networks (C...
This paper presents an enhanced YOLOv8 model designed to address multi-target detection challenges in complex traffic scenarios. The model integrates the Squeeze-and-Excitation attention mechanism, the deformable convolution C2f module, and the smoot...
Road markings that provide instructions for unmanned driving are important elements in high-precision maps. In road information collection technology, multi-beam mobile LiDAR scanning (MLS) is currently adopted instead of traditional mono-beam LiDAR...
Previous VideoGIS integration methods mostly used geographic homography mapping. However, the related processing techniques were mainly for independent cameras and the software architecture was C/S, resulting in large deviations in geographic video m...
An uplink multi-user tracking problem aided by multiple passive reconfigurable intelligent surfaces (RISs) is addressed in this work. Under a near-field circumstance, a multi-antenna base station (BS) localizes multiple moving single-antenna users by...
Federated learning is a collaborative machine learning paradigm where multiple parties jointly train a predictive model while keeping their data. On the other hand, multi-label learning deals with classification tasks where instances may simultaneous...
Distributed coherent aperture radar (DCAR) can realize high-precision long-range detection because of its excellent angular resolution. However, it is accompanied by a low search efficiency problem caused by the narrow main lobe and the angular ambig...
Barrel-type structures are ubiquitous in industry and life. A novel construction platform of barrel-type structures is introduced, and it involves a multi-motor system. The synchronous control of multiple motors has great importance. To guarantee the...
To address the industry pain points of high seed breakage rate and uncontrollable miss-filling rate, multiple-filling rate in traditional rapeseed roller-type precision centralized seed metering devices—while breaking the adaptation limitation...
At the core of AI-driven electrocardiogram diagnosis lies the precise localization of the QRS complex. While QRS detection methods for multiple leads have been researched adequately in the last few decades, their multi-lead strategies still need to b...
With the global population growth and increasing food demand, the development of precision agriculture has become particularly critical. In precision agriculture, accurately identifying areas of nitrogen stress in crops and planning precise fertiliza...
Synthetic aperture imaging radiometers (SAIRs) are powerful passive microwave systems for high-resolution imaging by use of synthetic aperture technique. However, the ill-posed inverse problem for SAIRs makes it difficult to reconstruct the high-prec...
Cameras are widely used in the detection and tracking of moving targets. Compared to target visual tracking using a single camera, cooperative tracking based on multiple cameras has advantages including wider visual field, higher tracking reliability...
Column-averaged dry air mole fraction of atmospheric CO2 (XCO2), obtained by multiple satellite observations since 2003 such as ENVISAT/SCIAMACHY, GOSAT, and OCO-2 satellite, is valuable for understanding the spatio-temporal variations of atmospheric...
Multi-spectral temperature measurement technology has been found to have extensive applications in engineering practice. Addressing the challenges posed by unknown emissivity in multi-spectral temperature measurement data processing, this paper adds...
The automatic cultivation of corn has become a significant research focus, with precision equipment operation being a key aspect of smart agriculture’s advancement. This work explores the tracking process of corn, simulating the detection and a...
The rapid development of synthetic aperture radar (SAR) imaging technology has significantly enhanced maritime monitoring capabilities; however, SAR ship detection remains constrained by the limited scale and representation capacity of existing rotat...
Integrated Energy Systems (IES) are an important way to improve the efficiency of energy, promote closer connections between various energy systems, and reduce carbon emissions. The transformation between electricity, heating, and cooling loads into...
With the development of science and technology, modern communication scenarios have put forward higher requirements for passive location technology. However, current location systems still use manual scheduling methods and cannot meet the current mis...
Railway track fasteners, serving as critical connecting components, have a reliability that directly impacts railway operational safety. To address the performance bottlenecks of existing detection methods in handling complex scenarios with diverse f...
The detection and recognition of marine targets can be improved by utilizing the micro-motion induced by ocean waves. However, distinguishing and tracking overlapping targets is challenging when multiple extended targets overlap in the range dimensio...
The detection and localization of radiation sources in urban areas present significant challenges in electromagnetic spectrum operations, particularly with the proliferation of small UAVs. To address these challenges, we propose the Multi-UAV Reconna...
With the widespread adoption of modern RGB cameras, an abundance of RGB images is available everywhere. Therefore, multi-view stereo (MVS) 3D reconstruction has been extensively applied across various fields because of its cost-effectiveness and acce...
Multi-camera Visual Simultaneous Localization and Mapping (V-SLAM) increases spatial coverage through multi-view image streams, improving localization accuracy and reducing data acquisition time. Despite its speed and generally robustness, V-SLAM oft...
This study proposes an advanced plant disease classification framework leveraging the Attention Score-Based Multi-Vision Transformer (Multi-ViT) model. The framework introduces a novel attention mechanism to dynamically prioritize relevant features f...
The security of the continuous-variable quantum key distribution (CVQKD) system is subject to various attacks by hackers. The traditional detection method of parameter estimation requires professionals to judge known attacks individually, so the gene...
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