Different from general face recognition, age-invariant recognition (AIFR) aims at matching faces with a big age gap. Previous discriminative methods usually focus on decomposing facial feature into age-related and components, which suffer the loss of identity information. In this article, we propose novel Multi-feature Fusion Decomposition (MFD) framework for learns more robust features reduces intra-class variants. Specifically, first sample multiple images different ages same as time...

Cross-view geo-localization is to spot images of the same geographic target from different platforms, e.g., drone-view cameras and satellites. It challenging in large visual appearance changes caused by extreme viewpoint variations. Existing methods usually concentrate on mining fine-grained feature image center, but underestimate contextual information neighbor areas. In this work, we argue that areas can be leveraged as auxiliary information, enriching discriminative clues for...

Optical remote sensing images (RSIs) have been widely used in many applications, and one of the interesting issues about optical RSIs is salient object detection (SOD). However, due to diverse types, various scales, numerous orientations, cluttered backgrounds RSIs, performance existing SOD models often degrade largely. Meanwhile, cutting-edge targeting typically focus on suppressing backgrounds, while they neglect importance edge information which crucial for obtaining precise saliency...

The optical remote sensing images (RSIs) show various spatial resolutions and cluttered background, where salient objects with different scales, types, orientations are presented in diverse RSI scenes. Therefore, it is inappropriate to directly extend cutting-edge saliency detection methods for conventional RGB RSIs. Besides, the existing models targeting RSIs often render imperfect maps, some of them coarse boundary details. To solve this problem, article attempts introduce edge information...

Recently, more and researchers have paid attention to the surface defect detection of strip steel. However, performance existing methods usually fails detect regions from some complex scenes, especially with noise disturbance diverse types. Therefore, this article proposes an end-to-end dense attention-guided cascaded network (DACNet) salient objects (i.e., defects) on steel surface, where proposed DACNet is a U-shape including encoder decoder. The first deploys multiresolution convolutional...

Natural language generation (NLG) is an essential component of task-oriented dialogue systems. Despite the recent success neural approaches for NLG, they are typically developed particular domains with rich annotated training examples. In this paper, we study NLG in a low-resource setting to generate sentences new scenarios handful We formulate problem from meta-learning perspective, and propose generalized optimization-based approach (Meta-NLG) based on well-recognized model-agnostic (MAML)...

RGB-D saliency detection is receiving more and attention in recent years. There are many efforts have been devoted to this area, where most of them try integrate the multi-modal information, i.e. RGB images depth maps, via various fusion strategies. However, some ignore inherent difference between two modalities, which leads performance degradation when handling challenging scenes. Therefore, paper, we propose a novel model, namely Dynamic Selective Network (DSNet), perform salient object...

Most cutting-edge video saliency prediction models rely on spatiotemporal features extracted by 3D convolutions due to its local contextual cues acquirement ability. However, the shortage of is that it cannot effectively capture long-term dependencies in videos. To address this limitation, we propose a novel Transformer-based Multi-scale Feature Integration Network (TMFI-Net) for prediction, where proposed TMFI-Net consists semantic-guided encoder and hierarchical decoder. Firstly, embarking...

Salient object detection of surface defects is one the defect tasks, which aims at highlighting regions from strip steel, magnetic tale, road, and so on. However, performance existing methods degrades dramatically when dealing with complex scenarios, such as low contrast various shapes. Therefore, in this article, we propose a novel saliency model, namely, localizing, focus, refinement network (LFRNet), consists semantic-guided localizing module, context-driven focus edge-aware (ER) module....

Depth images and thermal contain the spatial geometry information surface temperature information, which can act as complementary for RGB modality.However, quality of depth is often unreliable in some challenging scenarios, will result performance degradation two-modal based salient object detection (SOD).Meanwhile, researchers pay attention to triple-modal SOD task, namely visibledepth-thermal (VDT) SOD, where they attempt explore complementarity image, image.However, existing methods fail...

The application of nanoparticles in the biomedical field is an exciting interdisciplinary research area current materials science. In present study, size-tunable and water-soluble noble metal silver (Ag NPs) have been successfully synthesized with assistance glutathione (GSH). as-synthesized Ag NPs are ready to bind covalently a model protein (bovine serum albumin) mild conditions. optical property surface-modifiable was extremely sensitive their size surface modification, suggesting...

Abstract COVID-19 pandemic has spread all over the world for months. As its transmissibility and high pathogenicity seriously threaten people’s lives, accurate fast detection of infection is crucial. Although many recent studies have shown that deep learning based solutions can help detect on chest CT scans, there lacks a consistent systematic comparison evaluation these techniques. In this paper, we first build clean segmented dataset called Clean-CC-CCII by fixing errors removing some...

The recent advent of 3D bioprinting biopolymers provides a novel method for fabrication tissue-engineered scaffolds and also offers potentially promising avenue in cartilage regeneration. Silk fibroin (SF) is one the most popular used bioprinting, but further application SF hindered by its limited biological activities. Incorporation growth factors (GFs) has been identified as solution to improve function. Platelet-rich plasma (PRP) an autologous resource GFs, which widely clinic. In this...

Image demoireing is a multi-faceted image restoration task involving both moire pattern removal and color restoration. In this paper, we raise general degradation model to describe an contaminated by patterns, propose novel multi-scale bandpass convolutional neural network (MBCNN) for single demoireing. For removal, multi-block-size learnable filters (M-LBFs), based on block-wise frequency domain transform, learn the priors of patterns. We also introduce new loss function named Dilated...

Existing studies for gait recognition are dominated by in-the-lab scenarios. Since people live in real-world senses, the wild is a more practical problem that has recently attracted attention of community multimedia and computer vision. Current methods obtain state-of-the-art performance on benchmarks achieve much worse accuracy proposed in-the-wild datasets because these can hardly model varied temporal dynamics sequences unconstrained scenes. Therefore, this paper presents novel multi-hop...