79 citations · 98 across the 12 of their papers we have counts for
13 papers
Mind the Refinement Gap: When Safe High-Level Robot Plans Produce Unsafe Executions
Stabak Das, Priyesh Ranjan, Xiangfang Li +1
Language-enabled robot systems increasingly combine semantic-graph planning with temporal-logic safety monitors. We investigate a trace-completeness assumption in these systems: wh…
Transmitter Identification and Protocol Categorization in Shared Spectrum via Multi-Task RF Classification at the Network Edge
Tariq Abdul-Quddoos, Tasnia Sharmin, Xiangfang Li +1
As spectrum sharing becomes increasingly vital to meet rising wireless demands in the future, spectrum monitoring and transmitter identification are indispensable for enforcing spe…
Deep Knowledge Tracing for Personalized Adaptive Learning at Historically Black Colleges and Universities
Ming-Mu Kuo, Xiangfang Li, Lijun Qian +2
Personalized adaptive learning (PAL) stands out by closely monitoring individual students' progress and tailoring their learning paths to their unique knowledge and needs. A crucia…
Enhancing LLM Fine-tuning for Text-to-SQLs by SQL Quality Measurement
Shouvon Sarker, Xishuang Dong, Xiangfang Li +1
Text-to-SQLs enables non-expert users to effortlessly retrieve desired information from relational databases using natural language queries. While recent advancements, particularly…
Enhancing Deep Knowledge Tracing via Diffusion Models for Personalized Adaptive Learning
Ming Kuo, Shouvon Sarker, Lijun Qian +3
In contrast to pedagogies like evidence-based teaching, personalized adaptive learning (PAL) distinguishes itself by closely monitoring the progress of individual students and tail…
Inverse Quantum Fourier Transform Inspired Algorithm for Unsupervised Image Segmentation
Taoreed Akinola, Xiangfang Li, Richard Wilkins +2
Image segmentation is a very popular and important task in computer vision. In this paper, inverse quantum Fourier transform (IQFT) for image segmentation has been explored and a n…
Calibrated Bagging Deep Learning for Image Semantic Segmentation: A Case Study on COVID-19 Chest X-ray Image
Lucy Nwosu, Xiangfang Li, Lijun Qian +2
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19). Imaging tests such as chest X-ray (CXR) and computed tomography (CT) can pr…
Semi-supervised Learning for COVID-19 Image Classification via ResNet
Lucy Nwosu, Xiangfang Li, Lijun Qian +2
Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic in over 200 countries and territories, which has resulted in a great public health concern across the internationa…
A Survey of Complex-Valued Neural Networks
Joshua Bassey, Lijun Qian, Xianfang Li
Artificial neural networks (ANNs) based machine learning models and especially deep learning models have been widely applied in computer vision, signal processing, wireless communi…
Computation Offloading in Multi-Access Edge Computing Networks: A Multi-Task Learning Approach
Bo Yang, Xuelin Cao, Joshua Bassey +3
Multi-access edge computing (MEC) has already shown the potential in enabling mobile devices to bear the computation-intensive applications by offloading some tasks to a nearby acc…
Lessons Learned from Accident of Autonomous Vehicle Testing: An Edge Learning-aided Offloading Framework
Bo Yang, Xuelin Cao, Xiangfang Li +2
This letter proposes an edge learning-based offloading framework for autonomous driving, where the deep learning tasks can be offloaded to the edge server to improve the inference…
Cell Type Identification from Single-Cell Transcriptomic Data via Semi-supervised Learning
Xishuang Dong, Shanta Chowdhury, Uboho Victor +2
Cell type identification from single-cell transcriptomic data is a common goal of single-cell RNA sequencing (scRNAseq) data analysis. Neural networks have been employed to identif…
Device Authentication Codes based on RF Fingerprinting using Deep Learning
Joshua Bassey, Xiangfang Li, Lijun Qian
In this paper, we propose Device Authentication Code (DAC), a novel method for authenticating IoT devices with wireless interface by exploiting their radio frequency (RF) signature…