Thematische Bibliographien / Context Encoder

Inhaltsverzeichnis

  1. Zeitschriftenartikel
  2. Dissertationen
  3. Bücher
  4. Buchteile
  5. Konferenzberichte
  6. Berichte der Organisationen

Auswahl der wissenschaftlichen Literatur zum Thema „Context Encoder“

Autor: Grafiati
Veröffentlicht am 28. Juni 2021
Zuletzt aktualisiert am 18. Februar 2022

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Zeitschriftenartikel zum Thema "Context Encoder"

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Pinho, M. S., and W. A. Finamore. "Context-based LZW encoder." Electronics Letters 38, no. 20 (2002): 1172. http://dx.doi.org/10.1049/el:20020807.

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Han, Jialong, Aixin Sun, Haisong Zhang, Chenliang Li, and Shuming Shi. "CASE: Context-Aware Semantic Expansion." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (2020): 7871–78. http://dx.doi.org/10.1609/aaai.v34i05.6293.

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In this paper, we define and study a new task called Context-Aware Semantic Expansion (CASE). Given a seed term in a sentential context, we aim to suggest other terms that well fit the context as the seed. CASE has many interesting applications such as query suggestion, computer-assisted writing, and word sense disambiguation, to name a few. Previous explorations, if any, only involve some similar tasks, and all require human annotations for evaluation. In this study, we demonstrate that annotations for this task can be harvested at scale from existing corpora, in a fully automatic manner. On
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Marafioti, Andres, Nathanael Perraudin, Nicki Holighaus, and Piotr Majdak. "A Context Encoder For Audio Inpainting." IEEE/ACM Transactions on Audio, Speech, and Language Processing 27, no. 12 (2019): 2362–72. http://dx.doi.org/10.1109/taslp.2019.2947232.

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Yun, Hyeongu, Yongkeun Hwang, and Kyomin Jung. "Improving Context-Aware Neural Machine Translation Using Self-Attentive Sentence Embedding." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (2020): 9498–506. http://dx.doi.org/10.1609/aaai.v34i05.6494.

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Fully Attentional Networks (FAN) like Transformer (Vaswani et al. 2017) has shown superior results in Neural Machine Translation (NMT) tasks and has become a solid baseline for translation tasks. More recent studies also have reported experimental results that additional contextual sentences improve translation qualities of NMT models (Voita et al. 2018; Müller et al. 2018; Zhang et al. 2018). However, those studies have exploited multiple context sentences as a single long concatenated sentence, that may cause the models to suffer from inefficient computational complexities and long-range dep
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Dakwale, Praveen, and Christof Monz. "Convolutional over Recurrent Encoder for Neural Machine Translation." Prague Bulletin of Mathematical Linguistics 108, no. 1 (2017): 37–48. http://dx.doi.org/10.1515/pralin-2017-0007.

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AbstractNeural machine translation is a recently proposed approach which has shown competitive results to traditional MT approaches. Standard neural MT is an end-to-end neural network where the source sentence is encoded by a recurrent neural network (RNN) called encoder and the target words are predicted using another RNN known as decoder. Recently, various models have been proposed which replace the RNN encoder with a convolutional neural network (CNN). In this paper, we propose to augment the standard RNN encoder in NMT with additional convolutional layers in order to capture wider context
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Dligach, Dmitriy, Majid Afshar, and Timothy Miller. "Toward a clinical text encoder: pretraining for clinical natural language processing with applications to substance misuse." Journal of the American Medical Informatics Association 26, no. 11 (2019): 1272–78. http://dx.doi.org/10.1093/jamia/ocz072.

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Abstract Objective Our objective is to develop algorithms for encoding clinical text into representations that can be used for a variety of phenotyping tasks. Materials and Methods Obtaining large datasets to take advantage of highly expressive deep learning methods is difficult in clinical natural language processing (NLP). We address this difficulty by pretraining a clinical text encoder on billing code data, which is typically available in abundance. We explore several neural encoder architectures and deploy the text representations obtained from these encoders in the context of clinical te
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Trisedya, Bayu, Jianzhong Qi, and Rui Zhang. "Sentence Generation for Entity Description with Content-Plan Attention." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (2020): 9057–64. http://dx.doi.org/10.1609/aaai.v34i05.6439.

