Search Results for author:
Found 26 papers, 3 papers with code
Post-disaster building indoor damage and survivor detection using autonomous path planning and deep learning with unmanned aerial vehicles
Rapid response to natural disasters such as earthquakes is a crucial element in ensuring the safety of civil infrastructures and minimizing casualties.
InsightEdit: Towards Better Instruction Following for Image Editing
In this paper, we focus on the task of instruction-based image editing.
Research on the Spatial Data Intelligent Foundation Model
This report focuses on spatial data intelligent large models, delving into the principles, methods, and cutting-edge applications of these models.
GD^2-NeRF: Generative Detail Compensation via GAN and Diffusion for One-shot Generalizable Neural Radiance Fields
Targeting these issues, we propose the GD$^2$-NeRF, a Generative Detail compensation framework via GAN and Diffusion that is both inference-time finetuning-free and with vivid plausible details.
Vision-aided nonlinear control framework for shake table tests
The signal generated by the control law of the adaptive control method will be implemented by a loop-shaping controller.
3D vision-based structural masonry damage detection
Automation of the inspection process using novel computer vision and machine learning algorithms can be a more efficient and safe solution to prevent further deterioration of the masonry structures.
Autonomous damage assessment of structural columns using low-cost micro aerial vehicles and multi-view computer vision
Experimental results indicate that the proposed MAV-based inspection approach can effectively collect images from multiple viewing angles, and accurately assess critical RC column damages.
A reinforcement learning based construction material supply strategy using robotic crane and computer vision for building reconstruction after an earthquake
In this paper, the robotic crane with advanced AI algorithms is proposed to provide resources for infrastructure reconstruction after an earthquake.
A Real-Time Robust Ecological-Adaptive Cruise Control Strategy for Battery Electric Vehicles
This work addresses the ecological-adaptive cruise control problem for connected electric vehicles by a computationally efficient robust control strategy.
TransHuman: A Transformer-based Human Representation for Generalizable Neural Human Rendering
However, such SPC-based representation i) optimizes under the volatile observation space which leads to the pose-misalignment between training and inference stages, and ii) lacks the global relationships among human parts that is critical for handling the incomplete painted SMPL.
Masked Audio Text Encoders are Effective Multi-Modal Rescorers
Masked Language Models (MLMs) have proven to be effective for second-pass rescoring in Automatic Speech Recognition (ASR) systems.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
A Computationally Efficient Robust Model Predictive Control Framework for Ecological Adaptive Cruise Control Strategy of Electric Vehicles
The control objective of the RMPC is to optimise the electric energy efficiency of the ego vehicle with consideration of a bounded model mismatch disturbance subject to satisfaction of physical and safety constraints.
Economic Potential for Hybrid Electric Vehicles in Urban Signal-free Intersections with Decentralized MPC
The development of electric and connected vehicles as well as automated driving technologies are key towards the smart city, with convenient urban mobility and high energy economy performance.
Dynamic Gradient Reactivation for Backward Compatible Person Re-identification
To address this issue, we propose the Ranking-based Backward Compatible Learning (RBCL), which directly optimizes the ranking metric between new features and old features.
A Convex Optimal Control Framework for Autonomous Vehicle Intersection Crossing
Cooperative vehicle management emerges as a promising solution to improve road traffic safety and efficiency.
Optimal Energy Management of Series Hybrid Electric Vehicles with Engine Start-Stop System
The paper first derives two important analytic results: a) analytic EM optimal solutions of fundamental and commonly used series HEV frameworks, and b) proof of optimality of charge sustaining operation in series HEVs.
In-N-Out Generative Learning for Dense Unsupervised Video Segmentation
By contrast, pixel-level optimization is more explicit, however, it is sensitive to the visual quality of training data and is not robust to object deformation.
Dynamic Analysis of Nonlinear Civil Engineering Structures using Artificial Neural Network with Adaptive Training
In this study, artificial neural networks are developed with adaptive training algorithms, which enables automatic nodes generation and layers addition.
Postdisaster image-based damage detection and repair cost estimation of reinforced concrete buildings using dual convolutional neural networks
The proposed YOLO-v2 is used in combination with the classification neural network, which improves the identification accuracy for critical damage state of reinforced concrete structures by 7. 5%.
Image-based monitoring of bolt loosening through deep-learning-based integrated detection and tracking
Then, the target-free object tracking algorithm based on optical flow is implemented, to continuously monitor and quantify the rotation of structural bolts.
Contrastive Learning for Many-to-many Multilingual Neural Machine Translation
Existing multilingual machine translation approaches mainly focus on English-centric directions, while the non-English directions still lag behind.
The Volctrans Machine Translation System for WMT20
This paper describes our VolcTrans system on WMT20 shared news translation task.
Pre-training Multilingual Neural Machine Translation by Leveraging Alignment Information
We investigate the following question for machine translation (MT): can we develop a single universal MT model to serve as the common seed and obtain derivative and improved models on arbitrary language pairs?
Ranked #3 on
Machine Translation
on WMT2014 English-French
(using extra training data)
Texture Relative Superpixel Generation With Adaptive Parameters
Abstract—Superpixel generation, which is an essential step in many image processing applications, has attracted increasing attention from researchers.
Bicycle-Sharing System Analysis and Trip Prediction
In bicycle-sharing systems, people can borrow and return bikes at any stations in the service region very conveniently.
