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Real-Time Image Stitching with Convolutional Neural Networks | IEEE Conference Publication | IEEE Xplore
Source: ieeexplore.ieee.org
Article summary:
1. Image stitching algorithms are among the oldest and most widely used in computer vision.
2. Brown and Lowe proposed the first automatic image stitching algorithm, leading to many commercial tools.
3. Many methods have been proposed to improve the results of image stitching, mainly classified into two classes: seam-driven stitching and spatially-varying warping.
Article analysis:
The article is generally reliable and trustworthy as it provides a comprehensive overview of existing image stitching algorithms, their development over time, and potential improvements that can be made. The article also cites relevant sources for its claims, which adds to its credibility. However, there are some areas where the article could be improved upon. For example, it does not explore any counterarguments or present both sides of an argument equally; instead, it focuses solely on the positive aspects of image stitching algorithms without considering any potential drawbacks or risks associated with them. Additionally, the article does not provide any evidence for its claims or discuss any possible biases that may exist in the data used for image stitching algorithms. Finally, there is a lack of discussion about how these algorithms can be applied in real-world scenarios or what implications they may have on society at large.