Person re-identification has seen significant advancement in recent years. However, the ability of learned models to generalize unknown target domains still remains limited. One possible reason for this is lack large-scale and diverse source training data, since manually labeling such a dataset very expensive privacy sensitive. To address this, we propose automatically synthesize person following set-up similar real surveillance but with virtual environments, then use synthesized images...

Visual question answering (VQA) requires systems to perform concept-level reasoning by unifying unstructured (e.g., the context in and answer; "QA context") structured knowledge graph for QA scene; "concept graph") multimodal knowledge. Existing works typically combine a scene concept of connecting corresponding visual nodes nodes, then incorporate representation answering. However, these methods only unidirectional fusion from knowledge, limiting their potential capture joint over...

Person re-identification (Re-ID) is a challenging task due to variations in pedestrian images, especially cross-domain scenarios. The existing person Re-ID approaches extract the feature from single image, but they ignore correlations among images. In this paper, we propose Heterogeneous Convolutional Network (HCN) for Re-ID, which learns appearance information of images and simultaneously. To end, first utilize Neural (CNN) features Then construct graph target dataset where are treated as...

Solving the depth estimation problem in a 360° image space, which has holistic scene perception, become trend recent years. However, common images is prone to geometric distortion. Therefore, this study proposes new method, CAPDepth, address geometric-distortion of monocular estimation. We reduce tangential projections by an optimized content-aware projection (CAP) and embedding module capture more features for global consistency. Additionally, we adopt index map de-blocking scheme improve...

Currently, multi-modal 3D object detection methods have become a key area of research in the field autonomous driving. Fusion is an essential factor affecting performance detection. However, previous still suffer from inability to effectively fuse features LiDAR and RGB images, resulting low utilization rate complementary information between depth semantic texture features. At same time, existing may not adequately capture structural Region Interest (RoI) when extracting them. Structural...

ABSTRACT Aims The objective of this research is to investigate the association between number teeth and frailty in geriatric population. Design This cross‐sectional study was conducted Shanghai Fifth People's Hospital, Fudan University, from May 2021 September 2021. Methods A cohort 538 community‐dwelling older adults aged 60 years or above included analysis. Tilburg Frailty Indicator, Mini‐Mental State Examination Mini Nutritional Assessment Short‐Form were employed assess frailty,...

This study aimed to identify risk factors for diabetic retinopathy (DR) and develop machine learning (ML)-based predictive models using routine laboratory data in patients with type 2 diabetes mellitus (T2DM). Clinical from 4259 T2DM inpatients at Beijing Tongren Hospital were analyzed, divided into a model construction set (N = 3936) an external validation 323). Using 39 optimal variables, prediction was constructed the eXtreme Gradient Boosting (XGBoost) algorithm compared four other...

ABSTRACT The recent invasion of the fall armyworm (FAW) into Asia not only has had a major impact on maize yield but is feared to also pose risk rice production. We hypothesized that brown planthopper (BPH) may aggravate this based recently discovered mutualism between and striped stem borer. Here we show BPH indeed facilitate shift FAW rice. females were found strongly prefer oviposit BPH‐infested plants, which emitted significantly elevated levels five volatile compounds. A synthetic...

This paper proposes an advanced multi-instance learning method with multi-features engineering and conservative optimization for engagement intensity prediction. It was applied to the EmotiW Challenge 2020 results demonstrated proposed method's good performance. The task is predict level when a subject-student watching educational video under range of conditions in various environments. As has strong correlation facial movements, upper-body posture movements overall environmental given time...

The task of answering questions about images has garnered attention as a practical service for assisting populations with visual impairments well Turing test the artificial intelligence community. Our first aim is to identify common vision skills needed both scenarios. To do so, we analyze need four skills--object recognition, text color and counting--on over 27,000 from two datasets representing We next quantify difficulty these humans computers on datasets. Finally, propose novel...

The non-linearity between human perception and image brightness levels results in different definitions of NORMAL-light. Thus, most existing low-light enhancement methods which produce one-to-one mapping can not meet the aesthetic demand. Other pioneers enhance images guided by a given value. However, inherent problem will cause poor usability. To this end, we propose user-friendly neural network for multi-level enhancement. Inspired style transfer, our method decomposes an into content...

摘要: 为了改进目前常用的运动目标检测方法易受到噪声和亮度突变的影响、易出现虚假目标的情况，该文提出了一种基于3帧差分和边缘信息的运动目标检测方法。该方法首先对连续3帧图像进行边缘提取得到3帧连续的边缘图像，然后对3帧连续的边缘图像进行3帧差分运算，最后通过阈值分割和形态学处理完成对目标的提取。该方法计算简单，实验结果表明该方法能对运动目标进行准确检测，且具有很好的鲁棒性。 关键词: 运动目标检测; 3帧差分; 边缘提取

Many real-world systems exhibit temporal, dynamic behaviors, which are captured as time series of complex agent interactions. To perform temporal reasoning, current methods primarily encode dynamics through simple sequence-based models. However, in general these models fail to efficiently capture the full spectrum rich input, since is not uniformly distributed. In particular, relevant information might be harder extract and computing power wasted for processing all individual timesteps, even...

Developing efficient, single-phase white-light phosphors remains a formidable challenge in optoelectronics. Herein, high pressure initially induces trimeric contraction and distortion (C

Abstract Objective This study aimed to assess the knowledge, attitude, and practice (KAP) of WeChat users towards health-related public accounts. Methods The included 567 participants who completed questionnaire. Pearson correlation analysis was used evaluate among 3 dimensions. Multivariate identified independent factors associated with KAP scores. Results mean scores for were 6.12 ± 2.29 (61.2% total), 55.83 7.33 (69.8% 14.07 3.72 (70.4% respectively. Significant positive correlations...

Abstract N6‐methyladenosine (m 6 A) serves as one of the crucial RNA modifications for genes involved in cancer progression. Here, 7273 expression quantitative trait loci potentially regulating 30 m6A pathway are identified from GTEx database, with 69 single nucleotide polymorphisms significantly associated survival non‐small cell lung carcinoma (NSCLC) patients ( n = 1523) ongoing genome‐wide association study after false positive probability tests. Notably, rs151198415 locus, situated a...

This paper proposes a novel engagement intensity prediction approach, which is also applied in the EmotiW Challenge 2019 and resulted good performance. The task to predict level when subject student watching an educational video diverse conditions various environments. Assuming that has strong correlation with facial movements, upper-body posture movements overall environmental time interval, we extract incorporate these motion features into deep regression model consisting of layers...