Visual Affordance and Function Understanding

2021 ◽  
Vol 54 (3) ◽  
pp. 1-35
Author(s):  
Mohammed Hassanin ◽  
Salman Khan ◽  
Murat Tahtali
Keyword(s):  
State Of The Art ◽  
Scene Understanding ◽  
Robot Vision ◽  
Literature Survey ◽  
Research Gaps ◽  
Open Problems ◽  
Object Affordances ◽  
Current State ◽  
High Level ◽  
And Function

Nowadays, robots are dominating the manufacturing, entertainment, and healthcare industries. Robot vision aims to equip robots with the capabilities to discover information, understand it, and interact with the environment, which require an agent to effectively understand object affordances and functions in complex visual domains. In this literature survey, first, “visual affordances” are focused on and current state-of-the-art approaches for solving relevant problems as well as open problems and research gaps are summarized. Then, sub-problems, such as affordance detection, categorization, segmentation, and high-level affordance reasoning, are specifically discussed. Furthermore, functional scene understanding and its prevalent descriptors used in the literature are covered. This survey also provides the necessary background to the problem, sheds light on its significance, and highlights the existing challenges for affordance and functionality learning.

scholarly journals A Survey of Graphical Page Object Detection with Deep Neural Networks

2021 ◽  
Author(s):  
Jwalin Bhatt ◽  
Khurram Azeem Hashmi ◽  
Muhammad Zeshan Afzal ◽  
Didier Stricker
Keyword(s):  
Deep Learning ◽  
Object Detection ◽  
Conceptual Understanding ◽  
Deep Neural Networks ◽  
State Of The Art ◽  
Learning Approaches ◽  
Document Images ◽  
Essential Information ◽  
Current State ◽  
High Level

In any document, graphical elements like tables, figures, and formulas contain essential information. The processing and interpretation of such information require specialized algorithms. Off-the-shelf OCR components cannot process this information reliably. Therefore, an essential step in document analysis pipelines is to detect these graphical components. It leads to a high-level conceptual understanding of the documents that makes digitization of documents viable. Since the advent of deep learning, the performance of deep learning-based object detection has improved many folds. In this work, we outline and summarize the deep learning approaches for detecting graphical page objects in the document images. Therefore, we discuss the most relevant deep learning-based approaches and state-of-the-art graphical page object detection in document images. This work provides a comprehensive understanding of the current state-of-the-art and related challenges. Furthermore, we discuss leading datasets along with the quantitative evaluation. Moreover, it discusses briefly the promising directions that can be utilized for further improvements.

scholarly journals MSA Transformer

2021 ◽  
Author(s):  
Roshan Rao ◽  
Jason Liu ◽  
Robert Verkuil ◽  
Joshua Meier ◽  
John F. Canny ◽  
...  
Keyword(s):  
Structure Learning ◽  
State Of The Art ◽  
Language Model ◽  
Language Modeling ◽  
Language Models ◽  
Multiple Sequence ◽  
Wide Margin ◽  
Current State ◽  
Individual Sequences ◽  
And Function

AbstractUnsupervised protein language models trained across millions of diverse sequences learn structure and function of proteins. Protein language models studied to date have been trained to perform inference from individual sequences. The longstanding approach in computational biology has been to make inferences from a family of evolutionarily related sequences by fitting a model to each family independently. In this work we combine the two paradigms. We introduce a protein language model which takes as input a set of sequences in the form of a multiple sequence alignment. The model interleaves row and column attention across the input sequences and is trained with a variant of the masked language modeling objective across many protein families. The performance of the model surpasses current state-of-the-art unsupervised structure learning methods by a wide margin, with far greater parameter efficiency than prior state-of-the-art protein language models.

scholarly journals Making rainfall features fun: scientific activities for teaching children aged 5–12 years

2016 ◽  
Vol 20 (5) ◽  
pp. 1751-1763 ◽  
Author(s):  
Auguste Gires ◽  
Catherine L. Muller ◽  
Marie-Agathe le Gueut ◽  
Daniel Schertzer
Keyword(s):  
Environmental Science ◽  
State Of The Art ◽  
Scientific Output ◽  
Pedagogical Practices ◽  
Research Projects ◽  
Scientific Culture ◽  
Children's Book ◽  
Current State ◽  
High Level ◽  
Rainy Days

