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Found 14 papers, 2 papers with code
MTGA: Multi-view Temporal Granularity aligned Aggregation for Event-based Lip-reading
Then we design a spatio-temporal fusion module based on temporal granularity alignment, where the global spatial features extracted from event frames, together with the local relative spatial and temporal features contained in voxel graph list are effectively aligned and integrated.
Aligning Individual and Collective Objectives in Multi-Agent Cooperation
The visualization of learning dynamics effectively demonstrates that AgA successfully achieves alignment between individual and collective objectives.
Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results
The FeTA Challenge 2022 was able to successfully evaluate and advance generalizability of multi-class fetal brain tissue segmentation algorithms for MRI and it continues to benchmark new algorithms.
Transferring Modality-Aware Pedestrian Attentive Learning for Visible-Infrared Person Re-identification
Visible-infrared person re-identification (VI-ReID) aims to search the same pedestrian of interest across visible and infrared modalities.
Quantifying Zero-shot Coordination Capability with Behavior Preferring Partners
Current evaluation methods for ZSC capability still need to improve in constructing diverse evaluation partners and comprehensively measuring the ZSC capability.
Tackling Cooperative Incompatibility for Zero-Shot Human-AI Coordination
In order to solve cooperative incompatibility in learning and effectively address the problem in the context of ZSC, we introduce the Cooperative Open-ended LEarning (COLE) framework, which formulates open-ended objectives in cooperative games with two players using perspectives of graph theory to evaluate and pinpoint the cooperative capacity of each strategy.
Range of Motion Sensors for Monitoring Recovery of Total Knee Arthroplasty
It is to reduce hospital stay duration and overall medical cost after Total Knee Arthroplasty (TKA) procedures.
ECG Heartbeat classification using deep transfer learning with Convolutional Neural Network and STFT technique
In this paper, we propose a deep transfer learning framework that is aimed to perform classification on a small size training dataset.
Causal Inference in medicine and in health policy, a summary
We will discuss causal inference and ways to discover the cause-effect from observational studies in healthcare domain.
Domestic activities clustering from audio recordings using convolutional capsule autoencoder network
Domestic activities clustering from audio recordings aims at merging audio clips which belong to the same class of domestic activity into a single cluster.
A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits
This study provides a normative theory for how Bayesian causal inference can be implemented in neural circuits.
WOTBoost: Weighted Oversampling Technique in Boosting for imbalanced learning
In this paper, we propose a novel method that combines a Weighted Oversampling Technique and ensemble Boosting method (WOTBoost) to improve the classification accuracy of minority data without sacrificing the accuracy of the majority class.
Large-scale Causal Approaches to Debiasing Post-click Conversion Rate Estimation with Multi-task Learning
In addition, our methods are based on the multi-task learning framework and mitigate the data sparsity issue.
Using Deep Learning Method for Classification: A Proposed Algorithm for the ISIC 2017 Skin Lesion Classification Challenge
The models are built on the source images are using the Caffe [4] framework.
