A5059143690- Plant Stress Responses and Tolerance
- Teleoperation and Haptic Systems
- 3D Surveying and Cultural Heritage
- Soft Robotics and Applications
- Hibiscus Plant Research Studies
- AI-based Problem Solving and Planning
- Tactile and Sensory Interactions
- Aluminum toxicity and tolerance in plants and animals
- Geophysical Methods and Applications
- Robot Manipulation and Learning
- Plant Molecular Biology Research
- Seismology and Earthquake Studies
- Human Pose and Action Recognition
- Indoor and Outdoor Localization Technologies
- Gaze Tracking and Assistive Technology
- Plant biochemistry and biosynthesis
- Multimodal Machine Learning Applications
- Virtual Reality Applications and Impacts
- Image and Object Detection Techniques
- Photosynthetic Processes and Mechanisms
- Plant Gene Expression Analysis
- Anomaly Detection Techniques and Applications
University of Hong Kong
2022-2024
Guangxi University
2017-2020
Histone acetylation is an important epigenetic modification that regulates gene activity in response to stress. levels are reversibly regulated by histone acetyltransferases (HATs) and deacetylases (HDACs). The imperative roles of HDACs transcription, transcriptional regulation, growth responses stressful environment have been widely investigated Arabidopsis. However, data regarding kenaf crop has not disclosed yet. In this study, six genes (HcHDA2, HcHDA6, HcHDA8, HcHDA9, HcHDA19, HcSRT2)...
Understanding human intentions during interactions has been a long-lasting theme, that applications in human-robot interaction, virtual reality and surveillance. In this study, we focus on full-body with large-sized daily objects aim to predict the future states of humans given sequential observation human-object interaction. As there is no such dataset dedicated objects, collected large-scale containing thousands for training evaluation purposes. We also observe an object's intrinsic...
Teleoperation systems find many applications from earlier search-and-rescue to more recent daily tasks. It is widely acknowledged that using external sensors can decouple the view of remote scene motion robot arm during manipulation, facilitating control task. However, this design requires coordination multiple operators or may exhaust a single operator as s/he needs both manipulator and sensors. To address challenge, our work introduces viewpoint prediction model, first data-driven approach...
We propose a deep visuo-tactile model for real-time estimation of the liquid inside deformable container in proprioceptive way. fuse two sensory modalities, i.e., raw visual inputs from RGB camera and tactile cues our specific sensor without any extra calibrations. The robotic system is well controlled adjusted based on real time. main contributions novelties work are listed as follows: 1) Explore way volume by developing an end-to-end predictive with multi-modal convolutional networks,...
Proximity sensing detects an object's presence without contact. However, research has rarely explored proximity in granular materials (GM) due to GM's lack of visual and complex properties. In this paper, we propose a granular-material-embedded autonomous system (GRAINS) based on three phenomena (fluidization, jamming, failure wedge zone). GRAINS can automatically sense buried objects beneath GM real-time manner (at least ~20 hertz) perceive them 0.5 ~ 7 centimeters ahead different granules...
Enabling robotic agents to perform complex long-horizon tasks has been a long-standing goal in robotics and artificial intelligence (AI). Despite the potential shown by large language models (LLMs), their planning capabilities remain limited short-horizon they are unable replace symbolic approach. Symbolic planners, on other hand, may encounter execution errors due common assumption of complete domain knowledge which is hard manually prepare for an open-world setting. In this paper, we...
The proximity perception of objects in granular materials is significant, especially for applications like minesweeping. However, due to particles' opacity and complex properties, existing sensors suffer from high costs sophisticated hardware user-cost unintuitive results. In this paper, we propose a simple yet effective sensing system underground stuff based on the haptic feedback sensor-granules interaction. We study employ unique characteristic particles -- failure wedge zone, combine...
Granular materials (GMs) are ubiquitous in daily life. Understanding their properties is also important, especially agriculture and industry. However, existing works require dedicated measurement equipment need large human efforts to handle a number of particles. In this paper, we introduce method for estimating the relative values particle size density from video interaction with GMs. It trained on visuo-haptic learning framework inspired by contact model, which reveals strong correlation...
We propose a deep visuo-tactile model for realtime estimation of the liquid inside deformable container in proprioceptive way.We fuse two sensory modalities, i.e., raw visual inputs from RGB camera and tactile cues our specific sensor without any extra calibrations.The robotic system is well controlled adjusted based on real time. The main contributions novelties work are listed as follows: 1) Explore way volume by developing an end-to-end predictive with multi-modal convolutional networks,...