Abstract. Research projects now rely on an array of different channels to increase impact, including high-level scientific output, tools, and equipment, but also communication, outreach, and educational activities. This paper focuses on education for children aged 5–12 years and presents activities that aim to help them (and their teachers) grasp some of the complex underlying issues in environmental science. More generally, it helps children to become familiarized with science and scientists, with the aim to enhance scientific culture and promote careers in this field. The activities developed are focused on rainfall: (a) designing and using a disdrometer to observe the variety of drop sizes; (b) careful recording of successive dry and rainy days and reproducing patterns using a simple model based on fractal random multiplicative cascades; and (c) collaboratively writing a children's book about rainfall. These activities are discussed in the context of current state-of-the-art pedagogical practices and goals set by project funders, especially in a European Union framework.

scholarly journals Deep Convolutional Neural Network for Pedestrian Detection with Multi-Levels Features Fusion

2018 ◽  
Vol 232 ◽  
pp. 01061
Author(s):  
Danhua Li ◽  
Xiaofeng Di ◽  
Xuan Qu ◽  
Yunfei Zhao ◽  
Honggang Kong
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
State Of The Art ◽  
Pedestrian Detection ◽  
Deep Convolutional Neural Network ◽  
High Quality ◽  
Low Level ◽  
Features Fusion ◽  
Current State ◽  
High Level

Pedestrian detection aims to localize and recognize every pedestrian instance in an image with a bounding box. The current state-of-the-art method is Faster RCNN, which is such a network that uses a region proposal network (RPN) to generate high quality region proposals, while Fast RCNN is used to classifiers extract features into corresponding categories. The contribution of this paper is integrated low-level features and high-level features into a Faster RCNN-based pedestrian detection framework, which efficiently increase the capacity of the feature. Through our experiments, we comprehensively evaluate our framework, on the Caltech pedestrian detection benchmark and our methods achieve state-of-the-art accuracy and present a competitive result on Caltech dataset.

A Pragmatic Approach to Intrusion Response Metrics

2012 ◽  
pp. 1-22
Author(s):  
Chris Strasburg ◽  
Johnny Wong
Keyword(s):  
State Of The Art ◽  
Arms Race ◽  
Current Work ◽  
Diverse Population ◽  
Pragmatic Approach ◽  
Research Gaps ◽  
Intrusion Response ◽  
Current State ◽  
Production Environments ◽  
Response Capability

The arms race between cyber attackers and defenders has evolved to the point where an effective counter-measure strategy requires the use of an automated, distributed, and coordinated response. A key difficulty in achieving this goal lies in providing reliable measures by which to select appropriate responses to a wide variety of potential intrusions in a diverse population of network environments. In this chapter, the authors provide an analysis of the current state of automated intrusion response metrics from a pragmatic perspective. This analysis includes a review of the current state of the art as well as descriptions of the steps required to implement current work in production environments. The authors also discuss the research gaps that must be filled to improve security professionals’ ability to implement an automated intrusion response capability.

scholarly journals Editor's note

2008 ◽  
Vol 41 (3) ◽  
pp. i-ii
Keyword(s):  
Native Speaker ◽  
State Of The Art ◽  
Social Recognition ◽  
World Englishes ◽  
Future Research ◽  
Attitudes And Beliefs ◽  
Current State ◽  
English Speaking ◽  
Native English Speaking Teachers ◽  
And Function

In this issue's state-of-the-art article, Lucie moussu and Enric Llurda discuss research on non-native English-speaking teachers of English, highlighting throughout the need for more considered social recognition of the native-speaker/non-native-speaker identity. After discussing the current legitimacy of such labels in the light of research, they argue for a more reasoned approach both to the definition and function of non-native-speaker teachers, in particular in light of recent research on World Englishes. Particular attention is paid to the perception of the non-native and native-speaker teachers by students and to the attitudes and beliefs of both these students and hiring staff regarding such teachers' perceived differences, strengths, and weaknesses. In the final part of the paper the authors address past and present research methods used in studies and suggest areas, such as longitudinal and classroom-based studies, where future research might usefully add to the current state of knowledge. The article is accompanied by Amir Soheili-Mehr's review of four recent books.

