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Knowledge Graph Semantic Enhancement of Input Data for Improving AI

Shreyansh Bhatt, Amit Sheth, Valerie Shalin, Jinjin Zhao, Amit Sheth
2020 IEEE Internet Computing  
Background knowledge provides complementary, real world factual information that can augment the limited labeled data to train a machine learning algorithm.  ...  Recent academic research and implemented industrial intelligent systems have shown promising performance for machine learning algorithms that combine training data with a knowledge graph.  ...  A convolutional neural network is then applied on such representation that combines word level information with the KG's information.  ... 
doi:10.1109/mic.2020.2979620 fatcat:q4xrsmddnfbvzjhev4xqknfo64

What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation

Jiahua Dong, Yang Cong, Gan Sun, Bineng Zhong, Xiaowei Xu
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
Specifically, T D focuses on where to translate transferable visual information of medical lesions via residual transferability-aware bottleneck, while neglecting untransferable visual characterizations  ...  To address these challenges, we develop a new unsupervised semantic transfer model including two complementary modules (i.e., T D and T F ) for endoscopic lesions segmentation, which can alternatively  ...  Therefore, as shown in Figure 2 , we develop a residual transferabilityaware bottleneck, which determines where to translate transferable information by purifying semantic knowledge with high transfer  ... 
doi:10.1109/cvpr42600.2020.00408 dblp:conf/cvpr/DongCSZX20 fatcat:zzezimlfzndktmi3btkbnga6wy

Deep Unsupervised Embedding for Remotely Sensed Images Based on Spatially Augmented Momentum Contrast

Jian Kang, Ruben Fernandez-Beltran, Puhong Duan, Sicong Liu, Antonio J. Plaza
2020 IEEE Transactions on Geoscience and Remote Sensing  
Based on the first law of geography, the proposed approach defines a spatial augmentation criteria to uncover semantic relationships among land cover tiles.  ...  Convolutional neural networks (CNNs) have achieved great success when characterizing remote sensing (RS) images.  ...  It is important to highlight that this network should be defined with the same architecture with regards to the one of the anchor CNN for a scalable training.  ... 
doi:10.1109/tgrs.2020.3007029 fatcat:nzjqqiscfnco5hks3v4mfclmmm

What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation [article]

Jiahua Dong, Yang Cong, Gan Sun, Bineng Zhong, Xiaowei Xu
2020 arXiv   pre-print
Specifically, T_D focuses on where to translate transferable visual information of medical lesions via residual transferability-aware bottleneck, while neglecting untransferable visual characterizations  ...  To address these challenges, we develop a new unsupervised semantic transfer model including two complementary modules (i.e., T_D and T_F ) for endoscopic lesions segmentation, which can alternatively  ...  Therefore, as shown in Figure 2 , we develop a residual transferabilityaware bottleneck, which determines where to translate transferable information by purifying semantic knowledge with high transfer  ... 
arXiv:2004.11500v1 fatcat:nwrbioc6fvbyfgwaquv5zwr73q

Semantically Enriched Augmented Reality Applications: A Proposed System Architecture and a Case Study

Georgios Lampropoulos, Euclid Keramopoulos, Konstantinos Diamantaras
2022 International Journal of Recent Contributions from Engineering, Science & IT  
With a view to creating a mixed reality that combines coexisting real and virtual objects and to providing users with real-time access to information in an interactive manner, augmented reality enriches  ...  The study main purpose and contribution is to showcase the benefits of developing semantically enriched augmented reality applications and to present a system architecture for developing such applications  ...  With the aim of providing users with a more interactive way to be informed and educated, this study presented a system architecture for developing semantically enriched augmented reality applications as  ... 
doi:10.3991/ijes.v10i01.27463 fatcat:frfpd7yyxndaroheg7uhpvti5u

Visually-Driven Semantic Augmentation for Zero-Shot Learning

Abhinaba Roy, Jacopo Cavazza, Vittorio Murino
2018 British Machine Vision Conference  
Hence, there is no guarantee that visual and semantic information could fit well, and as to bridge this gap, we propose to augment the semantic information of attributes/DWEs with semantic representations  ...  Despite their fundamental role, semantic embeddings are not learnt from the visual data to be classified, but, instead, they either come from manual annotation (attributes) or from a linguistic text corpus  ...  This augmentation is semantic in nature since it exploits the class similarity information obtained from a deep neural network in the form of soft labels [28] , which are finally jointly considered with  ... 
dblp:conf/bmvc/RoyCM18 fatcat:ewp67goupvco7jaunnfyzgwv2q

ATReSN-Net: Capturing Attentive Temporal Relations in Semantic Neighborhood for Acoustic Scene Classification

Liwen Zhang, Jiqing Han, Ziqiang Shi
2020 Interspeech 2020  
obtained from the residual block into a semantic space.  ...  The ATReSN module has two primary components: first, a k-NN-based grouper for gathering a semantic neighborhood for each feature point in the feature maps.  ...  Ablated Network (k = 8) DCASE19 Acc. (%) Network without ATReSN 75.86 Network with relative positions 79.98 Network with augmented positions 80.17 The Full Network (ATReSN-Net) 80.68 Table  ... 
doi:10.21437/interspeech.2020-1151 dblp:conf/interspeech/ZhangHS20 fatcat:tiqxdhlxcjgtjdacsx53dzcnem

