Papers Edge Classification
“Edge Classification” 태그가 달린 논문 56편 · 필터 해제
Global Self-Attention as a Replacement for Graph Convolution
We propose an extension to the transformer neural network architecture for general-purpose graph learning by adding a dedicated pathway for pairwise structural information, called edge channels. The resultant framework -…
Edge ClassificationGraph ClassificationGraph LearningGraph Property Prediction+5Charged particle tracking via edge-classifying interaction networks
Recent work has demonstrated that geometric deep learning methods such as graph neural networks (GNNs) are well suited to address a variety of reconstruction problems in high energy particle physics. In particular, parti…
Edge Classificationgraph constructionAttrE2vec: Unsupervised Attributed Edge Representation Learning
Representation learning has overcome the often arduous and manual featurization of networks through (unsupervised) feature learning as it results in embeddings that can apply to a variety of downstream learning tasks. Th…
ClusteringEdge ClassificationRepresentation LearningAnalyzing the Performance of Graph Neural Networks with Pipe Parallelism
Many interesting datasets ubiquitous in machine learning and deep learning can be described via graphs. As the scale and complexity of graph-structured datasets increase, such as in expansive social networks, protein fol…
BIG-bench Machine LearningDeep LearningEdge ClassificationLink Prediction+1Unmixing Convolutional Features for Crisp Edge Detection
This paper presents a context-aware tracing strategy (CATS) for crisp edge detection with deep edge detectors, based on an observation that the localization ambiguity of deep edge detectors is mainly caused by the mixing…
Edge ClassificationEdge DetectionReal-Time Edge Classification: Optimal Offloading under Token Bucket Constraints
To deploy machine learning-based algorithms for real-time applications with strict latency constraints, we consider an edge-computing setting where a subset of inputs are offloaded to the edge for processing by an accura…
ClassificationEdge ClassificationEdge-computingGeneral Classification+2Deep Multi-Scale Feature Learning for Defocus Blur Estimation
This paper presents an edge-based defocus blur estimation method from a single defocused image. We first distinguish edges that lie at depth discontinuities (called depth edges, for which the blur estimate is ambiguous) …
Edge ClassificationLearning and Reasoning with the Graph Structure Representation in Robotic Surgery
Learning to infer graph representations and performing spatial reasoning in a complex surgical environment can play a vital role in surgical scene understanding in robotic surgery. For this purpose, we develop an approac…
Edge ClassificationGraph GenerationScene Graph GenerationScene Segmentation+2LoCEC: Local Community-based Edge Classification in Large Online Social Networks
Relationships in online social networks often imply social connections in the real world. An accurate understanding of relationship types benefits many applications, e.g. social advertising and recommendation. Some recen…
ClassificationCommunity DetectionEdge ClassificationGeneral Classification+1Shearlets as Feature Extractor for Semantic Edge Detection: The Model-Based and Data-Driven Realm
Semantic edge detection has recently gained a lot of attention as an image processing task, mainly due to its wide range of real-world applications. This is based on the fact that edges in images contain most of the sema…
Edge ClassificationEdge DetectionDynamic Graph Convolutional Networks Using the Tensor M-Product
Many irregular domains such as social networks, financial transactions, neuron connections, and natural language constructs are represented using graph structures. In recent years, a variety of graph neural networks (GNN…
Edge ClassificationLink PredictionRepresentation Learningtensor algebraLeaf segmentation through the classification of edges
We present an approach to leaf level segmentation of images of Arabidopsis thaliana plants based upon detected edges. We introduce a novel approach to edge classification, which forms an important part of a method to bot…
ClassificationEdge ClassificationGeneral ClassificationSegmentationEvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
Graph representation learning resurges as a trending research subject owing to the widespread use of deep learning for Euclidean data, which inspire various creative designs of neural networks in the non-Euclidean domain…
Dynamic Link PredictionEdge ClassificationGeneral ClassificationGraph Representation Learning+3LaneNet: Real-Time Lane Detection Networks for Autonomous Driving
Lane detection is to detect lanes on the road and provide the accurate location and shape of each lane. It severs as one of the key techniques to enable modern assisted and autonomous driving systems. However, several un…
Autonomous DrivingEdge ClassificationLane DetectionSalProp: Salient object proposals via aggregated edge cues
In this paper, we propose a novel object proposal generation scheme by formulating a graph-based salient edge classification framework that utilizes the edge context. In the proposed method, we construct a Bayesian proba…
ClassificationEdge ClassificationGeneral ClassificationObject+3Classification in biological networks with hypergraphlet kernels
Biological and cellular systems are often modeled as graphs in which vertices represent objects of interest (genes, proteins, drugs) and edges represent relational ties among these objects (binds-to, interacts-with, regu…
ClassificationEdge ClassificationGeneral ClassificationLink Prediction