Reliability is a major performance index in the electromechanical product conceptual design decision process. As function purpose of design, risk scheme easy to be caused when there failure (i.e., failure). However, existing reliability analysis models focus on functions but ignore quantitative assessment schemes failures occur. In addition, information with subjectivity and fuzziness difficult introduce into early stage for comprehensive decisions. To fill this gap, paper proposes model...

In slap fingerprint segmentation, crease is the most difficult edge to correctly detect. this paper, we present a novel yet simple and accurate algorithm for principal axis detection. Firstly, of each foreground region detected using minimal rotational inertia; Secondly, detection done based on cost function minimization. This has been incorporated in segmentation scheme, previously developed by authors, producing successful results.

Abstract Traffic congestion detection method based on surveillance video is gradually widely used in intelligent transportation systems (ITS). Due to complex challenges such as weather change, vehicle occlusion, camera jitter, installation location, and so on, current methods are difficult balance real time accuracy. Here, a new real‐time robust traffic framework vision‐based multi‐dimensional model proposed. Firstly, the introduces an object detector lightweight convolutional neural network...

Photoacoustic tomography (PAT) is a newly emerged imaging modality which enables both high optical contrast and acoustic depth of penetration. Reconstructing images photoacoustic from limited amount senser data among one the major challenges in imaging. Previous works based on deep learning were trained supervised fashion, directly map input partially known sensor to ground truth reconstructed full field view. Recently, score-based generative models played an increasingly significant role...

Abstract With the popularity of cameras, application action recognition is more and extensive. After emergence RGB‐D cameras human pose estimation algorithms, actions can be represented by a sequence skeleton joints. Therefore, skeleton‐based has been research hotspot. In this paper, novel 3D Graph Convolutional Network model (3D‐GCN) with space‐time attention mechanism for 2D data proposed. Three‐dimensional graph convolution employed to extract spatiotemporal features descriptor that...

This paper presents a spam immune method to effectively filter the unsolicited email messages. The idea is classify messages using trained antibodies, which are produced by artificial system based on gene fragment library. approach focuses libraries used generate detectors, training of antibody and filtering application. experimental results show accurate effective.

Years of research have been devoted to computer-generated 2D marbling, whereas 3D marbling has yet be explored. The proposed mathematical solids supports a compact random-access vector representation, creating solid textures by composing closed-form pattern tool functions. resulting representation is feature-preserving and resolution-independent, it consumes very little memory. To facilitate the solid-marbling texture authoring process, authors also developed an intuitive user interface...

The classification problem of multivariate time series has been widely used in many fields, but current methods still cannot achieve high accuracy. In this paper, a novel model named FDNet (Feature and Difference encoding fused Network) is proposed. A structure that comprehensively considers global feature extraction local multi-scale the encoding, which can better represent closeness between sequence true label. difference distance shape are combined to further enhance FDNet's...

The formation trajectory planning using complete graphs to model collaborative constraints becomes computationally intractable as the number of drones increases due curse dimensionality. To tackle this issue, paper presents a sparse graph construction method for realize better efficiency-performance trade-off. Firstly, sparsification mechanism is designed ensure global rigidity sparsified graphs, which necessary condition uniquely corresponding geometric shape. Secondly, good constructed...

Photoacoustic tomography is a hybrid biomedical technology, which combines the advantages of acoustic and optical imaging. However, for conventional image reconstruction method, quality affected obviously by artifacts under condition sparse sampling. in this paper, novel model-based method via implicit neural representation was proposed improving reconstructed from data. Specially, initial pressure distribution modeled as continuous function spatial coordinates, parameterized multi-layer...

Relative state estimation is crucial for vision-based swarms to estimate and compensate the unavoidable drift of visual odometry. For autonomous drones equipped with most compact sensor setting -- a stereo camera that provides limited field view (FoV), demand mutual observation relative conflicts environment observation. To balance two demands FoV by acquiring observations safety guarantee, this paper proposes an active localization correction system, which plans orientations via yaw planner...

In practical applications within the human body, it is often challenging to fully encompass target tissue or organ, necessitating use of limited-view arrays, which can lead loss crucial information. Addressing reconstruction photoacoustic sensor signals in detection spaces has become a focal point current research. this study, we introduce self-supervised network termed HIgh-quality Self-supervised neural representation (HIS), tackles inverse problem imaging reconstruct high-quality images...

Small Video Object Detection (SVOD) is a crucial subfield in modern computer vision, essential for early object discovery and detection. However, existing SVOD datasets are scarce suffer from issues such as insufficiently small objects, limited categories, lack of scene diversity, leading to unitary application scenarios corresponding methods. To address this gap, we develop the XS-VID dataset, which comprises aerial data various periods scenes, annotates eight major categories. further...

High-quality imaging in photoacoustic computed tomography (PACT) usually requires a high-channel count system for dense spatial sampling around the object to avoid aliasing-related artefacts. To reduce complexity, various image reconstruction approaches, such as model-based (MB) and deep learning based methods, have been explored mitigate artefacts associated with sparse-view acquisition. However, methods formulated problem discrete framework, making it prone measurement errors,...