scholarly journals Relation-Guided Spatial Attention and Temporal Refinement for Video-Based Person Re-Identification

2020 ◽  
Vol 34 (07) ◽  
pp. 11434-11441
Author(s):  
Xingze Li ◽  
Wengang Zhou ◽  
Yun Zhou ◽  
Houqiang Li
Keyword(s):  
Spatial Attention ◽  
Video Surveillance ◽  
State Of The Art ◽  
The State ◽  
Temporal Information ◽  
Feature Representations ◽  
Art Performance ◽  
The Individual ◽  
Significant Application

Video-based person re-identification has received considerable attention in recent years due to its significant application in video surveillance. Compared with image-based person re-identification, video-based person re-identification is characterized by a much richer context, which raises the significance of identifying informative regions and fusing the temporal information across frames. In this paper, we propose two relation-guided modules to learn reinforced feature representations for effective re-identification. First, a relation-guided spatial attention (RGSA) module is designed to explore the discriminative regions globally. The weight at each position is determined by its feature as well as the relation features from other positions, revealing the dependence between local and global contents. Based on the adaptively weighted frame-level feature, then, a relation-guided temporal refinement (RGTR) module is proposed to further refine the feature representations across frames. The learned relation information via the RGTR module enables the individual frames to complement each other in an aggregation manner, leading to robust video-level feature representations. Extensive experiments on four prevalent benchmarks verify the state-of-the-art performance of the proposed method.

scholarly journals Recent Advances in Dialogue Machine Translation

Information ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 484
Author(s):  
Siyou Liu ◽  
Yuqi Sun ◽  
Longyue Wang
Keyword(s):  
Personality Traits ◽  
Machine Translation ◽  
State Of The Art ◽  
The State ◽  
Comprehensive Review ◽  
Survey Paper ◽  
Recent Advances ◽  
Art Performance ◽  
Hotel Booking ◽  
Significant Application

Recent years have seen a surge of interest in dialogue translation, which is a significant application task for machine translation (MT) technology. However, this has so far not been extensively explored due to its inherent characteristics including data limitation, discourse properties and personality traits. In this article, we give the first comprehensive review of dialogue MT, including well-defined problems (e.g., 4 perspectives), collected resources (e.g., 5 language pairs and 4 sub-domains), representative approaches (e.g., architecture, discourse phenomena and personality) and useful applications (e.g., hotel-booking chat system). After systematical investigation, we also build a state-of-the-art dialogue NMT system by leveraging a breadth of established approaches such as novel architectures, popular pre-training and advanced techniques. Encouragingly, we push the state-of-the-art performance up to 62.7 BLEU points on a commonly-used benchmark by using mBART pre-training. We hope that this survey paper could significantly promote the research in dialogue MT.

scholarly journals A Graph-based Evolutionary Algorithm for Automated Machine Learning

2020 ◽  
Author(s):  
Fei Qi ◽  
Zhaohui Xia ◽  
Gaoyang Tang ◽  
Hang Yang ◽  
Yu Song ◽  
...  
Keyword(s):  
Machine Learning ◽  
Evolutionary Algorithm ◽  
Parameter Optimization ◽  
State Of The Art ◽  
The State ◽  
Complex Structures ◽  
Architecture Evolution ◽  
Automated Machine Learning ◽  
Art Performance

As an emerging field, Automated Machine Learning (AutoML) aims to reduce or eliminate manual operations that require expertise in machine learning. In this paper, a graph-based architecture is employed to represent flexible combinations of ML models, which provides a large searching space compared to tree-based and stacking-based architectures. Based on this, an evolutionary algorithm is proposed to search for the best architecture, where the mutation and heredity operators are the key for architecture evolution. With Bayesian hyper-parameter optimization, the proposed approach can automate the workflow of machine learning. On the PMLB dataset, the proposed approach shows the state-of-the-art performance compared with TPOT, Autostacker, and auto-sklearn. Some of the optimized models are with complex structures which are difficult to obtain in manual design.

scholarly journals Estado del arte del rendimiento académico en la educación media

2014 ◽  
Vol 17 (17) ◽  
pp. 197-220
Author(s):  
Oscar Hernán Cerquera Losada
Keyword(s):  
Academic Achievement ◽  
Secondary Education ◽  
State Of The Art ◽  
School Achievement ◽  
The State ◽  
Main Research ◽  
The World ◽  
El Sistema ◽  
The Individual

