The proposed Coordinate-Aware Feature Excitation (CAFE) module and Position-Aware Upsampling (Pos-Up) module both adhere to ...
Abstract: Change detection (CD) is a hot research topic in the field of remote sensing (RS), and using convolutional neural networks (CNNs) and Transformers for CD tasks is the mainstream option ...
Abstract: Although recent deep-learning-based speech enhancement (SE) methods significantly outperform traditional approaches, their computational demands often scale proportionally with their ...
Abstract: Dysarthric speech, common among people with hearing impairment, severely reduces intelligibility and limits daily communication. We proposed a Fuzzy Gated Convolutional Neural Network ...
This study presents a valuable advance in reconstructing naturalistic speech from intracranial ECoG data using a dual-pathway model. The evidence supporting the claims of the authors is solid, ...
Abstract: Convolutional neural networks (CNNs) have emerged as a preferred approach for medical image analysis. The dimensionality of images is a principal factor in CNN models, as they are designed ...
CNN is on the brink of having yet another new owner and, as of this moment, it's anyone's guess as to who it'll be. In October, CNN's parent company, Warner Bros. Discovery announced it was putting ...
Abstract: In the area of affective computing, speech has been identified as a promising biomarker for assessing depression and attention deficit hyperactivity disorder (ADHD). These disorders manifest ...