Search Results for author:
Found 13 papers, 3 papers with code
HVDetFusion: A Simple and Robust Camera-Radar Fusion Framework
In this study, we propose a new detection algorithm called HVDetFusion, which is a multi-modal detection algorithm that not only supports pure camera data as input for detection, but also can perform fusion input of radar data and camera data.
Ranked #110 on
3D Object Detection
on nuScenes
Data-driven Smart Ponzi Scheme Detection
To solve these problems, we propose a data-driven smart Ponzi scheme detection system in this paper.
Relabel the Noise: Joint Extraction of Entities and Relations via Cooperative Multiagents
Distant supervision based methods for entity and relation extraction have received increasing popularity due to the fact that these methods require light human annotation efforts.
Exploring and Distilling Cross-Modal Information for Image Captioning
Recently, attention-based encoder-decoder models have been used extensively in image captioning.
Self-Adaptive Scaling for Learnable Residual Structure
Residual has been widely applied to build deep neural networks with enhanced feature propagation and improved accuracy.
GCN-GAN: A Non-linear Temporal Link Prediction Model for Weighted Dynamic Networks
Different from conventional techniques of temporal link prediction that ignore the potential non-linear characteristics and the informative link weights in the dynamic network, we introduce a novel non-linear model GCN-GAN to tackle the challenging temporal link prediction task of weighted dynamic networks.
Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question Answering
Second, these two tasks can benefit each other: answer selection can incorporate the external knowledge from knowledge base (KB), while KBQA can be improved by learning contextual information from answer selection.
A Knowledge Graph Based Solution for Entity Discovery and Linking in Open-Domain Questions
In Question Entity Discovery and Linking (QEDL) problem, traditional methods are challenged because multiple entities in one short question are difficult to be discovered entirely and the incomplete information in short text makes entity linking hard to implement.
Improving Medical Short Text Classification with Semantic Expansion Using Word-Cluster Embedding
However, in electronic medical records (EMR), the texts containing sentences are shorter than that in general domain, which leads to the lack of semantic features and the ambiguity of semantic.
MedSim: A Novel Semantic Similarity Measure in Bio-medical Knowledge Graphs
We present MedSim, a novel semantic SIMilarity method based on public well-established bio-MEDical knowledge graphs (KGs) and large-scale corpus, to study the therapeutic substitution of antibiotics.
MedTruth: A Semi-supervised Approach to Discovering Knowledge Condition Information from Multi-Source Medical Data
In the light of these challenges, we propose a new truth discovery method, MedTruth, for medical knowledge condition discovery, which incorporates prior source quality information into the source reliability estimation procedure, and also utilizes the knowledge triple information for trustworthy information computation.
Databases
Cooperative Denoising for Distantly Supervised Relation Extraction
Distantly supervised relation extraction greatly reduces human efforts in extracting relational facts from unstructured texts.
Knowledge as A Bridge: Improving Cross-domain Answer Selection with External Knowledge
In this paper, we propose Knowledge-aware Attentive Network (KAN), a transfer learning framework for cross-domain answer selection, which uses the knowledge base as a bridge to enable knowledge transfer from the source domain to the target domains.