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We study neural data-to-text generation. Specifically, we consider a target entity that is associated with a set of attributes. We aim to generate a sentence to describe the target entity. Previous studies use encoder-decoder frameworks where the encoder treats the input as a linear sequence and uses LSTM to encode the sequence. However, linearizing a set of attributes may not yield the proper order of the attributes, and hence leads the encoder to produce an improper context to generate a description. To handle disordered input, recent studies propose two-stage neural models that use pointer
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Cai, Yuanyuan, Min Zuo, Qingchuan Zhang, Haitao Xiong, and Ke Li. "A Bichannel Transformer with Context Encoding for Document-Driven Conversation Generation in Social Media." Complexity 2020 (September 17, 2020): 1–13. http://dx.doi.org/10.1155/2020/3710104.

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Along with the development of social media on the internet, dialogue systems are becoming more and more intelligent to meet users’ needs for communication, emotion, and social intercourse. Previous studies usually use sequence-to-sequence learning with recurrent neural networks for response generation. However, recurrent-based learning models heavily suffer from the problem of long-distance dependencies in sequences. Moreover, some models neglect crucial information in the dialogue contexts, which leads to uninformative and inflexible responses. To address these issues, we present a bichannel
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Zhang, Biao, Deyi Xiong, Jinsong Su, and Hong Duan. "A Context-Aware Recurrent Encoder for Neural Machine Translation." IEEE/ACM Transactions on Audio, Speech, and Language Processing 25, no. 12 (2017): 2424–32. http://dx.doi.org/10.1109/taslp.2017.2751420.

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Pan, Yirong, Xiao Li, Yating Yang, and Rui Dong. "Multi-Source Neural Model for Machine Translation of Agglutinative Language." Future Internet 12, no. 6 (2020): 96. http://dx.doi.org/10.3390/fi12060096.

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Benefitting from the rapid development of artificial intelligence (AI) and deep learning, the machine translation task based on neural networks has achieved impressive performance in many high-resource language pairs. However, the neural machine translation (NMT) models still struggle in the translation task on agglutinative languages with complex morphology and limited resources. Inspired by the finding that utilizing the source-side linguistic knowledge can further improve the NMT performance, we propose a multi-source neural model that employs two separate encoders to encode the source word
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Dissertationen zum Thema "Context Encoder"

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Damecharla, Hima Bindu. "FPGA IMPLEMENTATION OF A PARALLEL EBCOT TIER-1 ENCODER THAT PRESERVES ENCODING EFFICIENCY." University of Akron / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=akron1149703842.

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Leufvén, Johan. "Integration of user generated content with an IPTV middleware." Thesis, Linköping University, Linköping University, Department of Computer and Information Science, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-55029.

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<p>IPTV is a growing form of distribution for TV and media. Reports show that the market will grow from the current 20-30 million subscribers to almost 100 million 2012. IPTV extends the traditional TV viewing with new services like renting movies from your TV. It could also be seen as a bridge between the traditional broadcast approach and the new on demand approach the users are used to from internet.</p><p>Since there are many actors in the IPTV market that all deliver the same basic functionality, companies must deliver better products that separate them from the competitors. This can be d
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May, Richard John. "Perceptual content loss in bit rate constrained IFS encoded speech." Thesis, University of Portsmouth, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.396323.

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Hsu, William. "Using knowledge encoded in graphical disease models to support context-sensitive visualization of medical data." Diss., Restricted to subscribing institutions, 2009. http://proquest.umi.com/pqdweb?did=1925776141&sid=13&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Anegekuh, Louis. "Video content-based QoE prediction for HEVC encoded videos delivered over IP networks." Thesis, University of Plymouth, 2015. http://hdl.handle.net/10026.1/3377.

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The recently released High Efficiency Video Coding (HEVC) standard, which halves the transmission bandwidth requirement of encoded video for almost the same quality when compared to H.264/AVC, and the availability of increased network bandwidth (e.g. from 2 Mbps for 3G networks to almost 100 Mbps for 4G/LTE) have led to the proliferation of video streaming services. Based on these major innovations, the prevalence and diversity of video application are set to increase over the coming years. However, the popularity and success of current and future video applications will depend on the perceive
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Sasko, Dominik. "Segmentace lézí roztroušené sklerózy pomocí hlubokých neuronových sítí." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442379.

