The availability of large annotated datasets and affordable computation power have led to impressive improvements in the performance convolutional neural networks (CNNs) on various face analysis tasks. In this paper, we describe a deep learning pipeline for unconstrained identification verification which achieves state-of-the-art several benchmark datasets. We provide design details modules involved automatic recognition: detection, landmark localization alignment,...

Image deblurring aims to restore the latent sharp images from corresponding blurred ones. In this paper, we present an unsupervised method for domain-specific, single-image based on disentangled representations. The disentanglement is achieved by splitting content and blur features in a image using encoders encoders. We enforce KL divergence loss regularize distribution range of extracted attributes such that little information contained. Meanwhile, handle unpaired training data, blurring...

Covariates are factors that have a debilitating influence on face verification performance. In this paper, we comprehensively study two covariate related problems for unconstrained verification: first, how covariates affect the performance of deep neural networks large-scale problem; second, to utilize improve To first problem, implement five state-of-the-art convolutional (DCNNs) and evaluate them three challenging datasets. total, seven considered: pose (yaw roll), age, facial hair,...

Introduction Nicosulfuron is the leading acetolactate synthase inhibitor herbicide product, and widely used to control gramineous weeds. Here, we investigated metabolic process of nicosulfuron into foxtail millet maize, in order clarify mechanism difference sensitivity maize from perspective physiological metabolism provide a theoretical basis for breeding nicosulfuron-resistant varieties. Methods We treated (Zhangzagu 10, Jingu 21) (Nongda 108, Ditian 8) with various doses both pot field...

Foxtail millet (Setaria italica [L.] P. Beauv.) is a climate-change-ready crop, and it crucial for predicting the impact of ecological factors on grain quality. In this study, multivariate statistical analysis was used to explore relationship between key nutritional quality Jingu 21 from twelve production areas. The results showed that crude fat amylopectin content foxtail millets downward trend south north. significantly affected by geographical, climatic, soil factors, produced in...

Waxy maize (Zea mays L. sinensis kulesh) contains a lot of nutrients, and has long history cultivation extensive consumption. In this study, six waxy varieties white (J18 W2000), yellow (J41 J7), black (J10 J20) were selected as experimental materials, the functional nutrients differences in anthocyanin anabolic pathways kernels at 14, 18, 22, 26 days after pollination determined. The result show that kernel development stages had significant effect on carotenoid, soluble sugar, vitamin C,...

Foxtail millet (Setaria italica L.) is a critical grain with high nutritional value and the potential for increased production in arid semiarid regions. The foxtail chain can be upgraded only by ensuring its comprehensive quality. Thus, samples were collected from different areas Shanxi province, China, compared terms of quality traits. We established evaluation system utilizing multivariate statistical analysis. results showed that appearance, content, culinary produced ecological regions...

Electromagnetically induced transparency (EIT) and electromagnetically absorption (EIA) have many applications, especially for achieving slow light fast light. EIT EIA been widely observed in both quantum classical systems where two transition pathways could interference destructively or constructively. Multipathway has a concern recent works, however, due to the difficulty of precisely controlling system parameters, experimental study multipathway is generally challenging. In this paper, we...

Selenium (Se) is a micronutrient known for its essential role in human health and plant metabolism. Waxy maize (

Recent advances in deep convolutional neural networks (DCNNs) and generative adversarial (GANs) have significantly improved the performance of single image blind deblurring algorithms. However, most existing algorithms require paired training data. In this paper, we present an unsupervised method for single-image without images. We introduce a disentangled framework to split content blur features blurred image, which yields performance. To handle unpaired data, blurring branch...

Domain adaptation (DA) methods attempt to solve the domain mismatch problem between source and target data. In this paper, we propose an incremental dictionary learning method where some data called supportive samples are selected assist adaptation. Supportive close have two properties: first, their predicted class labels reliable can be used for building more discriminative classification models; second, they act as a bridge connect domains reduce mismatch. Theoretical analysis shows that...

Low-temperature stress limits the growth and development of foxtail millet. Freezing caused by sudden temperature drops, such as late-spring coldness, often occurs in seedling stage However, ability coping strategies millet to cope with are not clear. In present study, we analyzed self-regulatory mechanisms freezing We conducted a physiological study on leaves at -4 °C for seven different durations (0, 2, 4, 6, 8, 10, 12 h). Longer time increased cell-membrane damage, relative conductance,...

Image deblurring aims to restore the latent sharp images from corresponding blurred ones. In this paper, we present an unsupervised method for domain-specific single-image based on disentangled representations. The disentanglement is achieved by splitting content and blur features in a image using encoders encoders. We enforce KL divergence loss regularize distribution range of extracted attributes such that little information contained. Meanwhile, handle unpaired training data, blurring...

Unconstrained video-based face recognition is a challenging problem due to significant within-video variations caused by pose, occlusion and blur. To tackle this problem, an effective idea propagate the identity from high-quality faces low-quality ones through contextual connections, which are constructed based on context such as body appearance. However, previous methods have often propagated erroneous information lack of uncertainty modeling noisy connections. In paper, we propose...

In this paper, we propose a pose-robust metric learning framework for unconstrained face verification by jointly optimizing and pose tasks. We learn joint model these two tasks explicitly discourage the information sharing between identity metrics so as to mitigate contained in task leading making more pose-robust. Specifically, use Bayesian both enforce an orthogonal regularization constraint on learned projection matrices The labels used training are automatically estimated do not require...

In this work, we propose a metric adaptation method for set-based face verification and evaluate it on the newly released IARPA Janus Benchmark A (IJB-A) dataset its extended version, Challenging Set 2 (CS2). template-specific is trained to adaptively learn discriminative information in test templates negative training set, which contains subjects that are mutually exclusive templates. The proposed regularized joint Bayesian learning framework not only alleviates over-fitting problem but...

Task-driven dictionary learning (TDDL) has shown great success in many classification applications. However, the performance of TDDL is limited by challenging properties hyperspectral images (HSI). Fortunately, previous research made significant progress HSI enforcing various structured sparsity constraints (priors) on TDDL-based model. In this paper, we extend some work relaxing priors and make model become more flexible powerful. Specifically, add class label Laplacian two different...

Abstract Ancient glass products are often weathered to varying degrees after excavation. Detection and analysis of their chemical composition will help study the ancient making process. In this paper, we take a group as samples, sub-classification type identification silicate glasses. Firstly, identify main factor weathering through chi-squared test Fisher’s exact test, then conduct significance on basis preprocessing various data cultural relics. Secondly, samples classified into high...

Abstract In order to ensure the normal operation of radio astronomy observations, an extremely sensitive receiver system needs be equipped in front large telescope. An 8-pole wideband high-temperature superconducting (HTS) filter using a Coplanar Spiral Resonator Structure with passband 1160∼1670 MHz is developed suppress strong interference. The fabricated on 36 mm × 14 YBCO HTS film, which deposited 0.5 thick MgO substrate. minimum insertion loss measured liquid nitrogen temperature region...

The availability of large annotated datasets and affordable computation power have led to impressive improvements in the performance CNNs on various object detection recognition benchmarks. These, along with a better understanding deep learning methods, also improved capabilities machine faces. are able detect faces, locate facial landmarks, estimate pose, recognize faces unconstrained images videos. In this paper, we describe details pipeline for face identification verification which...