We start this chapter by examining a few of the most widely used image processing algorithms, then move on to machine learning implementation in image processing. The chapter at a glance is as followsdoi:10.1007/978-1-4842-4149-3_5Himanshu Singh...
either based on intuition, domain expertise, or hypothesis. These features are then extracted from images, either manually or using image-processing algorithms. Stage B: this feature
Human taste perception is associated with the papillae on the tongue as they contain a large proportion of chemoreceptors for basic tastes and other chemosensation. Especially the density of fungiform papillae (FP) is considered as an index for responsiv
It is not easy to accomplish processing massive amounts of data manually. Here’s where Artificial Intelligence and machine learning algorithms become very helpful. The use of ML and AI to boost the data processing speed and generate quality image result. But of course, in order to get high-...
Digital image processing is the use of algorithms to make computers analyze the content of digital images. Here are 20,072 public repositories matching this topic... Language:All Sort:Most stars Open Source Computer Vision Library opencvc-plus-pluscomputer-visiondeep-learningimage-processing ...
Future scope:Further calibration-validation procedures are needed for other wheat cultivars to test MK-SVR models. Additionally, other machine learning algorithms such as XY-fusion network, Random Forest, Boosting or Bagging can also be tested for obtaining better results for the prediction of crop ...
suitable for processing large image sets, and it could be used for quantifying various protein expressions (Jiao et al.2019). Kobayashi et al. illustrated that combining bright-field microscopy with machine learning algorithms was useful in the identification of highly accurate drug-induced morphologica...
However, the three advanced non-parametric machine learning (ML) models, namely, k-nearest neighbor (kNN), random forest (RF), and support vector machine (SVM), resulted in high accuracies with RF outperforming the others. It is recommended that the handcrafted simple image processing ...
Model-based deep transfer learning is arguably the most frequently used method. However, very little work has been devoted to enhancing deep transfer learning by focusing on the influence of...关键词: Computer Science - Machine Learning DOI: 10.48550/arXiv.1708.07747 被引量: 411 ...
The common and recent used algorithms in this category are teaching–learning-based optimization (TLBO)28, and the heap-based optimizer (HBO)29. With respect to MTH in image processing, it is possible to use thresholding approaches such as the Otsu or Kapur method30 as the objective function....