Este documento muestra el Estado de arte de los determinantes del rendimiento académico en la educación media, teniendo en cuenta las principales investigaciones realizadas, tanto a nivel nacional como internacional, acerca de los factores que influyen en el logro escolar de los estudiantes. Con este trabajo, se busca establecer las principales variables, tanto en Colombia como en algunos lugares del mundo, que afectan el desempeño académico de los estudiantes. Este documento se organiza en dos sesiones, determinantes a nivel mundial y determinantes a nivel colombiano; cada sesión clasifica las investigaciones de acuerdo a los factores del estudiante, de la escuela y las características organizacionales y políticas. A pesar de existir muchas investigaciones sobre el tema, aún no se ha llegado a un consenso general sobre cómo determinar los factores del  rendimiento académico, pues en la realidad son muchas las características del individuo, la escuela o el sistema que se relacionan entre sí de diferente manera y pueden afectar el logro estudiantil.ABSTRACTThis document shows the state of the art of the determinants of academic achievement in secondary education, taking into account the main research conducted, both nationally and internationally, about the factors that influence school achievement of students. With this paper, we seek to establish the main variables which affect the academic achievement of students in Colombia as well as in some parts of the world. This document is organized in two sessions: world and Colombian determinants; each session classifies research according to the factors of the student, the school and organizational and political characteristics. Although there is much research on the topic so far it has not been possible to reach a consensus on how to determine the factors of academic achievement, because in reality many characteristics of the individual, of the school or of the system relate to each other differently and can affect student achievement.RESUMOEste documento mostra o Estado da arte dos determinantes do rendimento escolar no ensino medio, tendo em conta às principais pesquisas realizadas, tanto a nível nacional como internacionalmente, sobres os fatores que influenciam o desempenho escolar dos estudantes. Com este trabalho, se procura estabelecer as principais variáveis, tanto na Colômbia e em alguns lugares do mundo, afetando o desempenho acadêmico dos estudantes. Este documento está organizado em duas sessões, determinantes a nível mundial e determinantes a nível colombiano; cada sessão clasifica as pesquisas de acordó a os fatores do estudante, da escola e das características organizacionais e políticas. Embora haja muitas pesquisas sobre o tema, ainda não se chegou a um consenso geral sobre os fatores determinantes no desempenho acadêmico, porque na realidade são muitas as características do indivíduo, a escola ou o sistema que se relacionam uns com os outros de forma diferente e podem afetar o desempenho acadêmico.

Planning of Material Handling : Literature Review

2019 ◽  
Vol 13 (2) ◽  
pp. 29-44
Author(s):  
Péter Telek ◽  
Ákos Cservenák
Keyword(s):  
Literature Review ◽  
Material Handling ◽  
State Of The Art ◽  
The State ◽  
Integrated Planning ◽  
Complex Process ◽  
Individual Planning ◽  
The Individual ◽  
The University

Nowadays, there are many well proved, effective processes to solve planning tasks in the field of material handling used advanced calculations forms and software. Unfortunately, most of them are used for individual tasks, so the applicability of their results is limited. The Institute of Logistics of the University of Miskolc has been working on integrated planning of handling machines for decades, where the individual planning tasks have to be solved together in a complex process. The main aim of this paper to give an overview about the state of the art of the planning of material handling, based on a literature review of the Science Direct publication database. As a result of this research we can determine some new direction for the planning of material handling.

Researching Telework

2000 ◽  
pp. 255-276 ◽  
Author(s):  
Nicole B. Ellison
Keyword(s):  
Organizational Culture ◽  
State Of The Art ◽  
The State ◽  
Future Research ◽  
Scholarly Literature ◽  
Home Based ◽  
The Family ◽  
The Individual ◽  
The Impact

This chapter examines the state of the art in telework research. The author reviews the most central scholarly literature examining the phenomenon of telework (also called home-based work or telecommuting) and develops a framework for organizing this body of work. She organizes previous research on telework into six major thematic concerns relating to the definition, measurement, and scope of telework; management of teleworkers; travel-related impacts of telework; organizational culture and employee isolation; boundaries between “home” and “work” and the impact of telework on the individual and the family. Areas for future research are suggested.

Highly efficient thermophones based on freestanding single-walled carbon nanotube films

2019 ◽  
Vol 4 (5) ◽  
pp. 1158-1163 ◽  
Author(s):  
Stepan A. Romanov ◽  
Ali E. Aliev ◽  
Boris V. Fine ◽  
Anton S. Anisimov ◽  
Albert G. Nasibulin
Keyword(s):  
Carbon Nanotubes ◽  
Carbon Nanotube ◽  
State Of The Art ◽  
Single Walled Carbon Nanotubes ◽  
The State ◽  
Single Walled Carbon Nanotube ◽  
Single Walled Carbon ◽  
Highly Efficient ◽  
Art Performance ◽  
Walled Carbon Nanotubes

We present the state-of-the-art performance of air-coupled thermophones made of thin, freestanding films of randomly oriented single-walled carbon nanotubes (SWCNTs).

scholarly journals SOGNet: Scene Overlap Graph Network for Panoptic Segmentation

2020 ◽  
Vol 34 (07) ◽  
pp. 12637-12644 ◽  
Author(s):  
Yibo Yang ◽  
Hongyang Li ◽  
Xia Li ◽  
Qijie Zhao ◽  
Jianlong Wu ◽  
...  
Keyword(s):  
State Of The Art ◽  
Ground Truth ◽  
The State ◽  
Graph Representation ◽  
Weak Supervision ◽  
Scene Graph ◽  
Art Performance ◽  
Segmentation Task ◽  
Instance Segmentation ◽  
Relation Matrix