Distributed Semantic Video Tagging for Peer-to-Peer Authoring System

Giuseppe Rizzo, Biagio Meirone, Pierluigi Di Nunzio, Federico Di Gregorio
2010 2010 Workshops on Database and Expert Systems Applications  
The Authoring System allows partial annotations (applied to a part and not to the whole document) and time-based tagging of audio and video streams (where the semantic information is applied only to portions  ...  These resources are represented with an envelope composed of many references that point to other contents (whole or portions of) within the Internet.  ...  Additionally, a special thank to our advisor and professor, A.R. Meo, for his continuous suggestions and encouragements.  ... 
doi:10.1109/dexa.2010.51 dblp:conf/dexaw/RizzoMNG10 fatcat:gw3hbfbtebd3jows4gzq75cenu

From Semantic Models to Cognitive Buildings

Joern Ploennigs, Anika Schumann
2017 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
and user comfort, and (iii) speech-enabled Augmented Reality interfaces for immersive interaction with thousands of devices.  ...  We present a Cognitive Building demo that uses (i) semantic reasoning to model physical relationships of sensors and systems, (ii) machine learning to predict and detect anomalies in energy flow, occupancy  ...  We show how the model of a given building can be generated almost automatically based on (i) the building's sensor data, (ii) a generic semantic model characterizing the relationships among sensors and  ... 
doi:10.1609/aaai.v31i1.10539 fatcat:zr6v3ke6xjca5hyujxddp3wt3e

Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion [article]

Shi Qiu, Saeed Anwar, Nick Barnes
2021 arXiv   pre-print
By comparing with state-of-the-art networks on three different benchmarks, we demonstrate the effectiveness of our network.  ...  On the one hand, to reduce the ambiguity in nearby points, we augment their local context by fully utilizing both geometric and semantic features in a bilateral structure.  ...  To avoid the above problems, we propose to characterize the input information as geometric and semantic clues and then fully utilize them through a bilateral structure.  ... 
arXiv:2103.07074v2 fatcat:qqu2qaqrmbcsdimvahmqgc25zq

Semantic Integration and Knowledge Discovery for Environmental Research

Zhiyuan Chen, Aryya Gangopadhyay, George Karabatis, Michael McGuire, Claire Welty
2007 Journal of Database Management  
User requests are augmented with semantically related data sources and automatically presented as a visual semantic network.  ...  We describe a new metadata approach to elicit semantic information from environmental data and implement semanticsbased techniques to assist users in integrating, navigating, and mining multiple environmental  ...  augmentation of the semantic network.  ... 
doi:10.4018/jdm.2007010103 fatcat:qlyhhfxamzce3ize6pt2tvrifq

Learning Topometric Semantic Maps from Occupancy Grids [article]

Markus Hiller, Chen Qiu, Florian Particke, Christian Hofmann and Jörn Thielecke
2020 arXiv   pre-print
In this paper, we propose a new approach for deriving such instance-based semantic maps purely from occupancy grids.  ...  We further provide insight into which features are learned to detect doorways, and how the simulated training data can be augmented to train networks for the direct application on real-world grid maps.  ...  The authors are with the Institute of Information Technology, Department of Electrical, Electronic and Communication Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany; Correspondence  ... 
arXiv:2001.03676v1 fatcat:gpms6d4csbdi3a3tpsb3rbbe2i

A Multi-level Supervised Contrastive Learning Framework for Low-Resource Natural Language Inference [article]

Shu'ang Li, Xuming Hu, Li Lin, Aiwei Liu, Lijie Wen, Philip S. Yu
2022 arXiv   pre-print
Existing works fail to characterize discriminative representations between different classes with limited training data, which may cause faults in label prediction.  ...  MultiSCL adopts a data augmentation module that generates different views for input samples to better learn the latent representation.  ...  13] is a multi-task deep neural network for learning semantic representations across multiple natural language understanding tasks.  ... 
arXiv:2205.15550v1 fatcat:u7euduldxnfb5mdht7tdkbcncq

Offensive-Language Detection on Multi-Semantic Fusion Based on Data Augmentation

Junjie Liu, Yong Yang, Xiaochao Fan, Ge Ren, Liang Yang, Qian Ning
2022 Applied System Innovation  
To overcome these problems, we proposed a multi-semantic fusion model based on data augmentation (MSF).  ...  At the same time, we used a novel fusion mechanism that combines word-level semantic features and n-grams character features.  ...  Informed Consent Statement: Not applicable. Data Availability Statement: Data is contained within the article. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/asi5010009 fatcat:ighirdydl5cxldhm7bwap7vcqu

Divide and conquer: the formation and functional dynamics of the Modern English ing-clause network

LAUREN FONTEYN, NIKKI VAN DE POL
2015 English Language and Linguistics  
By treating present-participial adverbial clauses and adverbial gerunds as part of a single adverbialing-clause network, this article sheds new light on the different semantic and functional-pragmatic  ...  user's choice in (i) whether or not to include augmentation (syndesis) and (ii) whether or not to include an overt subject in the adverbialing-clause.  ...  Augmentation patterns in the ing-clause network Now that we have established the formal make-up of the adverbial ing-clause network, the question remains how the constructions in the network can be characterized  ... 
doi:10.1017/s1360674315000258 fatcat:2aa5d5ajprc4reeoulyznh374a
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