Export 7 results:
[ Author(Desc)] Title Type Year
Filters: First Letter Of Last Name is L  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
Lee-Leon A., Yuen C., Herremans D..  2019.  Doppler Invariant Demodulation for Shallow Water Acoustic Communications Using Deep Belief Networks. 16th IEEE Asia Pacific Wireless Communications Symposium (APWCS). PDF icon 1909.02850.pdf (790.54 KB)
Lee-Leon A., Yuen C., Herremans D..  2021.  Underwater Acoustic Communication Receiver Using Deep Belief Network. IEEE Transactions on Communications. :1-1.PDF icon 2102.13397.pdf (12.87 MB)
Lee-Leon A., Yuen C., Herremans D..  2019.  A Hybrid Fuzzy Logic-Neural Network Approach For Multi-path Separation Of Underwater Acoustic Signals. 89th IEEE Vehicular Technology Conference. PDF icon fuzzy logic.pdf (1.66 MB)
Lin K.W.E., BT B, Koh E., Lui S., Herremans D..  2018.  Singing Voice Separation Using a Deep Convolutional Neural Network Trained by Ideal Binary Mask and Cross Entropy. Neural Computing and Applications. PDF icon main.pdf (2.59 MB)
Luo Y.J., Cheuk K.W., Nakano T., Goto M., Herremans D..  2020.  Unsupervised disentanglement of pitch and timbre for isolated musical instrument sounds. Proceedings of the International Society of Music Information Retrieval (ISMIR).
Luo Y.J., Hsu C.-C., Agres K., Herremans D..  2020.  Singing voice conversion with disentangled representations of singer and vocal technique using variational autoencoders. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). PDF icon 1912.02613.pdf (2.9 MB)
Luo Y.J., Agres K., Herremans D..  2019.  Learning Disentangled Representations of Timbre and Pitch for Musical Instrument Sounds Using Gaussian Mixture Variational Autoencoders. ISMIR. PDF icon jyun-ismir.pdf (5.62 MB)