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Found 12 papers, 5 papers with code
TempCaps: A Capsule Network-based Embedding Model for Temporal Knowledge Graph Completion
In this paper, we tackle the temporal knowledge graph completion task by proposing TempCaps, which is a Capsule network-based embedding model for Temporal knowledge graph completion.
Box Supervised Video Segmentation Proposal Network
Video Object Segmentation (VOS) has been targeted by various fully-supervised and self-supervised approaches.
Conifer Seedling Detection in UAV-Imagery with RGB-Depth Information
Increasing the resolution of this height information also showed little effect.
MIRA: Multihop Relation Prediction in Temporal Knowledge Graphs
Given query entities, our agent starts to gather temporal relevant information about the neighborhood of the subject and object.
SEA: Graph Shell Attention in Graph Neural Networks
Intuitively, by increasing the number of experts, the models gain in expressiveness such that a node's representation is solely based on nodes that are located within the receptive field of an expert.
Learning Self-Expression Metrics for Scalable and Inductive Subspace Clustering
Consequently, our model benefits from a constant number of parameters and a constant-size memory footprint, allowing it to scale to considerably larger datasets.
Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network
Inspired by the success of edge enhanced GAN (EEGAN) and ESRGAN, we apply a new edge-enhanced super-resolution GAN (EESRGAN) to improve the image quality of remote sensing images and use different detector networks in an end-to-end manner where detector loss is backpropagated into the EESRGAN to improve the detection performance.
Unsupervised Anomaly Detection for X-Ray Images
Therefore, we adopt state-of-the-art approaches for unsupervised learning to detect anomalies and show how the outputs of these methods can be explained.
MMGAN: Generative Adversarial Networks for Multi-Modal Distributions
Moreover, MMGAN allows for clustering real data according to the learned data manifold in the latent space.
Semi-Supervised Learning on Graphs Based on Local Label Distributions
Precisely, we propose a new node embedding which is based on the class labels in the local neighborhood of a node.
Semi-supervised Outlier Detection using Generative And Adversary Framework
In the adversarial process of training CorGAN, the Generator is supposed to generate outlier samples for negative class, and the Discriminator as an one-class classifier is trained to distinguish data from training datasets (i. e. positive class) and generated data from the Generator (i. e. negative class).
Skill-Based Differences in Spatio-Temporal Team Behavior in Defence of The Ancients 2
Results indicate that spatio-temporal behavior of MOBA teams is related to team skill, with professional teams having smaller within-team distances and conducting more zone changes than amateur teams.
