This paper proposes a human-aware deblurring model that disentangles the motion blur between foreground (FG) humans and background (BG). The proposed is based on triple-branch encoder-decoder architecture. first two branches are learned for sharpening FG BG details, respectively; while third one produces global, harmonious results by comprehensively fusing multi-scale information from domains. further endowed with supervised, attention mechanism in an end-to-end fashion. It learns soft mask...

In this paper, we present an effective and efficient face deblurring algorithm by exploiting semantic cues via deep convolutional neural networks (CNNs). As images are highly structured share several key components (e.g., eyes mouths), the information of a provides strong prior for restoration. such, propose to incorporate global priors as input impose local structure losses regularize output within multi-scale CNN. We train network with perceptual adversarial generate photo-realistic...

Size effect of the nickel-based single crystal superalloy DD6 is investigated in this study by performing nanoindentation experiments and finite element (FE) simulations emphasizing strain rate effect. An analytical method proposed to identify whether a material has indentation size (ISE) based on incremental formulations rate. By taking ISE as critical factor, contact area further described considering curvature radius non-ideal indenters due wear issues practice. In order emphasize during...

Nanoindentation has been widely utilized for measuring mechanical properties at small scales over the past three decades. Indentation size effect (ISE) is a crucial phenomenon in nanoindentation testing of crystalline materials, which usually manifested as an increase hardness with decrease indent size. Tremendous efforts have made to understand ISE aim eliminating its influence on determining intrinsic properties. More importantly, key exploring unique deformation mechanisms materials...

Retinal fundus images are widely used for the clinical screening and diagnosis of eye diseases. However, captured by operators with various levels experience have a large variation in quality. Low-quality increase uncertainty observation lead to risk misdiagnosis. due special optical beam imaging structure retina, natural image enhancement methods cannot be utilized directly address this. In this article, we first analyze ophthalmoscope system simulate reliable degradation major...

Fourier ptychographic microscopy (FPM) is a newly developed microscopic technique for large field of view, high-resolution and quantitative phase imaging by combining the techniques from imaging, aperture synthesizing retrieval. In FPM, an LED array utilized to illuminate specimen different angles corresponding intensity images are synthesized reconstruct complex field. As flexible low-cost approach achieve high-resolution, wide-field FPM enormous potential in biomedical applications such as...

In this paper, we propose a computationally efficient and consistently accurate spatiotemporal salient object detection method to identify the most noticeable in video sequence. Intuitively, underlying motion is more stable saliency indicator than apparent color cues that often contain significant variations complex structures. Based on observation, build an uses information as leverage locate dynamic regions We first analyze optical flow field obtain foreground priors, then incorporate...

Visual object tracking with semantic deep features has recently attracted much attention in computer vision. Especially, Siamese trackers, which aim to learn a decision making-based similarity evaluation, are widely utilized the community. However, online updating of fashion is still tricky issue due limitation, tradeoff between model adaption and degradation. To address such an issue, this article, we propose novel attentional transfer learning-based network (SiamATL), fully exploits...

Most Correlation Filter (CF)-based tracking methods can hardly handle occlusion or severe deformation, due to the lack of effective utilization previous target information. To overcome this, we propose a novel Transfer Learning-based Discriminative (TLDCF), which extracts knowledge from multiple tasks and applies for new task through Instance-Transfer Learning (ITL) Probability-Transfer (PTL). ITL Gaussian Mixture Modelling (GMM) representations multi-channel filters learned in frames...

In this study, nanoindentation technology is utilized to investigate the in situ mechanical behavior of small-sized packaging materials. Rather than ideal cases with unprestressed materials which have been intensively studies, paper focuses on effect surface stress by prestressing be indented a Berkovich indenter. The loading process until maximum penetration depth simulated finite element (FE) models. With elastoplastic as described power-law model, extensive FE predictions are performed...

With the rapid development of convolutional neural networks (CNNs), significant progress has been achieved in semantic segmentation. Despite great success, such deep learning approaches require large scale real-world datasets with pixel-level annotations. However, considering that labeling semantics is extremely laborious, many researchers turn to utilize synthetic data free But due clear domain gap, segmentation model trained images tends perform poorly on datasets. Unsupervised adaptation...

By assuming the elastoplastic properties of thin-film materials, a reverse analysis method is proposed by deriving dimensionless function for indentation process. The substrate effect taken into account perfect interface between and materials. In order to obtain applied load–penetration depth (P-h) curves, process numerically modeled as an axisymmetric problem with rigid-body Berkovich indenter on semi-infinite when performing finite element (FE) simulations. As typical soft film/hard...

The aim of this study was to evaluate the family resilience and its psychosocial influencing factors patients with lung cancer. Relationships between variables pathways were also explored based on Double ABC-X as theoretical framework. A cross-sectional survey 318 cancer conducted in a tertiary hospital Anhui, China. questionnaires included general information survey, Chinese perceived stress scale, Connor-Davidson Resilience Scale, social support cognitive emotion regulation self-efficacy...

Abstract The stable Bardeen-Schrieffer-Cooper (BCS) pairing state of a bosonic system has long been sought theoretically and experimentally. Here we propose that BCS bosons can be realized in binary Bose gas with s-wave intra-species repulsions an inter-species attraction the mean-field-stable region. We find above Bose-Einstein-Condensation (BEC) transition temperature, there is phase from normal to due pairing. When temperature decreases, another mixture both atomic BEC pairs occurs. As...

Compressive spectral imaging systems have promising applications in the field of object classification. However, for soil classification problem, conventional methods addressing this specific task often fail to produce satisfying results due tradeoff between invariance and discrepancy each soil. In paper, we explore a liquid crystal tunable filters (LCTF)-based system propose three-dimensional convolutional neural network (3D-CNN) We first obtain set compressive measurements via low spatial...