Search Results for author:
Found 7 papers, 1 papers with code
Ensemble of Discriminators for Domain Adaptation in Multiple Sound Source 2D Localization
This paper introduces an ensemble of discriminators that improves the accuracy of a domain adaptation technique for the localization of multiple sound sources.
Data-Efficient Framework for Real-world Multiple Sound Source 2D Localization
Moreover, learning for different microphone array layouts makes the task more complicated due to the infinite number of possible layouts.
Learning Multiple Sound Source 2D Localization
In this paper, we propose novel deep learning based algorithms for multiple sound source localization.
Unsupervised Temporal Feature Aggregation for Event Detection in Unstructured Sports Videos
In this paper, we study the case of event detection in sports videos for unstructured environments with arbitrary camera angles.
Unifying Heterogeneous Classifiers with Distillation
In this paper, we study the problem of unifying knowledge from a set of classifiers with different architectures and target classes into a single classifier, given only a generic set of unlabelled data.
Focusing on What is Relevant: Time-Series Learning and Understanding using Attention
This paper is a contribution towards interpretability of the deep learning models in different applications of time-series.
Limiting the Reconstruction Capability of Generative Neural Network using Negative Learning
In the results section we demonstrate the features of the algorithm using MNIST handwritten digit dataset and latter apply the technique to a real-world obstacle detection problem.
