Short-term monitoring, usually over a 3-month period, is used to establish a clinical judgment about abnormal melanocytic tumors that do not exhibit clear SCM features [ 49, 51].
Also, the SCM preserves the interesting features of the original method: easiness of implementation, low memory requirements, small cost in terms of the CPU time.
The subsurface chlorophyll maximum (SCM) is a prominent biological feature in stratified waters, and may contribute substantial biomass to the water column.
Most of the previous studies have reported that the following sonographic features of the affected SCM in patients with CMT: echogenicity; texture; motility; softness; and the transverse and longitudinal extent of the involvement [ 11- 14].
However, statistically significant differences existed between the two groups with respect to other ultrasound features, including lesion boundaries, SCM thicknesses, echo signals from the lesion, color Doppler flow imaging, and clinical characteristics, such as the presence of palpable neck masses, neck activity, and treatment methods (P < 0.05) (Table 2).
This study proposes a conceptual framework featuring the ERP benefits and SCM competencies, and examines the impacts of the former on the latter.
In order to learn the visual features, we train a convolutional neural network (CNN) model to obtain the sum convolutional map (SCM) by using a pooling operation across all the feature maps in deep layers.
Table 6 The feature dimensionality of different layers Layers SCM dimensionality Features dimensionality conv3 13×13 169 conv4 13×13 169 conv5 13×13 169 Layers Neurons number Features dimensionality fc6 4096 4096 fc7 4096 4096.
Suppose the size of each feature map is H×W and the SCM is also with the size of H×W.
For the convolutional layers, the feature dimensionality is equal to that of SCM.
