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Learning to Interpret Satellite Images in Global Scale Using Wikipedia [article]

Burak Uzkent, Evan Sheehan, Chenlin Meng, Zhongyi Tang, Marshall Burke, David Lobell, Stefano Ermon
2019 arXiv   pre-print
We then propose two strategies to learn representations of satellite images by predicting properties of the corresponding articles from the images.  ...  Image recognition focuses on global features to associate an image x i with a label w i .  ...  This is important as it requires a complex network to learn from large-scale datasets such as WikiSatNet.  ... 
arXiv:1905.02506v3 fatcat:tqqvmoum5jfnbll4xujizsaqnu

Deep Learning the City : Quantifying Urban Perception At A Global Scale [article]

Abhimanyu Dubey, Nikhil Naik, Devi Parikh, Ramesh Raskar, César A. Hidalgo
2016 arXiv   pre-print
Our results show that crowdsourcing combined with neural networks can produce urban perception data at the global scale.  ...  Using this data, we train a Siamese-like convolutional neural architecture, which learns from a joint classification and ranking loss, to predict human judgments of pairwise image comparisons.  ...  So scaling up the computational methods to map urban appearance from the regional scale, to the global scale, requires methods that can be trained on larger and sparser datasets-which contain a large,  ... 
arXiv:1608.01769v2 fatcat:jwrf5fdbyfbhzaonvmsa44choa

Leveraging EfficientNet and Contrastive Learning for Accurate Global-scale Location Estimation [article]

Giorgos Kordopatis-Zilos, Panagiotis Galopoulos, Symeon Papadopoulos, Ioannis Kompatsiaris
2021 arXiv   pre-print
In this paper, we address the problem of global-scale image geolocation, proposing a mixed classification-retrieval scheme.  ...  The second introduces a new residual architecture that is trained with contrastive learning to map input images to an embedding space that minimizes the pairwise geodesic distance of same-location images  ...  In this study, we focus on global-scale location estimation from single images, which is the most challenging problem setting.  ... 
arXiv:2105.07645v1 fatcat:y2uryasmjfbv7fompit72fj42y

Local2Global: Scaling global representation learning on graphs via local training [article]

Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong, Marya Bazzi, Mihai Cucuringu
2021 arXiv   pre-print
We propose a decentralised "local2global" approach to graph representation learning, that one can a-priori use to scale any embedding technique.  ...  Preliminary results on medium-scale data sets (up to ∼7K nodes and ∼200K edges) are promising, with a graph reconstruction performance for local2global that is comparable to that of globally trained embeddings  ...  Our preliminary results on medium-scale data sets are promising and achieve comparable accuracy on graph reconstruction as globally trained VGAE embeddings.  ... 
arXiv:2107.12224v1 fatcat:zguygof3hndo5pddpkofsg36na

Probabilistic Relational Learning and Inductive Logic Programming at a Global Scale [chapter]

David Poole
2011 Lecture Notes in Computer Science  
Given such data, we can also learn from it.  ...  Thus probabilistic relational learning and inductive logic programming need to be a foundation of the semantic web.  ...  There are still many open fundamental problems for representations, inference and learning.  ... 
doi:10.1007/978-3-642-21295-6_3 fatcat:jy35vekfhzchxfab4te3qek3qe

Large-Scale Global Optimization Using Cooperative Coevolution with Variable Interaction Learning [chapter]

Wenxiang Chen, Thomas Weise, Zhenyu Yang, Ke Tang
2010 Parallel Problem Solving from Nature, PPSN XI  
The efficiency of the newly proposed framework is evaluated on the set of large-scale optimization benchmarks.  ...  In this paper, we propose a new CC framework named Cooperative Coevolution with Variable Interaction Learning (CCVIL), which initially considers all variables as independent and puts each of them into  ...  large-scale op- Instead of setting the group sizes as a constant or defining a set of values from which to choose them, we allow the optimization process to adapt them by learning the interaction between  ... 
doi:10.1007/978-3-642-15871-1_31 dblp:conf/ppsn/ChenWYT10 fatcat:dxvo4epodzhhjimcy5tdi4lzkq

Use of the Global Assessment of Function scale in learning disability

Patricia Oliver, Sherva Cooray, Peter Tyrer, Domenic Cicchetti
2003 British Journal of Psychiatry  
The Global Assessment of Function (GAF) scale is widely used in adult psychiatric practice and research but it has not often been used in learning disability, which is inherently more complex.  ...  Aims To evaluate the reliability of GAF in the assessment of learning disability.  ...  ACKNOWLEDGEMENTS ACKNOWLEDGEMENTS We thank Parkside Health NHS Trust for their fund-We thank Parkside Health NHS Trust for their funding and support of the Parkside Learning Disability ing and support  ... 
doi:10.1192/bjp.182.44.s32 fatcat:tyelh3qj7be2lf7ft4dk2agz2a

Global Exponential Stability of Learning-Based Fuzzy Networks on Time Scales

Juan Chen, Zhenkun Huang, Jinxiang Cai
2015 Abstract and Applied Analysis  
We investigate a class of fuzzy neural networks with Hebbian-type unsupervised learning on time scales.  ...  Moreover, our results reveal some new learning behavior of fuzzy synapses on time scales which are seldom discussed in the literature.  ...  Conclusion By using the time scale calculus theory and the Lyapunov functional method, we derive some sufficient conditions to ensure the global exponential stability of learning-based fuzzy networks on  ... 
doi:10.1155/2015/283519 fatcat:64xqm7ajibfvzc2rt5qsjfemim