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Hlavným zámerom tejto diplomovej práce bola automatická segmentácia lézií sklerózy multiplex na snímkoch MRI. V rámci práce boli otestované najnovšie metódy segmentácie s využitím hlbokých neurónových sietí a porovnané prístupy inicializácie váh sietí pomocou preneseného učenia (transfer learning) a samoriadeného učenia (self-supervised learning). Samotný problém automatickej segmentácie lézií sklerózy multiplex je veľmi náročný, a to primárne kvôli vysokej nevyváženosti datasetu (skeny mozgov zvyčajne obsahujú len malé množstvo poškodeného tkaniva). Ďalšou výzvou je manuálna anotácia týchto l
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和基, 塩谷, and Kazuki Shiotani. "Olfactory cortex ventral tenia tecta neurons encode the distinct context-dependent behavioral states of goal-directed behaviors." Thesis, 櫻井 芳雄, 2003. http://id.nii.ac.jp/1707/00028191/.

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和基, 塩谷, and Kazuki Shiotani. "Olfactory cortex ventral tenia tecta neurons encode the distinct context-dependent behavioral states of goal-directed behaviors." Thesis, 櫻井 芳雄, 2021. https://doors.doshisha.ac.jp/opac/opac_link/bibid/BB13158521/?lang=0.

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Munoz, Joshua. "Application of Multifunctional Doppler LIDAR for Non-contact Track Speed, Distance, and Curvature Assessment." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/77876.

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The primary focus of this research is evaluation of feasibility, applicability, and accuracy of Doppler Light Detection And Ranging (LIDAR) sensors as non-contact means for measuring track speed, distance traveled, and curvature. Speed histories, currently measured with a rotary, wheel-mounted encoder, serve a number of useful purposes, one significant use involving derailment investigations. Distance calculation provides a spatial reference system for operators to locate track sections of interest. Railroad curves, using an IMU to measure curvature, are monitored to maintain track infrastr
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Sultana, Tania. "L'influence du contexte génomique sur la sélection du site d'intégration par les rétrotransposons humains L1." Thesis, Université Côte d'Azur (ComUE), 2016. http://www.theses.fr/2016AZUR4133.

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Les rétrotransposons L1 (Long INterspersed Element-1) sont des éléments génétiques mobiles dont l'activité contribue à la dynamique du génome humain par mutagenèse insertionnelle. Les conséquences génétiques et épigénétiques d'une nouvelle insertion, et la capacité d'un L1 à être remobilisé, sont directement liées au site d’intégration dans le génome. Aussi, l’analyse des sites d’intégration des L1s est capitale pour comprendre leur impact fonctionnel - voire pathogène -, en particulier lors de la tumorigenèse ou au cours du vieillissement, et l’évolution de notre génome. Dans ce but, nous avo
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Bücher zum Thema "Context Encoder"

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May, Richard John. Perceptual content loss in bit rate constrained IFS encoded speech. University of Portsmouth, 2002.

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Bill, Stockting, and Queyroux Fabienne, eds. Encoding across frontiers: Proceedings of the European Conference on Encoded Archival Description and Context (EAD and EAC), Paris, France, 1-8 October, 2004. Haworth Information Press, 2005.

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L' Afrique noire, peut-elle encore parler français?: Essai sur la méthodologie de l'enseignement du français langue étrangère en Afrique noire francophone à travers l'étude du cas sénégalais. L'Harmattan, 1986.

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M, Dooley Jackie, ed. Encoded Archival Description: Context, theory, and case studies. Society of American Archivists, 1998.

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Dooley, Jackie M. Encoded Archival Description: Context, Theory, and Case Studies. Society of American Archivists, 1998.

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Mayle, Peter. Encore Provence Consumer Contest Display Kit. Alfred A. Knopf, 1999.

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Lepore, Ernie, and Matthew Stone. Explicit Indirection. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198738831.003.0007.

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Our goal in this chapter is to contest the traditional view of indirection in utterances such as, ‘Can you pass the salt?’ by developing a very different way of characterizing the interpretations involved. We argue that the felt “indirection” of such utterances reflects the kind of meaning the utterances have, rather than the way that meaning is derived. So understood, there is no presumption that indirect meanings involve the pragmatic derivation of enriched contents froma literal interpretation; rather, we argue that indirect meanings are explicitly encoded in grammar. We build on recent wor
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Duffley, Patrick. Linguistic Meaning Meets Linguistic Form. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198850700.001.0001.

