PDF Ebook about: Semantic Networks

Semantic Networks

List of ebooks and manuals about Semantic Networks

38 documents available in our comprehensive collection of Semantic Networks resources. Find practical guides, tutorials, and documentation to enhance your knowledge.

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[OpenAccess] (82180337-semantic-rule-filtering-for-web-scale-relation-extraction.pdf)

238 KBEN 16 pages
Researchers propose a method to improve precision in web-scale relation extraction by utilizing a lexical semantic network, BabelNet, for semantic rule
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Semantic Subnet Extraction (C12-1045.pdf)

918 KBSuman Deb Roy ; Wenjun ZengEN 18 pages
A computational cognitive model extracts semantic sub-networks from natural language queries by leveraging semantic forms from cognitive psychology,
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(Song_Box-Driven_Class-Wise_Region_Masking_and_Filling_Rate_Guided_Loss_for_CVPR_2019_paper.pdf)

1.36 MBChunfeng Song, Yan Huang, Wanli Ouyang, Liang WangEN 10 pages
Semantic segmentation has made significant progress with deep Fully Convolutional Networks (FCN), but its performance relies heavily on expensive and
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(1708.04943.pdf)

1.92 MBEN 12 pages
Researchers propose a Stacked Deconvolutional Network (SDN) for semantic image segmentation, addressing the issue of spatial resolution loss in Fully
Preview of Polarization-Driven Segmentation
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Polarization-Driven Segmentation (2011.13313.pdf)

3.6 MBEN 18 pages
Polarization-driven semantic segmentation is proposed via an Efficient Attention-bridged Fusion Network (EAFNet) to leverage complementary information from
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(1805.04554v1.pdf)

12.98 MBEN 11 pages
ContextNet is a deep neural network architecture for real-time semantic segmentation, combining a deep branch at low resolution for global context information
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(1907.10958.pdf)

7.12 MBEN 5 pages
The proposed Cross Attention Network (CANet) for semantic segmentation combines contextual features and spatial information through two branches and a Feature
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Logic Tensor Networks (1606.04422.pdf)

150 KBEN 12 pages
Logic Tensor Networks integrate deep learning and logical reasoning, using a first-order language with truth-values in [0,1] and semantics defined on real
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Fracking Sarcasm (W16-0425.pdf)

304 KBAniruddha Ghosh ; Dr. Tony VealeEN 9 pages
Researchers propose a neural network semantic model for sarcasm detection, outperforming state-of-the-art text-based methods with an F-score of 0
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Moving vehicle tracking and scene understanding: A hybrid approach. (Xiaoxu_Liu-manuscript.pdf)

1.31 MBEN 22 pages
A novel deep learning method for detecting and tracking vehicles in autonomous driving scenarios is presented, focusing on vehicle failures.
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Co-Attention in Visual Question Answering (On_the_Efficacy_of_Co-Attention_Transformer_Layers.pdf)

35.54 MBEN 15 pages
We investigate the efficacy of co-attention transformer layers in Visual Question Answering, generating visual attention maps using question-conditioned image attention scores. We evaluate the effect of critical components on visual attention of a state-of-the-art VQA model.
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http://www.lix.polytechnique.fr/Labo/Samuel.Mimram/docs/mimram_nsk.pdf (mimram_nsk.pdf)

541 KBEN 15 pages
Kahn process networks are modeled using a new syntax called "nets", which are graphs with boxes and wires, and are shown to form a fixpoint category,
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Invertible Interpretation Network (paper.pdf)

13.07 MBEN 19 pages
Neural networks learn powerful representations, but their hidden layers lack interpretability due to distributed coding, making it hard to attribute meaning to
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Stimulus-Sensor-Observation (paper12.pdf)

844 KBEN 15 pages
Researchers Krzysztof Janowicz and Michael Compton present a generic ontology design pattern for observation-based data on the Semantic Web, integrating it
Preview of NUIG-UNLP at SemEval-2016 Task 1: Soft Alignment and Deep Learning for Semantic Textual Similarity
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NUIG-UNLP at SemEval-2016 Task 1: Soft Alignment and Deep Learning for Semantic Textual Similarity (S16-1110.pdf)

475 KBJohn Philip McCrae ; Kartik Asooja ; Nitish Aggarwal ; Paul BuitelaarEN 6 pages
The paper introduces a multi-feature system for semantic text similarity, utilizing soft alignment and Explicit Semantic Analysis techniques, achieving top performance in 4 out of 5 datasets at SemEval-2016 Task 1
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Download (4MB) (Devereaux_etal_NT_2020_Automated_object_detection_for_visual_inspection_of_nuclear_reactor.pdf)

4.46 MBEN 28 pages
Automated object detection is applied to visual inspection of nuclear reactor cores, specifically Advanced Gas-Cooled Reactors (AGR), to identify reference...
Preview of Sentinel-2 Imagery for Fine-Grained Road Map Extraction Using Deep Learning Techniques
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Sentinel-2 Imagery for Fine-Grained Road Map Extraction Using Deep Learning Techniques (isprs-annals-V-3-2021-9-2021.pdf)

3.15 MBEN 6 pages
This study explores extracting detailed road maps using Sentinel-2 satellite imagery with deep learning techniques, specifically convolutional neural networks (CNNs)
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http://ceur-ws.org/Vol-2266/T1-3.pdf (T1-3.pdf)

299 KBEN 3 pages
DAIICT-Hildesheim participated in the IRMiDis 2018 track with three runs to distinguish between fact-checkable and non-fact-checkable tweets.
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CNS Journal (vol8iss1.pdf)

12.76 MBEN 101 pages
Nijmegen CNS journal, volume 8, issue 1, features editorials and research articles on cognitive neuroscience, including GABA, excitability, and plasticity in...
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Download (3MB) (Kamakura_11_PhD.pdf)

