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Found 13 papers, 4 papers with code
Minimize Quantization Output Error with Bias Compensation
Quantization is a promising method that reduces memory usage and computational intensity of Deep Neural Networks (DNNs), but it often leads to significant output error that hinder model deployment.
Exploring the Adversarial Frontier: Quantifying Robustness via Adversarial Hypervolume
To address this gap, we propose a new metric termed adversarial hypervolume, assessing the robustness of deep learning models comprehensively over a range of perturbation intensities from a multi-objective optimization standpoint.
AutoQNN: An End-to-End Framework for Automatically Quantizing Neural Networks
QSS introduces five quantizing schemes and defines three new schemes as a candidate set for scheme search, and then uses the differentiable neural architecture search (DNAS) algorithm to seek the layer- or model-desired scheme from the set.
Using multiple reference audios and style embedding constraints for speech synthesis
The end-to-end speech synthesis model can directly take an utterance as reference audio, and generate speech from the text with prosody and speaker characteristics similar to the reference audio.
Elastic Significant Bit Quantization and Acceleration for Deep Neural Networks
We implement ESB as an accelerator and quantitatively evaluate its efficiency on FPGAs.
Orientation-Aware Planning for Parallel Task Execution of Omni-Directional Mobile Robot
Omni-directional mobile robot (OMR) systems have been very popular in academia and industry for their superb maneuverability and flexibility.
Autonomous Driving Strategies at Intersections: Scenarios, State-of-the-Art, and Future Outlooks
Due to the complex and dynamic character of intersection scenarios, the autonomous driving strategy at intersections has been a difficult problem and a hot point in the research of intelligent transportation systems in recent years.
DiDiSpeech: A Large Scale Mandarin Speech Corpus
This paper introduces a new open-sourced Mandarin speech corpus, called DiDiSpeech.
Audio and Speech Processing
High-precision target positioning system for unmanned vehicles based on binocular vision
In order to verify the effect of the system, this paper collects the accuracy and calculation time of the output results of the cylinder in different poses.
Driver Behavior Modelling at the Urban Intersection via Canonical Correlation Analysis
Accurately modelling the driver behavior at the intersection is essential for intelligent transportation systems (ITS).
VecQ: Minimal Loss DNN Model Compression With Vectorized Weight Quantization
Quantization has been proven to be an effective method for reducing the computing and/or storage cost of DNNs.
DELTA: A DEep learning based Language Technology plAtform
In this paper we present DELTA, a deep learning based language technology platform.
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Enhanced-alignment Measure for Binary Foreground Map Evaluation
The existing binary foreground map (FM) measures to address various types of errors in either pixel-wise or structural ways.