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This book steers a middle course between two opposing conceptions that currently dominate the field of semantics, the logical and cognitive approaches. It brings to light the inadequacies of both frameworks, and argues along with the Columbia School that linguistic semantics must be grounded on the linguistic sign itself and the meaning it conveys across the full range of its uses. The book offers 12 case studies demonstrating the explanatory power of a sign-based semantics, dealing with topics such as complementation with aspectual and causative verbs, control and raising, wh- words, full-ver
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Balentine, Samuel E., ed. The Oxford Handbook of Ritual and Worship in the Hebrew Bible. Oxford University Press, 2020. http://dx.doi.org/10.1093/oxfordhb/9780190222116.001.0001.

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The focus of this Handbook is on ritual and worship from the perspective of biblical studies, particularly on the Hebrew Bible and its ancient Near Eastern antecedents. Within this context, attention will be given to the development of ideas in Jewish, Christian, and Muslim thinking, but only insofar as they connect with or extend the trajectory of biblical precedents. The volume reflects a wide range of analytical approaches to ancient texts, inscriptions, iconography, and ritual artifacts. It examines the social history and cultural knowledge encoded in rituals, and explores the way rituals
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Carston, Robyn. Pragmatics and Semantics. Edited by Yan Huang. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199697960.013.19.

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A cognitive-scientific approach to the pragmatic interpretive ability is presented, according to which it is seen as a specific cognitive system dedicated to the interpretation of ostensive stimuli, that is, verbal utterances and other overtly communicative acts. This approach calls for a dual construal of semantics. The semantics which interfaces with the pragmatic interpretive system is not a matter of truth-conditional content, but of whatever components of meaning (lexical and syntactic) are encoded by the language system (independent of any particular use of the system by speakers in spec
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Buchteile zum Thema "Context Encoder"

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Keya, Mumenunnessa, Abu Kaisar Mohammad Masum, Sheikh Abujar, Sharmin Akter, and Syed Akhter Hossain. "Bengali Context–Question Similarity Using Universal Sentence Encoder." In Advances in Intelligent Systems and Computing. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4367-2_30.

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Tian, Xiaohua, Thinh M. Le, and Yong Lian. "Efficient Architecture for Context Modeling in the CABAC Encoder." In Entropy Coders of the H.264/AVC Standard. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14703-6_5.

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Qiu, Hao, Zaiwang Gu, Lei Mou, et al. "The Channel Attention Based Context Encoder Network for Inner Limiting Membrane Detection." In Ophthalmic Medical Image Analysis. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32956-3_13.

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Stagakis, Nikolaos, Evangelia I. Zacharaki, and Konstantinos Moustakas. "Hierarchical Image Inpainting by a Deep Context Encoder Exploiting Structural Similarity and Saliency Criteria." In Lecture Notes in Computer Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34995-0_42.

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Zhu, Kanghua, Yongfang Wang, Jian Wu, Yun Zhu, and Wei Zhang. "Content Oriented Video Quality Prediction for HEVC Encoded Stream." In Communications in Computer and Information Science. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4211-9_33.

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El-Haddad, Christiane, and Yiannis Laouris. "The Ability of Children with Mild Learning Disabilities to Encode Emotions through Facial Expressions." In Toward Autonomous, Adaptive, and Context-Aware Multimodal Interfaces. Theoretical and Practical Issues. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18184-9_34.

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Saito, Kuniaki, Kate Saenko, and Ming-Yu Liu. "COCO-FUNIT: Few-Shot Unsupervised Image Translation with a Content Conditioned Style Encoder." In Computer Vision – ECCV 2020. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58580-8_23.

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Modegi, Toshio. "Development of MIDI Encoder “Auto-F” for Creating MIDI Controllable General Audio Contents." In Entertainment Computing. Springer US, 2003. http://dx.doi.org/10.1007/978-0-387-35660-0_28.

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Jallais, Maëliss, and Demian Wassermann. "Single Encoding Diffusion MRI: A Probe to Brain Anisotropy." In Mathematics and Visualization. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-56215-1_8.

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AbstractThis chapter covers anisotropy in the context of probing microstructure of the human brain using single encoded diffusion MRI. We will start by illustrating how diffusion MRI is a perfectly adapted technique to measure anisotropy in the human brain using water motion, followed by a biological presentation of human brain. The non-invasive imaging technique based on water motions known as diffusion MRI will be further presented, along with the difficulties that come with it. Within this context, we will first review and discuss methods based on signal representation that enable us to get an insight into microstructure anisotropy. We will then outline methods based on modeling, which are state-of-the-art methods to get parameter estimations of the human brain tissue.
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Bryant, Peter T. "Evaluation of Performance." In Augmented Humanity. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76445-6_7.

