finding interpretations poses a significant challenge. In this paper we present an explainable deep one-class classification method,Fully Convolutional Data Description(FCDD), where the mapped samples are thems
Despite interesting results, the main focus of the present study was to investigate how the CNN achieved this classification. The explainable Artificial Intelligence (xAI) technique of Gradient-weighted Class Activation Mapping (Grad-CAM) was applied. xAI made it possible to visually identify the ...
在《Deep Learning with Python》中就有简单的实现例子: 不过这个方法的一个问题是对于不同class的activation map的重合度可能很高,导致无法分辨决定性的因素到底是什么。所以后续提出了一些操作网络结构的想法,例如在Xing et al., 2020中,把决策树的结构加到网络中,让预测更有可解释性。在Chen et al., 2020中...
Kotios D, Makridis G, Fatouros G, Kyriazis D (2022) Deep learning enhancing banking services: a hybrid transaction classification and cash flow prediction approach. J. Big Data 9(1):100 Article Google Scholar La Gatta V, Moscato V, Postiglione M, Sperli G (2021a) CASTLE: Cluster-aided...
one or several features were dominant (Supplementary Fig.S4d). The feature importance scores measure the joint effect of multiple factors and help guide cancer gene classification (Fig.4b, Source Data file). Many cancer-driven genes (class-5) were as reported to be dominated by genetic mutation...
Classification loss Define vector \({{{\bf{b}}}_{i}\) with its \(k\) th element be one and the other \(K-1\) elements be zero, where \(k\) is the observed class label of cell \(i\). Let gi = nk(i)/n where nk (k = 1,...,K) is the number of cells with cell ...
However, categorical emotion classification has not been fully explored to classify a text sentence into discrete emotion categories. The TER system proposed in this work performs multi-class text emotion recognition and classifies a given text input into discrete emotion categories. Lately, Deep neural...
(2022) Feature Relevance Evaluation using Grad-CAM, LIME and SHAP for Deep Learning SAR Data Classification. In 2022 23rd International Radar Symposium (IRS), pp. 457–462. [72] Park, N.-W. (2015) Using maximum entropy modeling for landslide susceptibility mapping with multiple ...
importquantusfromquantus.helpers.model.modelsimportLeNetimporttorchimporttorchvisionfromtorchvisionimporttransforms# Enable GPU.device=torch.device("cuda:0"iftorch.cuda.is_available()else"cpu")# Load a pre-trained LeNet classification model (architecture at quantus/helpers/models).model=LeNet()ifdevice....
the output of the first-stage classifier could be obtained either in binary format (class labels) or numeric format (probability associated with each class). The classification scheme of the second classifier is another hyper-parameter that its effect is investigated on the overall performance of\te...