14 citations · 25 across the 11 of their papers we have counts for
14 papers
Investigating Spatiotemporal Redundancy in Video Transformer for Collision Anticipation
Xiaoshan Zhou
In worker-equipment proximity monitoring, video transformers are widely used for collision anticipation and have demonstrated strong performance. However, their accuracy comes with…
CrisisFake: Benchmark Validity of AI-Generated Text Detection for Disaster Social Sensing
Xiaoshan Zhou, Zaifu Zhan
Disaster social sensing converts public social-media posts into evidence for situational awareness and humanitarian response, but plausible LLM-generated posts can contaminate this…
ConsensusTAS: Self-Supervised Temporal Action Segmentation for Long-Horizon Construction Videos
Xiaoshan Zhou, Yafei Sun
Recognizing sequential construction activities is important for collaborative human-robot work; for example, robots are able to understand workers' current and upcoming actions and…
Self-Supervised Evolutionary Learning of Neurodynamic Progression and Identity Manifolds from EEG During Safety-Critical Decision Making
Xiaoshan Zhou, Carol C. Menassa, Vineet R. Kamat
Human-vehicle interaction in safety-critical traffic environments increasingly incorporates neural sensing to infer user intent and cognitive state, yet most existing approaches ei…
Feasibility of Embodied Dynamics Based Bayesian Learning for Continuous Pursuit Motion Control of Assistive Mobile Robots in the Built Environment
Xiaoshan Zhou, Carol C. Menassa, Vineet R. Kamat
Non-invasive electroencephalography (EEG)-based brain-computer interfaces (BCIs) offer an intuitive means for individuals with severe motor impairments to independently operate ass…
Retrieval-augmented in-context learning for multimodal large language models in disease classification
Zaifu Zhan, Shuang Zhou, Xiaoshan Zhou +6
Objectives: We aim to dynamically retrieve informative demonstrations, enhancing in-context learning in multimodal large language models (MLLMs) for disease classification. Methods…
Siamese Network with Dual Attention for EEG-Driven Social Learning: Bridging the Human-Robot Gap in Long-Tail Autonomous Driving
Xiaoshan Zhou, Carol C. Menassa, Vineet R. Kamat
Robots with wheeled, quadrupedal, or humanoid forms are increasingly integrated into built environments. However, unlike human social learning, they lack a critical pathway for int…
Interoceptive Robots for Convergent Shared Control in Collaborative Construction Work
Xiaoshan Zhou, Carol C. Menassa, Vineet R. Kamat
Building autonomous mobile robots (AMRs) with optimized efficiency and adaptive capabilities-able to respond to changing task demands and dynamic environments-is a strongly desired…
Towards Probabilistic Inference of Human Motor Intentions by Assistive Mobile Robots Controlled via a Brain-Computer Interface
Xiaoshan Zhou, Carol M. Menassa, Vineet R. Kamat
Assistive mobile robots are a transformative technology that helps persons with disabilities regain the ability to move freely. Although autonomous wheelchairs significantly reduce…
Biologically Inspired Predictive Coding TCN-Transformer for Anticipatory Human-Robot Interaction in Shared Physical Spaces
Xiaoshan Zhou, Carol C. Menassa, Vineet R. Kamat
As mobile robots increasingly operate in environments shared with humans, proactively anticipating human motion rather than responding reactively is critical for preempting collisi…
A privacy-preserving data storage and service framework based on deep learning and blockchain for construction workers' wearable IoT sensors
Xiaoshan Zhou, Pin-Chao Liao
Classifying brain signals collected by wearable Internet of Things (IoT) sensors, especially brain-computer interfaces (BCIs), is one of the fastest-growing areas of research. Howe…
Brain informed transfer learning for categorizing construction hazards
Xiaoshan Zhou, Pin-Chao Liao
A transfer learning paradigm is proposed for "knowledge" transfer between the human brain and convolutional neural network (CNN) for a construction hazard categorization task. Part…
Weighing votes in human-machine collaboration for hazard recognition: Inferring hazard perceptual threshold and decision confidence from electroencephalogram wavelets
Xiaoshan Zhou, Pin-Chao Liao
Purpose: Human-machine collaboration is a promising strategy to improve hazard inspection. However, research on the effective integration of opinions from humans with machines for…
EEG-based performance-driven adaptive automated hazard alerting system in security surveillance support
Xiaoshan Zhou, Pin-Chao Liao
Computer-vision technologies have emerged to assist security surveillance. However, automation alert/alarm systems often apply a low-beta threshold to avoid misses and generates ex…