They exhibited strong absorption below 500 nm with the threshold edges around 700 nm.
Using the bistochastic filter with an edge weight threshold, edges were removed exponentially quickly even when the edge weight threshold was only slightly above zero (see Figure S5 for more detail).
For pairs with Jaccard indices greater than a given threshold, edges are drawn connecting the respective nodes where the thickness of each edge is proportional to the Jaccard index (Jaccard, 1901; Merico et al., 2010).
For a set of λ ∈ Λ, the probability of each edge in the inferred network is (25) ∏ (i, j ) = max λ ∈ Λ ∏ λ (i, j ) The final network topology can be obtained by setting a threshold, edges with probabilities or scores less than which are considered nonexistent.
However, on the high-threshold edge of the stability region ( θ = 30 ), where replay eventually dies out, most failures are caused by small-to-big pattern transitions ( ∼ 80%% of points above the red line).
On the low-threshold edge of the stability region, which is prone to over-excitement ( θ = 25, cf. Fig. 5), a big-to-small pattern transition is as likely to lead to a failure in sequence replay as a small-to-big transition.
One of the mostly used is provided by Gonzalez and Woods [1], which categorizes the techniques in three generic classes: thresholding, edge detection, and region growing.
In that work, 4 main blocks are detailed: pre-processing methods (image enhancement and de-noising), space-domain recognition algorithms (thresholding, edge detection, and seed growing), frequency-domain recognition algorithms (Wavelet transform), and supervised learning methods.
As a result, these images are difficult to process and segment, and consequently conventional methods such as thresholding, edge detection, texture analysis, and others fail to give interesting results.
Table 3 Comparison of defect detection systems Paper Method Type of defects Sample size Features Detection accuracy Resolution (across × along) Speed of steel object (m/s) Real-time operation Remark Detection Classification [67] - slab Gabor filter, two-level thresholding, edge pair detection SVM Scratch 7,110 cases 7 histogram, gradient 94.08 Classification w.r.t.
