… Therefore, in this work, we propose a hybrid deep learning model called DeepTumorNet
for three … We propose a hybrid deep learning model for three types of BT classification (pituitary, …

… methods and different deep learning models. We propose a new hybrid deep learning model
that uses different representations of data and different deep learning model to analyze a …

… deep learning (DL). By default, DL consists of a single architecture and is termed solo deep
learning … are fused, the result is termed a hybrid deep learning (HDL) model. The use of HDL …

… We also showed that the end-to-end hybrid deep learning architecture is more effective
than the traditional machine learning analysis flow: feature extraction, sampling, …

… hybrid CNN-based architecture to classify three brain tumour types through MRI images. The
method suggested in this paper uses hybrid deep learning classification … classification. The …

… is to propose a hybrid deep network framework to improve the classification accuracy of the
… a new hybrid deep learning framework by combining CNN and LSTM to learn the spatial and …

… This study proposes a multilayer hybrid deep-learning system (MHS) to automatically sort …
the manually labelled items, achieving overall classification accuracy higher than 90% under …

… In this paper, an automated deep learning-based method is proposed to distinguish …
classification system using a hybrid of two Convolution Neural Network (CNN) and transfer learning …

… Section 5 describes merits of hybrid CNN-ELM model. We also analyze the time complexity
of hybrid classification in Section 6. The experiments and results are illustrated in Section 7. …

… video classification performance. We introduce a novel hybrid deep learning framework that
… The hybrid deep learning framework is able to exploit a comprehensive set of multimodal …