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Found 10 papers, 2 papers with code
ANNA”:" Enhanced Language Representation for Question Answering
Pre-trained language models have brought significant improvements in performance in a variety of natural language processing tasks.
FieldHAR: A Fully Integrated End-to-end RTL Framework for Human Activity Recognition with Neural Networks from Heterogeneous Sensors
In this work, we propose an open-source scalable end-to-end RTL framework FieldHAR, for complex human activity recognition (HAR) from heterogeneous sensors using artificial neural networks (ANN) optimized for FPGA or ASIC integration.
ANNA: Enhanced Language Representation for Question Answering
Pre-trained language models have brought significant improvements in performance in a variety of natural language processing tasks.
Korean-Specific Dataset for Table Question Answering
Subsequently, we then build a pre-trained language model based on Transformer and fine-tune the model for table question answering with these datasets.
Layer-specific Optimization for Mixed Data Flow with Mixed Precision in FPGA Design for CNN-based Object Detectors
The proposed design employs two layer-specific optimizations: layer-specific mixed data flow and layer-specific mixed precision.
QE BERT: Bilingual BERT Using Multi-task Learning for Neural Quality Estimation
Our proposed model is re-purposed BERT for the translation quality estimation and uses multi-task learning for the sentence-level task and word-level subtasks (i. e., source word, target word, and target gap).
Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving
Therefore, a detection algorithm that can cope with mislocalizations is required in autonomous driving applications.