The panoptic segmentation task requires a unified result from semantic and instance segmentation outputs that may contain overlaps. However, current studies widely ignore modeling overlaps. In this study, we aim to model overlap relations among instances and resolve them for panoptic segmentation. Inspired by scene graph representation, we formulate the overlapping problem as a simplified case, named scene overlap graph. We leverage each object's category, geometry and appearance features to perform relational embedding, and output a relation matrix that encodes overlap relations. In order to overcome the lack of supervision, we introduce a differentiable module to resolve the overlap between any pair of instances. The mask logits after removing overlaps are fed into per-pixel instance id classification, which leverages the panoptic supervision to assist in the modeling of overlap relations. Besides, we generate an approximate ground truth of overlap relations as the weak supervision, to quantify the accuracy of overlap relations predicted by our method. Experiments on COCO and Cityscapes demonstrate that our method is able to accurately predict overlap relations, and outperform the state-of-the-art performance for panoptic segmentation. Our method also won the Innovation Award in COCO 2019 challenge.

scholarly journals Appearance and Motion Enhancement for Video-Based Person Re-Identification

2020 ◽  
Vol 34 (07) ◽  
pp. 11394-11401
Author(s):  
Shuzhao Li ◽  
Huimin Yu ◽  
Haoji Hu
Keyword(s):  
Semantic Information ◽  
State Of The Art ◽  
Complex Model ◽  
The State ◽  
Final Model ◽  
Backbone Network ◽  
Proposed Model ◽  
Art Performance ◽  
Attribute Recognition

In this paper, we propose an Appearance and Motion Enhancement Model (AMEM) for video-based person re-identification to enrich the two kinds of information contained in the backbone network in a more interpretable way. Concretely, human attribute recognition under the supervision of pseudo labels is exploited in an Appearance Enhancement Module (AEM) to help enrich the appearance and semantic information. A Motion Enhancement Module (MEM) is designed to capture the identity-discriminative walking patterns through predicting future frames. Despite a complex model with several auxiliary modules during training, only the backbone model plus two small branches are kept for similarity evaluation which constitute a simple but effective final model. Extensive experiments conducted on three popular video-based person ReID benchmarks demonstrate the effectiveness of our proposed model and the state-of-the-art performance compared with existing methods.

Library simulation: The computer locates the data needle in the journal haystack

SIMULATION ◽  
1968 ◽  
Vol 10 (2) ◽  
pp. 69-70
Author(s):  
Joseph J. Mangino
Keyword(s):  
Information Technology ◽  
State Of The Art ◽  
Current Data ◽  
The State ◽  
High Response ◽  
Operational System ◽  
Work Assignment ◽  
Normal Text ◽  
The Individual

Developments in the information technology make pos sible the use of computer searching of normal text, to locate the articles of interest to match a professional pro file. These profiles are computer equivalents of an indi vidual's description of his work assignment, and are stored in the computer to be compared with new or current data being processed in normal text by the computer. The data is the author's/publisher's abstract of the article in the orig inal form. The computer reads the data and compares it with over 2500 profiles. When a match occurs, the abstract is selectively printed out and sent to the individual. This is an operational system used in the IBM Technical Informa tion Retrieval Center to keep IBMers aware of the state-of- the-art in their specialty. Feedback statistics are included to indicate the high response and satisfaction criteria of the users.

scholarly journals Uncertainty-Aware Few-Shot Image Classification

2021 ◽  
Author(s):  
Zhizheng Zhang ◽  
Cuiling Lan ◽  
Wenjun Zeng ◽  
Zhibo Chen ◽  
Shih-Fu Chang
Keyword(s):  
Neural Network ◽  
Image Classification ◽  
State Of The Art ◽  
Metric Learning ◽  
The State ◽  
Modeling Uncertainty ◽  
Support Set ◽  
Art Performance ◽  
Graph Based Model ◽  
Query Sample

Few-shot image classification learns to recognize new categories from limited labelled data. Metric learning based approaches have been widely investigated, where a query sample is classified by finding the nearest prototype from the support set based on their feature similarities. A neural network has different uncertainties on its calculated similarities of different pairs. Understanding and modeling the uncertainty on the similarity could promote the exploitation of limited samples in few-shot optimization. In this work, we propose Uncertainty-Aware Few-Shot framework for image classification by modeling uncertainty of the similarities of query-support pairs and performing uncertainty-aware optimization. Particularly, we exploit such uncertainty by converting observed similarities to probabilistic representations and incorporate them to the loss for more effective optimization. In order to jointly consider the similarities between a query and the prototypes in a support set, a graph-based model is utilized to estimate the uncertainty of the pairs. Extensive experiments show our proposed method brings significant improvements on top of a strong baseline and achieves the state-of-the-art performance.

Sign in / Sign up

Export Citation Format

Share Document