3.4 MByoshi kamakuraEN 337 pages
This study explores the relationship between prepositions 'over', 'into', and 'through' and their preceding and following nouns, using concepts from corpus...
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Semi-Supervised Fire Segmentation (Lisa_Kuhlmann_Semi_Supervised_Smoke_Fire_Segmentation.pdf)

28.13 MBEN 87 pages
The semantic segmentation of smoke and fire can be a basis for the application of useful tools to support firefighting actions, but the amount of annotated
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electronic edition @ stanford.edu (open access) (intro-innovative.pdf)

553 KBTiffany MurrayEN 3 pages
The increasing use of Whole Genome Sequencing (WGS) and Whole Exome Sequencing (WES) in clinical settings has made it difficult to determine the causal variant...
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DeepLabv3+ (1802.02611.pdf)

4 MBEN 18 pages
The authors propose DeepLabv3+, an encoder-decoder model for semantic image segmentation, which extends DeepLabv3 by adding a simple yet effective decoder
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(1911.11981.pdf)

2.55 MBEN 10 pages
Class-Conditional Domain Adaptation (CCDA) is proposed for semantic segmentation to address the issue of domain shift and overfitting
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Automatic Shortcut Removal for Self-Supervised Representation Learning (2002.08822.pdf)

6.99 MBMatthias Minderer, Olivier Bachem, Neil Houlsby, Michael TschannenEN 20 pages
Researchers propose a framework to mitigate the effect of "shortcut" features in self-supervised visual representation learning, where a neural network...
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http://www.meanotek.io/files/natgen.pdf (natgen.pdf)

793 KBTarasov D. S.EN 8 pages
The model is trained on a large dataset of consumer reviews in Russian and can generate novel sentences and document summaries.
Preview of Instance Segmentation via Instance Categories: A Simple and Flexible Framework
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Instance Segmentation via Instance Categories: A Simple and Flexible Framework (1912.04488v1.pdf)

8.85 MBEN 10 pages
A novel, simple approach to instance segmentation that categorizes pixels based on instance location and size, eliminating the need for complex "detect-then-segment" or clustering methods. This method significantly simplifies the task by introducing "instance categories.
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Distributed Condition Monitoring (SS01-06-002.pdf)

604 KBPaul Benninghoff and Sanguk NohEN 7 pages
Distributed Condition Monitoring (DCM) is expensive and difficult to scale due to frequent information updates, leading to significant network traffic and...
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PDF (Ying_Weakly-Supervised_Object_Representation_Learning_for_Few-Shot_Semantic_Segmentation_WACV_2021_paper.pdf)

2.76 MBXiaowen Ying, Xin Li, Mooi Choo ChuahEN 10 pages
Training semantic segmentation models requires large, densely-annotated image datasets, which are costly to obtain
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https://cert-portal.siemens.com/productcert/pdf/ssa-833048.pdf (ssa-833048.pdf)

36 KBSiemens ProductCERTEN 2 pages
Siemens discovered a vulnerability in SIMATIC S7-1200 CPU Family products prior to version 4, allowing circumvention of user program block protection under...
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Il Calendario degli esami di marzo 2021 (1421_Appelli-esame-di-mar_2021.pdf)

45 KBIT 1 page
marzo 2021, sessione straordinaria riservata agli studenti fuori corso, con date, orari, presidenti e note per vari corsi, tra cui Advanced english, Big data...
Preview of Managing Stress: Principles and Strategies for Health and Wellbeing
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Managing Stress: Principles and Strategies for Health and Wellbeing (Ch 2_Seaward_Managing Stress_5e.pdf)

5.37 MBDebra HealyEN 15 pages
The stress response is a complex physiological process that involves the nervous, endocrine, and immune systems.
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Download full text (pdf) of Immunoglobulin gene sequence analysis in chronic lymphocytic leukemia: updated ERIC recommendations (FULLTEXT01.pdf)

143 KBR RosenquistEN 5 pages
Immunoglobulin gene sequence analysis in chronic lymphocytic leukemia (CLL) has been pivotal in understanding the disease's natural history, with studies from...
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BCA 6th Sem Assignment (BCA-6TH-SEM-ASSIGNMENT.pdf)

293 KBIAITEN 9 pages
Part A with 5 short answer questions (4 marks each) and Part B with 4 long answer questions (5 marks each). All questions are compulsory. Students must submit their assignments in written form to their respective faculty/examiners by June 18.
Preview of https://symantec.broadcom.com/hubfs/Attacks-Against-Critical_Infrastructrure.pdf
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https://symantec.broadcom.com/hubfs/Attacks-Against-Critical_Infrastructrure.pdf (Attacks-Against-Critical_Infrastructrure.pdf)

782 KBThreat Hunter TeamEN 19 pages
Cyber attacks on Critical National Infrastructure (CNI) are a major concern due to their potential to cause immense disruption.
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Disinfo Threat Report (J153-160- White paper.pdf)

977 KBEN 8 pages
The Department of Homeland Security's 2020 report identifies foreign influence activity as a significant threat to national security.
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Loss as Model Inconsistency (richardson22b.pdf)

717 KBEN 30 pages
Richardson argues that loss function choice in probabilistic dependency graphs (PDGs) should align with the model, not personal preference. He shows that many standard loss functions and statistical divergences can be derived from PDG inconsistency, offering intuitive visual...
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Wikipedia Taxonomy Mapping (IJCAI09-343.pdf)

489 KBSimone Paolo Ponzetto, Roberto NavigliEN 6 pages
Ponzetto and Navigli propose a method to disambiguate Wikipedia categories using WordNet synsets, restructuring the resulting taxonomy. They demonstrate high accuracy in evaluation and enrich WordNet with Wikipedia instances.

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