Motivated by previous success of using non-parametric methods to recognize objects, e.g., NBNN [2], we extend it actions skeletons. Each 3D action is presented a sequence poses. Similar NBNN, our proposed Spatio-Temporal-NBNN applies stage-to-class distance classify actions. However, ST-NBNN takes the spatio-temporal structure into consideration and relaxes Naive Bayes assumption NBNN. Specifically, adopts bilinear classifiers [19] identify both key temporal stages as well spatial joints for...

Abstract Polyesters, a highly promising class of circular polymers for achieving closed‐loop sustainable plastic economy, inherently exhibit material stability defects, especially in thermal and hydrolytic instability. Here, we introduce polyesters, P(4 R ‐BL) (R=Ph, Bu), featuring conformationally rigid 1,3 ‐ cyclobutane rings the backbone. These polyesters not only superior thermostability ( T d,5% =376–380 °C) but also demonstrate exceptional resistance with good integrity even after 1...

Selective actinide coordination (from lanthanides) is critical for both nuclear waste management and sustainable development of power. Hydrophilic ligands used as masking agents to withhold actinides in the aqueous phase are currently highly pursued, while synthetic accessibility, water solubility, acid resistance, extraction capability remaining problems. Most reported hydrophilic only effective at low acidity. We recently proved that phenanthroline diimide skeleton was an efficient...

In this paper, we propose a novel formulation for multi-feature clustering using minimax optimization. To find consensus result that is agreeable to all feature modalities, our objective universal embedding, which not only fits each individual modality well, but also unifies different modalities by minimizing their pairwise disagreements. The loss function consists of both (1) unary embedding cost modality, and (2) disagreement pair with weighting parameters automatically selected maximize...

Despite the recent success of 3D action recognition using depth sensor, most existing works target how to improve performance, rather than understanding different types actions are performed. In this paper, we propose discover discriminative spatio-temporal patterns for recognition. Discovering these can not only help performance but also us understand and differentiate between category. Our proposed method takes structure into consideration essential that play key roles in Instead relying...

Polyesters featuring a linear topology and in‐chain 1,3‐cyclobutane rings, synthesized via ring‐opening polymerization (ROP) of 2‐oxabicyclo[2.1.1]hexan‐3‐one (4R‐BL, R = Bu, Ph) through coordination‐insertion mechanism, display excellent thermal hydrolytic stability, making them promising candidates for sustainable circular materials. However, achieving diverse topological stereochemical structures remains challenging. Herein, we demonstrate precise control over cyclic topologies these...

Unveiling the lanthanides selectivity in aqueous media from molecular structures bias was demonstrated which could potentially contribute to establish structure-function relationship for intragroup discrimination and extractions.

Abstract The short lifespan of most commercial plastics as disposables and the failure to adequately address end‐of‐life issues synthetic polymers have led outrageous global plastic pollution resource depletion. To solve problem, one effective strategies is develop circular thus establish a new material economy. Polymers from ring‐opening polymerization five‐membered (thio)lactones contribute greatly this field due their excellent performance recyclability. emerging topic emphasizes on...

Abstract Polyesters, a highly promising class of circular polymers for achieving closed‐loop sustainable plastic economy, inherently exhibit material stability defects, especially in thermal and hydrolytic instability. Here, we introduce polyesters, P(4 R ‐BL) (R=Ph, Bu), featuring conformationally rigid 1,3 ‐ cyclobutane rings the backbone. These polyesters not only superior thermostability ( T d,5% =376–380 °C) but also demonstrate exceptional resistance with good integrity even after 1...

Scene image is a spatial composition of objects and background contexts finding discriminative layouts critical for scene recognition. In this letter, we propose an ℓ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -regularized max-margin formulation to discover class-specific by jointly learning the classifier Unlike previous methods that classify images into different categories either without considering explicitly or only using class...

