Search Results for author:
Found 12 papers, 2 papers with code
Evolutionary Trigger Detection and Lightweight Model Repair Based Backdoor Defense
In the second phase of our method, we leverage several lightweight unlearning methods with the trigger detected by CETF for model repair, which also constructively demonstrate the underlying correlation of the backdoor with Batch Normalization layers.
A Survey on Consumer IoT Traffic: Security and Privacy
Although CIoT has improved the convenience of daily activities, it also introduces new security and privacy concerns.
Syntax-Guided Domain Adaptation for Aspect-based Sentiment Analysis
In this work, we propose a novel Syntax-guided Domain Adaptation Model, named SDAM, for more effective cross-domain ABSA.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+2
LeVoice ASR Systems for the ISCSLP 2022 Intelligent Cockpit Speech Recognition Challenge
This paper describes LeVoice automatic speech recognition systems to track2 of intelligent cockpit speech recognition challenge 2022.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+6
CGNN: Traffic Classification with Graph Neural Network
Extensive evaluation over real-world traffic data sets, including normal, encrypted and malicious labels, show that, CGNN improves the prediction accuracy by 23\% to 29\% for application classification, by 2\% to 37\% for malicious traffic classification, and reaches the same accuracy level for encrypted traffic classification.
The Role of Explainability in Assuring Safety of Machine Learning in Healthcare
Established approaches to assuring safety-critical systems and software are difficult to apply to systems employing ML where there is no clear, pre-defined specification against which to assess validity.
BIG-bench Machine Learning
Explainable Artificial Intelligence (XAI)
The DKU System Description for The Interspeech 2021 Auto-KWS Challenge
This paper introduces the system submitted by the DKU-SMIIP team for the Auto-KWS 2021 Challenge.
Guidance on the Assurance of Machine Learning in Autonomous Systems (AMLAS)
Machine Learning (ML) is now used in a range of systems with results that are reported to exceed, under certain conditions, human performance.
A Framework for Assurance of Medication Safety using Machine Learning
As healthcare is now data rich, it is possible to augment safety analysis with machine learning to discover actual causes of medication error from the data, and to identify where they deviate from what was predicted in the safety analysis.
Training Wake Word Detection with Synthesized Speech Data on Confusion Words
Confusing-words are commonly encountered in real-life keyword spotting applications, which causes severe degradation of performance due to complex spoken terms and various kinds of words that sound similar to the predefined keywords.
Domain Aware Training for Far-field Small-footprint Keyword Spotting
In this paper, we focus on the task of small-footprint keyword spotting under the far-field scenario.
From RGB to Spectrum for Natural Scenes via Manifold-Based Mapping
Spectral analysis of natural scenes can provide much more detailed information about the scene than an ordinary RGB camera.