scholarly journals A Review of Stochastic Programming Methods for Optimization of Process Systems Under Uncertainty

2021 ◽  
Vol 2 ◽  
Author(s):  
Can Li ◽  
Ignacio E. Grossmann
Keyword(s):  
Stochastic Programming ◽  
Systems Engineering ◽  
State Of The Art ◽  
Mathematical Framework ◽  
Process Systems Engineering ◽  
Process Industries ◽  
Process Systems ◽  
Current State ◽  
Engineering Problems ◽  
High Level

Uncertainties are widespread in the optimization of process systems, such as uncertainties in process technologies, prices, and customer demands. In this paper, we review the basic concepts and recent advances of a risk-neutral mathematical framework called “stochastic programming” and its applications in solving process systems engineering problems under uncertainty. This review intends to provide both a tutorial for beginners without prior experience and a high-level overview of the current state-of-the-art developments for experts in process systems engineering and stochastic programming. The mathematical formulations and algorithms for two-stage and multistage stochastic programming are reviewed with illustrative examples from process industries. The differences between stochastic programming under exogenous uncertainty and endogenous uncertainties are discussed. The concepts and several data-driven methods for generating scenario trees are also reviewed.

scholarly journals Recent Advances and Challenges in XML Document Routing

2010 ◽  
pp. 136-150
Author(s):  
Mirella M. Moro ◽  
Zografoula Vagena ◽  
Vassilis J. Tsotras
Keyword(s):  
Data Exchange ◽  
State Of The Art ◽  
Data Delivery ◽  
Open Problems ◽  
Ip Address ◽  
Current State ◽  
Recent Advances ◽  
Xml Document

Content-based routing is a form of data delivery whereby the flow of messages is driven by their content rather than the IP address of their destination. With the recognition of XML as the standard for data exchange, specialized XML routing services become necessary. In this chapter, the authors first demonstrate the relevance of such systems by presenting different world application scenarios where XML routing systems are needed and/or employed. Then, they present a survey of the current state of the art. Lastly, they attempt to identify issues and problems that have yet to be investigated. Their discussion will help identify open problems and issues and suggest directions for further research in the context of such systems.

A Brief History of Prosthetics and Orthotics of the Lower Body and Their Types

2021 ◽  
pp. 365-380
Author(s):  
Dheeman Bhuyan ◽  
Kaushik Kumar
Keyword(s):  
Historical Perspective ◽  
State Of The Art ◽  
Lower Body ◽  
Form And Function ◽  
Current State ◽  
History Of ◽  
And Function ◽  
Shed Light

Prosthetics and orthotics are items taken for granted in today's day and age. However, this has not always been the case. The history of these everyday items is long and very colorful. In this chapter, the authors shed light on the history and development of prosthetics and orthotics of the lower body in order to better understand the current state of the art in the fields. A historical perspective is provided followed by enumeration of the types of devices and techniques available without going into the form and function of individual products.

Critical Analysis of Digital Steganography

2011 ◽  
pp. 352-382
Author(s):  
Hafiz Malik
Keyword(s):  
Performance Analysis ◽  
Information Hiding ◽  
Critical Analysis ◽  
State Of The Art ◽  
Covert Channel ◽  
Covert Communication ◽  
Open Problems ◽  
Current State ◽  
Channel Type

This chapter provides critical analysis of current state-of-the-art in steganography. First part of the this chapter provides the classification of steganography based on the underlying information hiding methodology used and covert-channel type, and desired features of the information hiding used for covert communication. This chapter also discusses various known steganalysis techniques developed to counteract the covert-communication and highlights limitations of existing steganographic techniques. Performance analysis of commonly used shareware/freeware steganographic tools and steganalysis tools is also provided in this chapter. Some open problems in covert-communication are also discussed.

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