IEEE transactions on visualization and computer graphics
Dec 24, 2021
Existing research on making sense of deep neural networks often focuses on neuron-level interpretation, which may not adequately capture the bigger picture of how concepts are collectively encoded by multiple neurons. We present Neurocartography, an ...
IEEE transactions on visualization and computer graphics
Dec 24, 2021
The interpretation of deep neural networks (DNNs) has become a key topic as more and more people apply them to solve various problems and making critical decisions. Concept-based explanations have recently become a popular approach for post-hoc inter...
This work outlines an approach for localizing anomalies in nuclear reactor cores during their steady state operation, employing deep, one-dimensional, convolutional neural networks. Anomalies are characterized by the application of perturbation diagn...
Parkinson's disease (PD) is one of the most common neurodegenerative diseases, and early diagnosis is crucial to delay disease progression. The diagnosis of early PD has always been a difficult clinical problem due to the lack of reliable biomarkers....
This study was to explore the adoption effect of magnetic resonance imaging (MRI) image features based on back propagation neural network (BPNN) in evaluating the curative effect of Chengqi Decoction (CD) for intestinal obstruction (ileus), so as to ...
To not only optimize the hyper-parameters of the classification layer of dense convolutional network with 201 convolutional layers (DenseNet-201) but also use data augmentation processes could enhance the performance of DenseNet-201, and DenseNet-201...
Neural networks : the official journal of the International Neural Network Society
Dec 23, 2021
Neural network architectures are high-performing variable models that can solve many learning tasks. Designing architectures manually require substantial time and also prior knowledge and expertise to develop a high-accuracy model. Most of the archit...
Angewandte Chemie (International ed. in English)
Dec 23, 2021
Manipulation of cell-cell interactions via cell surface engineering has potential biomedical applications in tissue engineering and cell therapy. However, manipulation of the comprehensive and multiple intercellular interactions remains a challenge a...
AIM: The purpose of this study was to automatically extract myocardial regions from transaxial single-photon emission computed tomography (SPECT) images using deep learning to reduce the effects of extracardiac activity, which has been problematic in...
Deep learning (DL) is being successfully applied across multiple domains, yet these models learn in a most artificial way: they require large quantities of labeled data to grasp even simple concepts. Thus, the main bottleneck is often access to super...
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