Autonomous Vehicles (AV) and Advanced Driver Assistance Systems (ADAS) require smart built-in systems to recognize pedestrian intention avoid casualties. Recent approaches towards predicting use motion information his/her situational awareness distinguish between of either crossing or stopping before a vehicle. We investigate the power including contextual into this problem. Examples cues include position with respect curb road relative locations vehicles in scene. propose graphical model...

Abstract Copolymerization stands as a versatile and potent method for tailoring polymer properties by adjusting structural unit composition sequence distribution. However, achieving sequence‐controlled copolymerization in one‐step one‐pot process remains challenging. This study introduces solvent‐dependent strategy to produce block statistical copolyesters from 4‐phenyl‐2‐oxabicyclo[2.1.1]hexan‐3‐one (4 Ph ‐BL) ϵ ‐caprolactone ( ‐CL). The distinct kinetics of the two monomers enable facile...

The co-occurrence features are the composition of base that have more discriminative power than individual features. Although they show promising performance in visual recognition applications such as object, scene, and action recognition, discovery optimal is usually a computationally demanding task. Unlike previous feature mining methods fix order or rely on two-stage frequent pattern to select feature, we propose novel branch-and-bound search-based algorithm can directly mine both...

Local feature extraction, coding, spatial pooling, and image classification are the four typical steps for state-of-the-art visual recognition systems. Unlike previous work that treats pooling as separated steps, we propose to jointly learn geometric classifier such class-specific information of local descriptors can be incorporated improve performance. Inspired by pyramid matching receptive field learning, also random partition approaches further exploit structural boost Experiments on...

This paper is concerned with a system for detecting and tracking multiple 3D bounding boxes based on information from sensors. Our framework built around an inference engine similar to the probability hypothesis density (PHD) filter, where state space consists of stochastic constant velocity dynamics. We outline measurement equations two modalities (vision radar). The result flexible suitable use autonomous vehicles.

We propose a novel hierarchical sparse coding algorithm with spatial pooling and multi-feature fusion, to construct the low-level visual primitives, e.g., local image patches or regions, into high-level phrases, patterns. In first layer we learn codes for primitives then pass them second by fusion. further phrases. order obtain high-quality representations our proposed iteratively optimizes over two-layer codes, as well codebooks. Since have explored both contextual information, more...

Background: There is considerable evidence on the benefits of endovascular thrombectomy (EVT) for acute ischemic stroke (AIS) within 6 h after symptom onset. However, uncertainties remain regarding EVT efficacy beyond We undertook a meta-analysis to assess and safety in patients with AIS &amp;gt;6 Methods: searched PubMed, EMBASE, Chinese Biomedical through July 2019. included studies involving early (≤6 h) vs. delayed (&amp;gt;6 selected AIS, based radiological evaluation criteria....

Abstract Copolymerization stands as a versatile and potent method for tailoring polymer properties by adjusting structural unit composition sequence distribution. However, achieving sequence‐controlled copolymerization in one‐step one‐pot process remains challenging. This study introduces solvent‐dependent strategy to produce block statistical copolyesters from 4‐phenyl‐2‐oxabicyclo[2.1.1]hexan‐3‐one (4 Ph ‐BL) ϵ ‐caprolactone ( ‐CL). The distinct kinetics of the two monomers enable facile...

In multiple instance learning, the training set consists of labeled bags that include unlabeled instances, and target is to predict labels unseen bags. A bag positive only if it contains at least one instance, otherwise a negative bag. Over past years, many popular machine learning algorithms have been adapted tackle problems. this paper, train discriminative classifier which generalize well, we present boosting approach with global smoothness regularization, in weak learners are either...

The co-occurrence features are the composition of base that have more discriminative power than individual features. Although they show promising performance in visual recognition applications such as object and scene recognition, discovery is usually a computational demanding task. Unlike previous feature mining methods fix order or rely on two-stage frequent pattern to select optimal co-occurrence, we propose novel branch-and-bound based algorithm can directly mine both conjunctions (AND)...