Exact(11)
It plays an important role in many mid-level and high-level image processing tasks.
Considering high-level image representation, sparse and soft-assignment coding-based approaches are well-known.
The success of CNN is attributed to its superior multi-scale high-level image representations as opposed to hand-engineering low-level features.
Tools have been developed to assist pathologists in image analysis and diagnosis, and they cover low and high-level image processing methods applied to histological images.
The advantage of using RSM over RAP for deriving high-level image abstractions is that parameter estimation is faster and stable.
On top of the basic features, there are few approaches which are used for mid- or high-level image representation [55 58].
Similar(49)
Ultrasound images are corrupted by a multiplicative noise – the speckle – which makes hard high level image analysis.
Unlike the conventional CADx, deep learning techniques have the basic advantage of an automatic exploitation feature as they have the ability to learn mid and high level image representations.
Higher level image analysis may also be employed for photo ranking.
Enhanced features are segregated by size: fine details are prominent in the lower level images while progressively coarser features are prominent in the higher level images.
The resulting contours could be used for high-level PolSAR image analysis, for instance, object recognition.
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