Sentence examples for solving image from inspiring English sources

Recently, sparse representation based methods have proven to be successful towards solving image restoration problems.

Partial differential equations (PDEs) have emerged as a useful tool for recovering structures when solving image inpainting problems.

The application of the proposed model is demonstrated by solving image fusion problems in a multi-resolution framework.

Even when restricted to images in specific domains such as music score recognition, solving image processing problems usually requires the design of customized algorithms.

Unfortunately, algorithms capable of solving image based CAPTCHAs can be used to create spam accounts and design malicious denial of service (DoS) attacks, causing financial and social damage.

The dynamics of cellular neural networks has been deeply investigated due to its applicability in solving image processing, signal processing and pattern recognition problems [1, 2].

In this paper, an effective technique is introduced called Wavelet-Modified Single Layer Linear Forward Only Counter Propagation Network (MSLLFOCPN) technique to solve image compression.

On the other hand, since Zadeh [37] introduced the fuzzy set (FS) theory, it has been used to solve image segmentation problems regarding vague images.

The success in implementing many-to-many teleradiology applications also depends on the ability of the service provider not only to solve image reading but also to participate in the planning of procedures to find the best diagnostic approach, to discuss the reports in multidisciplinary meetings and to facilitate clinical communication.

In the future, we will extend the proposed model to solve images with more than two images.

The proposed method is evaluated by solving the image retrieval task using challenging image datasets, and is compared with seven state-of-the-art algorithms in the field.