493 research outputs found
Fine-Grained Object Recognition and Zero-Shot Learning in Remote Sensing Imagery
Fine-grained object recognition that aims to identify the type of an object
among a large number of subcategories is an emerging application with the
increasing resolution that exposes new details in image data. Traditional fully
supervised algorithms fail to handle this problem where there is low
between-class variance and high within-class variance for the classes of
interest with small sample sizes. We study an even more extreme scenario named
zero-shot learning (ZSL) in which no training example exists for some of the
classes. ZSL aims to build a recognition model for new unseen categories by
relating them to seen classes that were previously learned. We establish this
relation by learning a compatibility function between image features extracted
via a convolutional neural network and auxiliary information that describes the
semantics of the classes of interest by using training samples from the seen
classes. Then, we show how knowledge transfer can be performed for the unseen
classes by maximizing this function during inference. We introduce a new data
set that contains 40 different types of street trees in 1-ft spatial resolution
aerial data, and evaluate the performance of this model with manually annotated
attributes, a natural language model, and a scientific taxonomy as auxiliary
information. The experiments show that the proposed model achieves 14.3%
recognition accuracy for the classes with no training examples, which is
significantly better than a random guess accuracy of 6.3% for 16 test classes,
and three other ZSL algorithms.Comment: G. Sumbul, R. G. Cinbis, S. Aksoy, "Fine-Grained Object Recognition
and Zero-Shot Learning in Remote Sensing Imagery", IEEE Transactions on
Geoscience and Remote Sensing (TGRS), in press, 201
A STUDY EXAMINING THE ATTITUDE OF UAE VOCATIONAL INSTITUTES GRADUATING STUDENTS TOWARDS ENTREPRENEURSHIP
Entrepreneurship is important for the economy’s growth especially in the current time of recession. This paper aims to examine the attitude of graduating students of UAE vocational institutes towards entrepreneurship and also assess its influencing factors. Research highlights the ratio of graduating student intending to start their own business as the majority of Middle East population is expats and family businesses are considered to be very important in Middle Eastern economies, contributing 60% to GDP and employing over 80% of the workforce (Middle East Family Business Survey, 2016). By applying Multivariate regression analysis on the data collected from 4 vocational institutes across UAE through structured questionnaire; it is found that family experience has a significant impact on the positive attitude of graduates towards entrepreneurship. The surprising finding of this paper is that in spite of positive attitude of graduate towards entrepreneurship, their enterprise knowledge is low. Results are encouraging for future studies to compare the entrepreneurial attitude for different nationalities in private and public sector. As there is less support from institutions for entrepreneurs, the findings of this research would be beneficial for the academic institutions and government to strategise initiatives for their easy access to training and financial aid.  
Strategic style change using grammar transformations
New styles can be created by modifying existing ones. In order to formalize style change using grammars, style has to be formally defined in the design language of a grammar. Previous studies in the use of grammars for style change do not give explicit rationale for transformation. How would designers decide which rules to modify in a grammar to generate necessary changes in style(s) of designs? This paper addresses the aforementioned issues by presenting a framework for strategic style change using goal-driven grammar transformations. The framework employs a style description scheme constructed by describing the aesthetic qualities of grammar elements using adjectival descriptors. We present techniques for the formal definition of style in the designs generated by grammars. The utility of the grammar transformation framework and the style description scheme is tested with an example of mobile phone design. Analyses reveal that constraining rules in grammars is a valid technique for generating designs with a dominance of desired adjectival descriptors, thus aiding in strategic style change
SOCIAL EVILS IN MEDIA: CHALLENGES AND SOLUTIONS IN 21ST CENTURY
echnology and social media has become a vital part of daily lives of people, especially children. There are advantages of using technology and being active on social media but there are equal disadvantages and risks that come along with excessive use of electronic devices. As per American Academy of Pediatricians children are spending 7 hours a day on media such as computers, phones, I-pads, television and other electronic devises. A child as young as age 2 starts using mobile phone to view rhymes and videos on you tube which brings many risks to their health and wellbeing. This paper reviews the literature and discusses the problems caused by social media, technology such as obesity, aggressive behavior, negative effects on mental health, cyber bullying, texting/sexting and contact to problematic and illegal content etc. in children from age 2 till 18. The paper highlights the ratio of UAE parents, who are aware of social evils and take measures to protect their children. Also, the study attempts to provide solutions and guidelines from pediatricians that would be helpful for parents and individuals, in addressing the difficulties instigated by electronic devices and social media in addition to molding their children as healthier citizens. We hope that this paper will make relevant institutions provide more educational platforms to parents in order to spread awareness about the impact of media on children along with appropriate measures that can be taken to deal with it. 
