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20172024
most citedImplicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation

52 citations · 124 across the 21 of their papers we have counts for

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Showing 2019Show all

8 papers · 1 filter

cs.LG2019

Multimodal Deep Learning for Mental Disorders Prediction from Audio Speech Samples

Habibeh Naderi, Behrouz Haji Soleimani, Stan Matwin

Key features of mental illnesses are reflected in speech. Our research focuses on designing a multimodal deep learning structure that automatically extracts salient features from r…

cs.LG2019

Unsupervised Behavior Change Detection in Multidimensional Data Streams for Maritime Traffic Monitoring

Lucas May Petry, Amilcar Soares, Vania Bogorny +1

The worldwide growth of maritime traffic and the development of the Automatic Identification System (AIS) has led to advances in monitoring systems for preventing vessel accidents…

cs.SD2019

Marine Mammal Species Classification using Convolutional Neural Networks and a Novel Acoustic Representation

Mark Thomas, Bruce Martin, Katie Kowarski +2

Research into automated systems for detecting and classifying marine mammals in acoustic recordings is expanding internationally due to the necessity to analyze large collections o…

cs.LG20193 cited

Efficient Neural Task Adaptation by Maximum Entropy Initialization

Farshid Varno, Behrouz Haji Soleimani, Marzie Saghayi +2

Transferring knowledge from one neural network to another has been shown to be helpful for learning tasks with few training examples. Prevailing fine-tuning methods could potential…

cs.CL201920 cited

When a Tweet is Actually Sexist. A more Comprehensive Classification of Different Online Harassment Categories and The Challenges in NLP

Sima Sharifirad, Stan Matwin

Sexism is very common in social media and makes the boundaries of freedom tighter for feminist and female users. There is still no comprehensive classification of sexism attracting…

eess.AS20199 cited

Recurrent Neural Networks with Stochastic Layers for Acoustic Novelty Detection

Duong Nguyen, Oliver S. Kirsebom, Fábio Frazão +2

In this paper, we adapt Recurrent Neural Networks with Stochastic Layers, which are the state-of-the-art for generating text, music and speech, to the problem of acoustic novelty d…