Evaluating deep learning architectures for speech emotion recognition HM Fayek, M Lech, L Cavedon Neural Networks 92, 60-68, 2017 | 595 | 2017 |
Detection of clinical depression in adolescents’ speech during family interactions LSA Low, NC Maddage, M Lech, LB Sheeber, NB Allen IEEE Transactions on Biomedical Engineering 58 (3), 574-586, 2010 | 278 | 2010 |
Hand-gesture recognition using two-antenna Doppler radar with deep convolutional neural networks S Skaria, A Al-Hourani, M Lech, RJ Evans IEEE Sensors Journal 19 (8), 3041-3048, 2019 | 242 | 2019 |
Towards real-time speech emotion recognition using deep neural networks HM Fayek, M Lech, L Cavedon 2015 9th international conference on signal processing and communication …, 2015 | 133 | 2015 |
Loudness perception and frequency discrimination in subjects with steeply sloping hearing loss: possible correlates of neural plasticity HJ McDermott, M Lech, MS Kornblum, DRF Irvine The Journal of the Acoustical Society of America 104 (4), 2314-2325, 1998 | 129 | 1998 |
Real-time speech emotion recognition using a pre-trained image classification network: Effects of bandwidth reduction and companding M Lech, M Stolar, C Best, R Bolia Frontiers in Computer Science 2, 14, 2020 | 117 | 2020 |
Two-stage deep learning approach to the classification of fine-art paintings C Sandoval, E Pirogova, M Lech IEEE Access 7, 41770-41781, 2019 | 111 | 2019 |
Influence of acoustic low-level descriptors in the detection of clinical depression in adolescents LSA Low, NC Maddage, M Lech, L Sheeber, N Allen 2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010 | 108 | 2010 |
Multichannel weighted speech classification system for prediction of major depression in adolescents KEB Ooi, M Lech, NB Allen IEEE Transactions on Biomedical Engineering 60 (2), 497-506, 2012 | 105 | 2012 |
Study of empirical mode decomposition and spectral analysis for stress and emotion classification in natural speech L He, M Lech, NC Maddage, NB Allen Biomedical Signal Processing and Control 6 (2), 139-146, 2011 | 98 | 2011 |
Using grayscale images for object recognition with convolutional-recursive neural network HM Bui, M Lech, E Cheng, K Neville, IS Burnett 2016 IEEE Sixth International Conference on Communications and Electronics …, 2016 | 89 | 2016 |
Real time speech emotion recognition using RGB image classification and transfer learning MN Stolar, M Lech, RS Bolia, M Skinner 2017 11th International Conference on Signal Processing and Communication …, 2017 | 83 | 2017 |
Modeling subjectiveness in emotion recognition with deep neural networks: Ensembles vs soft labels HM Fayek, M Lech, L Cavedon 2016 international joint conference on neural networks (IJCNN), 566-570, 2016 | 81 | 2016 |
Automated Screening for Alzheimer's Dementia Through Spontaneous Speech. MSS Syed, ZS Syed, M Lech, E Pirogova Interspeech 2020, 2222-6, 2020 | 76 | 2020 |
Object recognition using deep convolutional features transformed by a recursive network structure HM Bui, M Lech, E Cheng, K Neville, IS Burnett IEEE Access 4, 10059-10066, 2016 | 76 | 2016 |
Facial expression recognition using neural networks and log-gabor filters SM Lajevardi, M Lech 2008 Digital Image Computing: Techniques and Applications, 77-83, 2008 | 62 | 2008 |
Facial expression recognition from image sequences using optimized feature selection SM Lajevardi, M Lech 2008 23rd international conference image and vision computing New Zealand, 1-6, 2008 | 59 | 2008 |
Stress detection using speech spectrograms and sigma-pi neuron units L He, M Lech, NC Maddage, N Allen 2009 Fifth International Conference on Natural Computation 2, 260-264, 2009 | 53 | 2009 |
Averaged Gabor filter features for facial expression recognition SM Lajevardi, M Lech 2008 Digital Image Computing: Techniques and Applications, 71-76, 2008 | 52 | 2008 |
Automatic evaluation of hypernasality and consonant misarticulation in cleft palate speech L He, J Zhang, Q Liu, H Yin, M Lech IEEE Signal Processing Letters 21 (10), 1298-1301, 2014 | 43 | 2014 |