The International Journal of Integrated Care (IJIC) is an online, open-access, peer-reviewed scientific journal that publishes original articles in the field integrated care on a continuous basis.IJIC has Impact Factor 2.913 (2021 JCR, received June 2022)The IJIC 20th Anniversary Issue was published 2021.

We present an approach for object instance detection that uses model recommendation to predict a subset of relevant exemplar models for object detection based on an testing image at runtime. An initial subset of randomly selected exemplar models, the probe set, is first applied to the testing image, and its responses are used, in conjunction with a rating matrix, to predict the responses of all...

Solving real-world classification and recognition problems requires a principled way of modeling the physical phenomena generating the observed data and the uncertainty in it. The uncertainty originates from the fact that many data generation aspects are influenced by non-directly measurable variables or are too complex to model and hence are treated as random fluctuations. For example, in spee...

Clustering is often formulated as the maximum likelihood estimation of a mixture model that explains the data. The EM algorithm widely used to solve the resulting optimization problem is inherently a gradient-descent method and is sensitive to initialization. The resulting solution is a local optimum in the neighborhood of the initial guess. This sensitivity to initialization presents a signifi...

Detecting topics in Twitter streams has been gaining an increasing amount of attention. It can be of great support for communities struck by natural disasters, and could assist companies and political parties understand users’ opinions and needs. Traditional approaches for topic detection focus on representing topics using terms, are negatively affected by length limitation and the lack of cont...

Non-local methods for image denoising and inpainting have gained considerable attention in recent years. This is due to their superior performance in textured images, a known weakness of purely local methods. Local methods on the other hand have shown to be very appropriate for the recovering of geometric structure such as image edges. The synthesis of both types of methods is a trend in curren...

Recovering lost part of an image plays a great role in image processing. Inpainting is a technique that helps in recovering lost pixels from an image. From the existing techniques of Inpainting, Exemplar Inpainting is one of the fast and better techniques that help in restoring the lost part of an image. Exemplar based method chooses a patch similar to the lost patch from the known area to fill...

Saliency detection is an important problem. Researchers in this area mainly focus on advanced models to achieve high performance on benchmark datasets with a large number of labeled images. However, most conventional saliency detection methods only use these benchmark datasets for saliency evaluation. We argue that we can use these valuable labeled data to generate precise saliency results. In ...

Recovering lost part of an image plays a great role in image processing. Inpainting is a technique that helps in recovering lost pixels from an image. From the existing techniques of Inpainting, Exemplar Inpainting is one of the fast and better techniques that help in restoring the lost part of an image. Exemplar based method chooses a patch similar to the lost patch from the known area to fill...

Exemplar-based learning or, equally, nearest neighbour methods have recently gained interest from researchers in a variety of computer science domains because of the prevalence of large amounts of accessible data and storage capacity. In computer vision, these types of technique have been successful in several problems such as scene recognition, shape matching, image parsing, character recognit...