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AbstractAgents evaluate their performances to assess progress, learn, and improve. In doing so, they refer to criteria of various kinds. Some criteria are deeply encoded in mental models, organizational procedures, or cultural norms and logics, while other evaluative criteria are adaptive and may upregulate or downregulate, depending on the agent’s goals, expectations, and context. Here, too, digitalization is transformative. Artificial agents bring unprecedented power to the evaluation of performance, including the rapid intra-cyclical evaluation of ongoing processes. These mechanisms support feedforward guidance in real time. Therefore, when human and artificial agents combine in the evaluation of augmented performance, they face additional risks. Artificial evaluative processing could be fast and precise, while at the same time, human evaluation may be relatively sluggish and imprecise. Overall evaluations of performance could be distorted and dysfunctional.
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Konferenzberichte zum Thema "Context Encoder"

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Qu, Zhenshen, Shimeng Yu, and Mengyu Fu. "Motion background modeling based on context-encoder." In 2016 Third International Conference on Artificial Intelligence and Pattern Recognition (AIPR). IEEE, 2016. http://dx.doi.org/10.1109/icaipr.2016.7585207.

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Liao, Liang, Ruimin Hu, Jing Xiao, and Zhongyuan Wang. "Edge-Aware Context Encoder for Image Inpainting." In ICASSP 2018 - 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018. http://dx.doi.org/10.1109/icassp.2018.8462549.

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Altay, Fatih, and Senem Velipasalar. "Image Completion with Discriminator Guided Context Encoder." In 2018 52nd Asilomar Conference on Signals, Systems, and Computers. IEEE, 2018. http://dx.doi.org/10.1109/acssc.2018.8645434.

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Xu, Hongfei, Deyi Xiong, Josef van Genabith, and Qiuhui Liu. "Efficient Context-Aware Neural Machine Translation with Layer-Wise Weighting and Input-Aware Gating." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/544.

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Existing Neural Machine Translation (NMT) systems are generally trained on a large amount of sentence-level parallel data, and during prediction sentences are independently translated, ignoring cross-sentence contextual information. This leads to inconsistency between translated sentences. In order to address this issue, context-aware models have been proposed. However, document-level parallel data constitutes only a small part of the parallel data available, and many approaches build context-aware models based on a pre-trained frozen sentence-level translation model in a two-step training man
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Yamane, Satoshi, and Tetsuto Takano. "Machine Translation Considering Context Informaiton Using Encoder-Decoder Model." In 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC). IEEE, 2018. http://dx.doi.org/10.1109/compsac.2018.00123.

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Moris, Daniel I., Alvaro S. Hervella, Jose Rouco, Jorge Novo, and Marcos Ortega. "Context encoder self-supervised approaches for eye fundus analysis." In 2021 International Joint Conference on Neural Networks (IJCNN). IEEE, 2021. http://dx.doi.org/10.1109/ijcnn52387.2021.9533567.

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Yu, Zhen, Youyi Song, and Jing Qin. "Dense Pyramid Context Encoder-Decoder Network for Kidney Lesion Segmentation." In 2019 Kidney Tumor Segmentation Challenge: KiTS19. University of Minnesota Libraries Publishing, 2019. http://dx.doi.org/10.24926/548719.046.

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Tian, X. H., T. M. Le, H. C. Teo, B. L. Ho, and Y. Lian. "CABAC HW Encoder with RDO Context Management and MBIST Capability." In 2007 International Symposium on Integrated Circuits - ISIC 2007. IEEE, 2007. http://dx.doi.org/10.1109/isicir.2007.4441841.

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Zeng, Yanhong, Jianlong Fu, Hongyang Chao, and Baining Guo. "Learning Pyramid-Context Encoder Network for High-Quality Image Inpainting." In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2019. http://dx.doi.org/10.1109/cvpr.2019.00158.

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Ma, Zhiqiang, Chunyu Wang, Ji Shen, and Baoxiang Du. "A Context-Aware Variational Auto-Encoder Model for Text Generation." In 2020 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom). IEEE, 2020. http://dx.doi.org/10.1109/ispa-bdcloud-socialcom-sustaincom51426.2020.00175.

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Berichte der Organisationen zum Thema "Context Encoder"

1

Faltstrom, P., D. Crocker, and E. Fair. MIME Content Type for BinHex Encoded Files. RFC Editor, 1994. http://dx.doi.org/10.17487/rfc1741.

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