Exploring the challenges in scaling up the delivery of action learning facilitator training within a global organisation

Sonja Antell, John Heywood
2015 Action Learning: Research and Practice  
The focus of the paper is to explore learning, challenges and opportunities created by scaling up the delivery of ALFT to a global target audience of approximately 700 people.  ...  Action Learning Associates (ALA) has been working with an international organisation for three years to deliver the global 'First Line Manager Programme' (FLMP).  ...  Learning for all those involved Learning for ALA For ALA, the experience of scaling up for delivery reinforced the value of a strong team and a single shared action learning methodology.  ... 
doi:10.1080/14767333.2015.1001552 fatcat:d47nsu4725hovd6p356u2vvfm4

Learning Multi-scale Features and Batch-normalized Global Features for Person Re-identification

Zongjing Cao, Hyo Jong Lee
2020 IEEE Access  
His research interests lie in deep learning, computer vision, and image processing. His more recent research focuses on image retrieval and person reidentification.  ...  In the training phase, the triplet loss and identification loss are calculated by using multi-scale global features and batch-normalized global features respectively.  ...  ., deep learning methods that are pose-guided, deep learning methods with part features and deep learning methods with the global feature. All the experiments evaluate the single-query setting.  ... 
doi:10.1109/access.2020.3029594 fatcat:6opjvzmy6bgujewgituqkgv7tm

Development and Validation of the Purdue Global Online Teaching Effectiveness Scale

Elizabeth Reyes-Fournier, Edward J. Cumella, Michelle March, Jennifer Pedersen, Gabrielle Blackman
2020 Online Learning  
, student evaluations, asynchronous learning.  ...  Students enrolled in exclusively online coursework and programs at Purdue University Global, N = 213, completed the survey, rating the effectiveness of their instructors.  ...  The lowest correlations with OTES scores occurred for the SEOTE Active Learning and Student Cooperation factors.  ... 
doi:10.24059/olj.v24i2.2071 fatcat:zuyikkwgrbehdgu4wg3qsnrhky

Learning distance effect on lignite quality variables at global and local scales

Cem Yaylagul, Bulent Tutmez
2020 International Journal of Coal Science & Technology  
In this way, the critical roles of spatial weights provided by the coordinates have been specified at a global scale.  ...  Determining scale and variable effects have critical importance in developing an energy resource policy.  ...  Globally, the GAM structure can be expressed as follows (James et al. 2013 ): Fig. 1 Location map Learning distance effect on lignite quality variables at global and local scales y i ¼ b 0 þ X p j¼1  ... 
doi:10.1007/s40789-020-00372-7 fatcat:3r4dkd7bnjdpdooemc76z5dp4q

International large-scale assessments, the Global Alliance to Monitor Learning (GAML) and adult education systems

Shalini Singh
2020 Zeitschrift für Weiterbildungsforschung - Report  
The methodology includes a comparison of four ILSAs and an analysis of their linkages with the Global Alliance to Monitor Learning (GAML), SDGs and global policy changes in the adult education systems  ...  International Large-scale Assessments (ILSAs) have become the quality checklist for education systems globally, especially since the adoption of the Sustainable Development Goals (SDGs) in 2015.  ...  Introduction International Large-scale Assessments (ILSAs) have become the quality checklist for education systems globally, especially since the adoption of the Sustainable Development Goals (SDGs) in  ... 
doi:10.1007/s40955-020-00161-4 fatcat:j56ovcevlrdjxidq5afu32er7u

Using Deep Learning to Explore Local Physical Similarity for Global-scale Bridging in Thermal-hydraulic Simulation [article]

Han Bao, Nam Dinh, Linyu Lin, Robert Youngblood, Jeffrey Lane, Hongbin Zhang
2020 arXiv   pre-print
Case studies based on mixed convection have been designed for demonstrating the capability of data-driven models in bridging global scale gaps.  ...  This paper proposes a data-driven approach, Feature Similarity Measurement FFSM), to establish a technical basis to overcome these difficulties by exploring local patterns using machine learning.  ...  The central idea of this data-driven approach is discussed in Section 2; it is proposed that the similarity of local physics could be identified using deep machine learning to bridge the global scale gap  ... 
arXiv:2001.04298v1 fatcat:6nvdohoyibg2laouoiodgie7wm

The role of categories and spatial cuing in global-scale location estimates

Alinda Friedman
2009 Journal of Experimental Psychology. Learning, Memory and Cognition  
response modalities affect accuracy differently at the different levels, biases at the regional level have multiple sources, and accurate spatial cues improve estimates primarily by limiting the use of global  ...  s (1991) theory and extends it to global-scale, real-world estimates.  ...  Thus, the use of regional categories in global-scale geographic location estimates appears to be ubiquitous.  ... 
doi:10.1037/a0013590 pmid:19210083 fatcat:zzkc5p5fcrbihmohimfcxppstu
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