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Found 21 papers, 1 papers with code
PRIME: A CyberGIS Platform for Resilience Inference Measurement and Enhancement
This study aims to address these gaps through the power of CyberGIS with three objectives: 1) To develop an empirically validated disaster resilience model - Customized Resilience Inference Measurement designed for multi-scale community resilience assessment and influential socioeconomic factors identification, 2) To implement a Platform for Resilience Inference Measurement and Enhancement module in the CyberGISX platform backed by high-performance computing, 3) To demonstrate the utility of PRIME through a representative study.
Context-Aware Block Net for Small Object Detection
State-of-the-art object detectors usually progressively downsample the input image until it is represented by small feature maps, which loses the spatial information and compromises the representation of small objects.
Ranked #1 on
Traffic Sign Detection
on TT100K
TopoBERT: Plug and Play Toponym Recognition Module Harnessing Fine-tuned BERT
Extracting precise geographical information from textual contents is crucial in a plethora of applications.
Multi-scale Feature Aggregation for Crowd Counting
The SkipAgg module directly propagates features with small receptive fields to features with much larger receptive fields.
Multi-Spatio-temporal Fusion Graph Recurrent Network for Traffic forecasting
The network proposes a data-driven weighted adjacency matrix generation method to compensate for real-time spatial dependencies not reflected by the predefined adjacency matrix.
STCGAT: A Spatio-temporal Causal Graph Attention Network for traffic flow prediction in Intelligent Transportation Systems
Existing methods are usually based on graph neural networks using predefined spatial adjacency graphs of traffic networks to model spatial dependencies, ignoring the dynamic correlation of relationships between road nodes.
Sparse Depth Completion with Semantic Mesh Deformation Optimization
Sparse depth measurements are widely available in many applications such as augmented reality, visual inertial odometry and robots equipped with low cost depth sensors.
User-Guided Personalized Image Aesthetic Assessment based on Deep Reinforcement Learning
This framework leverages user interactions to retouch and rank images for aesthetic assessment based on deep reinforcement learning (DRL), and generates personalized aesthetic distribution that is more in line with the aesthetic preferences of different users.
Emotional Contagion-Aware Deep Reinforcement Learning for Antagonistic Crowd Simulation
In this paper, we propose an Emotional contagion-aware Deep reinforcement learning model for Antagonistic Crowd Simulation (ACSED).
Agent-Based Campus Novel Coronavirus Infection and Control Simulation
Corona Virus Disease 2019 (COVID-19), due to its extremely high infectivity, has been spreading rapidly around the world and bringing huge influence to socioeconomic development as well as people's daily life.
Social and Information Networks Physics and Society Populations and Evolution
Probability Trajectory: One New Movement Description for Trajectory Prediction
Based on this unique description, we develop one novel trajectory prediction method, called social probability.
Personality-Aware Probabilistic Map for Trajectory Prediction of Pedestrians
We update this map dynamically based on the agents in the environment and prior trajectory of a pedestrian.
Multi-scale discriminative Region Discovery for Weakly-Supervised Object Localization
On ILSVRC 2016, the proposed method yields the Top-1 localization error of 48. 65\%, which outperforms previous results by 2. 75\%.
Interpretability Analysis of Heartbeat Classification Based on Heartbeat Activity’s Global Sequence Features and BiLSTM-Attention Neural Network
Arrhythmia is a disease that threatens human life.
Ranked #2 on
Arrhythmia Detection
on MIT-BIH AR
Abnormal Event Detection and Location for Dense Crowds using Repulsive Forces and Sparse Reconstruction
This paper proposes a method based on repulsive forces and sparse reconstruction for the detection and location of abnormal events in crowded scenes.
MDSSD: Multi-scale Deconvolutional Single Shot Detector for Small Objects
The performance of small object detection, however, is still less than satisfactory because of the deficiency of semantic information on shallow feature maps.
USAR: an Interactive User-specific Aesthetic Ranking Framework for Images
When assessing whether an image is of high or low quality, it is indispensable to take personal preference into account.
Bi-directional Graph Structure Information Model for Multi-Person Pose Estimation
The first branch predicts the confidence maps of joints and uses a geometrical transform kernel to propagate information between neighboring joints at the confidence level.
Depth Information Guided Crowd Counting for Complex Crowd Scenes
DigCrowd first uses the depth information of an image to segment the scene into a far-view region and a near-view region.
Macroblock Classification Method for Video Applications Involving Motions
We demonstrate that this low-computation-complexity method can efficiently catch the characteristics of the frame.
Improved Image Deblurring based on Salient-region Segmentation
Image deblurring techniques play important roles in many image processing applications.
