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Machine Learning
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Domain Adaptation
8,656 papers
Papers per year
2003: 1
2004: 2
2006: 11
2007: 9
2008: 8
2009: 13
2010: 14
2011: 16
2012: 16
2013: 44
2014: 32
2015: 44
2016: 126
2017: 203
2018: 378
2019: 662
2020: 726
2021: 1006
2022: 964
2023: 1217
2024: 1326
2025: 1387
2026: 451
Papers
Speech Enhancement Based on Beamforming and Post-Filtering by Combining Phase Information
INTERSPEECH 2020
Domain Adaptation for Enhancing Speech-Based Depression Detection in Natural Environmental Conditions Using Dilated CNNs
INTERSPEECH 2020
Spectrum Correction: Acoustic Scene Classification with Mismatched Recording Devices
INTERSPEECH 2020
Improving Cross-Lingual Transfer Learning for End-to-End Speech Recognition with Speech Translation
INTERSPEECH 2020
Transliteration Based Data Augmentation for Training Multilingual ASR Acoustic Models in Low Resource Settings
INTERSPEECH 2020
Massively Multilingual ASR: 50 Languages, 1 Model, 1 Billion Parameters
INTERSPEECH 2020
Acoustic Feature Extraction with Interpretable Deep Neural Network for Neurodegenerative Related Disorder Classification
INTERSPEECH 2020
Single-Channel Blind Direct-to-Reverberation Ratio Estimation Using Masking
INTERSPEECH 2020
U-Net Based Direct-Path Dominance Test for Robust Direction-of-Arrival Estimation
INTERSPEECH 2020
Prediction regions through Inverse Regression
JMLR 2020
A First Principles Approach for Data-Efficient System Identification of Spring-Rod Systems via Differentiable Physics Engines
L4DC 2020
NeuralExplorer: State Space Exploration of Closed Loop Control Systems Using Neural Networks
L4DC 2020
Addressing The False Negative Problem of Deep Learning MRI Reconstruction Models by Adversarial Attacks and Robust Training
MIDL 2020
On the limits of cross-domain generalization in automated X-ray prediction
MIDL 2020
3D-RADNet: Extracting labels from DICOM metadata for training general medical domain deep 3D convolution neural networks
MIDL 2020
Understanding Alzheimer disease’s structural connectivity through explainable AI
MIDL 2020
A deep learning approach to segmentation of the developing cortex in fetal brain MRI with minimal manual labeling
MIDL 2020
Adversarial Domain Adaptation for Cell Segmentation
MIDL 2020
Quantifying the Value of Lateral Views in Deep Learning for Chest X-rays
MIDL 2020
Continual Learning for Domain Adaptation in Chest X-ray Classification
MIDL 2020
On Direct Distribution Matching for Adapting Segmentation Networks
MIDL 2020
Domain adaptation model for retinopathy detection from cross-domain OCT images
MIDL 2020
Developing Personalized Models of Blood Pressure Estimation from Wearable Sensors Data Using Minimally-trained Domain Adversarial Neural Networks
MLHC 2020
Phenotyping with Prior Knowledge using Patient Similarity
MLHC 2020
Attention-Based Network for Weak Labels in Neonatal Seizure Detection
MLHC 2020
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