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Compiler-Driven Simulation of Reconfigurable Hardware Accelerators ...
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Innovative Vineyards Environmental Monitoring System Using Deep Edge AI
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In: Artificial Intelligence for Digitising Industry Applications ; https://hal.univ-reims.fr/hal-03355270 ; Artificial Intelligence for Digitising Industry Applications, River Publishers, pp.261-278, 2021, 9788770226646 ; https://www.riverpublishers.com/research_details.php?book_id=967 (2021)
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Elastic Silicon Interconnects: Abstracting Communication in Accelerator Design ...
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HIR: An MLIR-based Intermediate Representation for Hardware Accelerator Description ...
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Hand-gesture recognition based on EMG and event-based camera sensor fusion: a benchmark in neuromorphic computing
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In: ISSN: 1662-4548 ; EISSN: 1662-453X ; Frontiers in Neuroscience ; https://hal.archives-ouvertes.fr/hal-02617084 ; Frontiers in Neuroscience, Frontiers, 2020, pp.36 ; https://www.frontiersin.org/ (2020)
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Written and spoken digits database for multimodal learning
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In: https://hal.archives-ouvertes.fr/hal-02327938 ; 2019 (2019)
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Abstract:
The written and spoken digits database is not a new database but a constructed database from existing ones, in order to provide a ready-to-use database for multimodal fusion.The written digits database is the original MNIST handwritten digits database [1] with no additional processing. It consists of 70000 images (60000 for training and 10000 for test) of 28 x 28 = 784 dimensions.The spoken digits database was extracted from Google Speech Commands [2], an audio dataset of spoken words that was proposed to train and evaluate keyword spotting systems. It consists of 105829 utterances of 35 words, amongst which 38908 utterances of the ten digits (34801 for training and 4107 for test). A pre-processing was done via the extraction of the Mel Frequency Cepstral Coefficients (MFCC) with a framing window size of 50 ms and frame shift size of 25 ms. Since the speech samples are approximately 1 s long, we end up with 39 time slots. For each one, we extract 12 MFCC coefficients with an additional energy coefficient. Thus, we have a final vector of 39 x 13 = 507 dimensions. Standardization and normalization were applied on the MFCC features.To construct the multimodal digits dataset, we associated written and spoken digits of the same class respecting the initial partitioning in [1] and [2] for the training and test subsets. Since we have less samples for the spoken digits, we duplicate some random samples to match the number of written digits and have a multimodal digits database of 70000 samples (60000 for training and 10000 for test).The dataset is provided in six files as described below. Therefore, if a shuffle is performed on the training or test subsets, it must be performed in unison with the same order for the written digits, spoken digits and labels.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR]
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URL: https://hal.archives-ouvertes.fr/hal-02327938
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Adaptation and Implementation of the ISO42010 Standard to Software Design and Modeling Tools
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In: Model-Driven Engineering and Software Development. MODELSWARD 2018, Communications in Computer and Information Science ; https://hal-cea.archives-ouvertes.fr/cea-02572737 ; Model-Driven Engineering and Software Development. MODELSWARD 2018, Communications in Computer and Information Science, pp.236-258, 2019, ⟨10.1007/978-3-030-11030-7_11⟩ (2019)
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An LSTM-Based Neural Network Architecture for Model Transformations
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In: 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems (MODELS) ; https://hal-cea.archives-ouvertes.fr/cea-02572669 ; 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems (MODELS), Sep 2019, Munich, Germany. pp.294-299, ⟨10.1109/MODELS.2019.00013⟩ (2019)
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Preface to MDE Intelligence 2019: 1st Workshop on Artificial Intelligence and Model-Driven Engineering
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In: 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C) ; https://hal-cea.archives-ouvertes.fr/cea-02572659 ; 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C), Sep 2019, Munich, Germany. pp.168-169, ⟨10.1109/MODELS-C.2019.00028⟩ (2019)
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The Future of Model Transformation Languages: An Open Community Discussion.
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In: ISSN: 1660-1769 ; The Journal of Object Technology ; https://hal-cea.archives-ouvertes.fr/cea-02572743 ; The Journal of Object Technology, Chair of Software Engineering, 2019, 18 (3), pp.7:1. ⟨10.5381/jot.2019.18.3.a7⟩ (2019)
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A Model Driven Tool for Requirements and Hardware Engineering
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In: 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C) ; https://hal-cea.archives-ouvertes.fr/cea-02572673 ; 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C), Sep 2019, Munich, Germany. pp.769-773, ⟨10.1109/MODELS-C.2019.00120⟩ (2019)
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On the Need for Intellectual Property Protection in Model-Driven Co-Engineering Processes
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In: International Conference on Evaluation and Modeling Methods for Systems Analysis and Development ; https://hal-cea.archives-ouvertes.fr/cea-02572729 ; International Conference on Evaluation and Modeling Methods for Systems Analysis and Development, Jun 2019, Rome, Italy. pp.169-177, ⟨10.1007/978-3-030-20618-5_12⟩ ; https://www.emmsad.org/2019-program (2019)
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Belief Uncertainty in Software Models
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In: 2019 IEEE/ACM 11th International Workshop on Modelling in Software Engineering (MiSE) ; https://hal-cea.archives-ouvertes.fr/cea-02572731 ; 2019 IEEE/ACM 11th International Workshop on Modelling in Software Engineering (MiSE), May 2019, Montreal, Canada. pp.19-26, ⟨10.1109/MiSE.2019.00011⟩ (2019)
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Using augmented reality with speech input for non-native children's language learning
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The 3D indoor deployment in DL-IoT with experimental validation using a particle swarm algorithm based on the dialects of songs
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In: Proceedings of IWCMC 2018 ; 14th International Wireless Communications and Mobile Computing Conference (IWCMC 2018) ; https://hal.archives-ouvertes.fr/hal-02883831 ; 14th International Wireless Communications and Mobile Computing Conference (IWCMC 2018), Jun 2018, Limassol, Cyprus. pp.928-933, ⟨10.1109/IWCMC.2018.8450473⟩ (2018)
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Cognifying Model-Driven Software Engineering
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In: Software Technologies: Applications and Foundations ; https://hal-cea.archives-ouvertes.fr/cea-02572650 ; Software Technologies: Applications and Foundations, pp.154-160, 2018, ⟨10.1007/978-3-319-74730-9_13⟩ (2018)
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High-Level Synthesis Using Application-Specific Arithmetic: A Case Study
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In: https://hal.archives-ouvertes.fr/hal-01502644 ; 2017 (2017)
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Bridging High-Level Synthesis and Application-Specific Arithmetic: The Case Study of Floating-Point Summations
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In: 27th International Conference on Field-Programmable Logic and Applications (FPL) ; https://hal.inria.fr/hal-01373954 ; 27th International Conference on Field-Programmable Logic and Applications (FPL), IEEE, Sep 2017, Gent, Belgium. pp.8 (2017)
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