Hybrid transformer-CNN networks using superpixel segmentation for remote sensing building change detection
Sign Up to like & getrecommendations! Published in 2023 at "International Journal of Remote Sensing"
DOI: 10.1080/01431161.2023.2208711
Abstract: ABSTRACT Convolution in convolutional neural network(CNN) essentially uses a filter (kernel) with shared parameters to achieve feature extraction by computing the weighted sum of the centre pixel and adjacent pixels. The transformer divides the input… read more here.
Keywords: hybrid transformer; remote sensing; transformer cnn; cnn ... See more keywords
TCSR: Lightweight Transformer and CNN Interaction Network for Image Super-Resolution
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3476369
Abstract: Convolutional neural network (CNN) has achieved impressive success in lightweight image super-resolution (SR) methods, yet the nature of its local operations constrains the SR performance. Recent Transformer has attracted increasing attention in lightweight SR methods… read more here.
Keywords: cnn; lightweight transformer; transformer cnn; network ... See more keywords
Transformer-CNN Interactive Learned Image Compression for Resource-Deficient Industrial Visual Information Communication
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Sensors Journal"
DOI: 10.1109/jsen.2025.3569520
Abstract: The application of image compression in industrial information systems has significantly enhanced data processing efficiency and emerged as a supportive technique for realizing Industry 4.0. The learned image compression (LIC) approach has rapidly surpassed classical… read more here.
Keywords: cnn interactive; image; learned image; transformer cnn ... See more keywords
Transformer and CNN Hybrid Deep Neural Network for Semantic Segmentation of Very-high-resolution Remote Sensing Imagery
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3144894
Abstract: This paper presents a transformer and CNN hybrid deep neural network for semantic segmentation of very-high-resolution remote sensing imagery. The model follows an encoder-decoder structure. The encoder module uses a new universal backbone swin transformer… read more here.
Keywords: network; cnn hybrid; remote sensing; transformer cnn ... See more keywords
Transformer-CNN: Swiss knife for QSAR modeling and interpretation
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Cheminformatics"
DOI: 10.1186/s13321-020-00423-w
Abstract: We present SMILES-embeddings derived from the internal encoder state of a Transformer [ 1 ] model trained to canonize SMILES as a Seq2Seq problem. Using a CharNN [ 2 ] architecture upon the embeddings results… read more here.
Keywords: cnn swiss; qsar; swiss knife; transformer cnn ... See more keywords
Be aware of overfitting by hyperparameter optimization!
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Cheminformatics"
DOI: 10.1186/s13321-024-00934-w
Abstract: Hyperparameter optimization is very frequently employed in machine learning. However, an optimization of a large space of parameters could result in overfitting of models. In recent studies on solubility prediction the authors collected seven thermodynamic… read more here.
Keywords: hyperparameter optimization; overfitting hyperparameter; transformer cnn; aware overfitting ... See more keywords
A Novel Transformer-CNN Approach for Predicting Soil Properties from LUCAS Vis-NIR Spectral Data
Sign Up to like & getrecommendations! Published in 2024 at "Agronomy"
DOI: 10.3390/agronomy14091998
Abstract: Soil, a non-renewable resource, requires continuous monitoring to prevent degradation and support sustainable agriculture. Visible-near-infrared (Vis-NIR) spectroscopy is a rapid and cost-effective method for predicting soil properties. While traditional machine learning methods are commonly used… read more here.
Keywords: predicting soil; transformer cnn; soil; vis nir ... See more keywords
A Hybrid Transformer-CNN Model for Interpolating Meteorological Data on the Tibetan Plateau
Sign Up to like & getrecommendations! Published in 2025 at "Atmosphere"
DOI: 10.3390/atmos16040431
Abstract: High-quality observational data play a crucial role in deepening the investigation of the Tibetan Plateau’s influence on the Asian climate. This study employs eight machine learning models (support vector regression (SVR), k-nearest neighbors (KNN), extreme… read more here.
Keywords: tibetan plateau; transformer; cnn model; transformer cnn ... See more keywords
P300 Spatiotemporal Prior-Based Transformer-CNN for Auxiliary Diagnosis of PTSD
Sign Up to like & getrecommendations! Published in 2025 at "Brain Sciences"
DOI: 10.3390/brainsci15101124
Abstract: Objectives: To address the challenges of subjectivity, misdiagnosis and underdiagnosis in post-traumatic stress disorder (PTSD), this study proposes an objective auxiliary diagnostic method based on P300 signals. Existing studies largely rely on conventional P300 features,… read more here.
Keywords: cnn; transformer cnn; ptsd; auxiliary diagnosis ... See more keywords