A Deep Multi-Attention Driven Approach for Multi-Label Remote Sensing Image Classification
Deep learning (DL) based methods have been found popular in the framework of remote sensing (RS) image scene classification. Most of the existing DL based methods assume that training images are annotated by single-labels, however RS images typically contain multiple classes and thus can simultaneously be associated with multi-labels. Despite the success of existing methods in describing the information content of very high resolution aerial images with RGB bands, any direct adaptation for high-dimensional high-spatial resolution RS images falls short of accurate modeling the spectral and spatial information content. To address this problem, this paper presents a novel approach in the framework of the multi-label classification of high dimensional RS images. The proposed approach is based on three main steps. The first step describes the complex spatial and spectral content of image local areas by a novel KBranch CNN that includes spatial resolution specific CNN branches. The second step initially characterizes the importance scores of different local areas of each image and then defines a global descriptor for each image based on these scores. This is achieved by a novel multi-attention strategy that utilizes the bidirectional long short-term memory networks. The final step achieves the classification of RS image scenes with multilabels. Experiments carried out on BigEarthNet (which is a large-scale Sentinel-2 benchmark archive) show the effectiveness of the proposed approach in terms of multi-label classification accuracy compared to the state-of-the-art approaches. The code of the proposed approach is publicly available at https://gitlab.tubit.tuberlin.de/rsim/MAML-RSIC.EC/H2020/759764/EU/Accurate and Scalable Processing of Big Data in Earth Observation/BigEart
Can Low Molecular Weight Heparins Circumvent the Problem of Coumadine and Chemotherapy Interaction in Cancer Patients with Prosthetic Heart Valves?
Refugee Protection as Human Rights Protection: International Principles and Practice in India
This article focuses on the relationship
between international human rights
standards and refugee protection. The
foundational status of the Universal
Declaration of Human Rights and other
human rights treaties are surveyed in
light of India's international legal obligations.
The authors argue that international
human rights law and practice
have had a significant impact on the
protection activities of the Ofice of the
United Nations High Commissioner for
Refugees (UNHCR) both in countries
of asylum, countries of origin and in
relation to the United Nations and other
human rights actors. In this context,
courts and national human rights institutions
are important players in safeguarding
the rights of refugees. As none
of the countries of South Asia is party to
the international refugee instruments
nor have any of them adopted a national
refugee law or procedure, the activities
of the Indian National Human Rights
Commission stand out as a positive example
of national institution expanding
the legal protection of refugees in the
region.Cet article porte sur la relation entre
critères internationaux en matière de
droits humains et protection des réfugiés.
Les statuts fondateurs de la
Déclaration Universelle des droits de
l'Homme et d'autres traités sur les
droits humains sont analysés à la lumière
des obligations juridiques internationales de l'Inde. Les auteurs
développent une argumentation selon
laquelle les lois et pratiques internationales
en matière de droits humains ont
un impact significatif sur les activités
de protection assurées par l'Office du
Haut Commissariat des Nations Unies
aux réfugiés, autant dans les pays asiles,
que dans les pays d'origine, et ce
dans toute interaction entre les Nations
Unies et les autres intervenants en matière
de droits humains. Dans un tel
contexte, les tribunaux et les institutions
nationales traitant des droits humains
sont des acteurs cruciaux en ce
qui concerne la protection des droits des
réfugiés. Comme aucun des pays d'Asie
du Sud n'est engagé dans les grands
mécanismes internationaux en matière
de droit des réfugiés, et comme aucun
d'entre eux n'a adopté de loi ou procédure
nationale en matière de droit des
réfugiés, les activités de la Commission
Nationale Indienne des droits de
l'Homme s'avèrent représenter un
exemple positif d'institution nationale
assurant le progrès de la protection légale
des réfugiés dans cette région du
monde
Comparative Analysis of Fractal Properties of Solar Faculae
Present study is aimed at investigating the solar faculae area from 1990 to 2007 which partially covered the22nd and 23rd solar cycle. Rescaled Range Analysis (RRA) and Detrended Fluctuation Analysis (DFA) have beenadopted to evaluate the behaviour of nonlinear dynamics of solar faculae area. Results show that the value of Hurstexponent for solar faculae area from RRA and DFA is negatively correlated. It means it is non-persistent and longrange correlated. Obtained result is inaccurate so the only solution is to transform the data into stationary data by takingdifferencing. RRA is applied on residuals and RRA to evaluate the fractal property of the time series. Solar faculae areainvestigated in this study is fractal in nature and predictable ass well. Moreover, the time series of solar faculae area isnon-linear as established by the Brock – Dechert – Scheinkman (BDS) test result
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