Multi-modal medical image classification using deep residual network and genetic algorithm.

Artificial intelligence (AI) development across the health sector has recently been the most crucial. Early medical information, identification, diagnosis, classification, then analysis, along with viable remedies, are always beneficial developments. Precise and consistent image classification has critical in diagnosing and tactical decisions for healthcare.

Early embryonic death in equines and camelids.

This paper includes the study of early embryonic death (EED), predisposing factors of EED and treatment. EED refers to the fetal mortality which varies in mare and camelids but most probably not later than 50 days of gestation. This duration may be divided into very early mortality, early mortality and late embryonic mortality.

Image classification by addition of spatial information based on histograms of orthogonal vectors.

The Bag-of-Visual-Words (BoVW) model is widely used for image classification, object recognition and image retrieval problems. In BoVW model, the local features are quantized and 2-D image space is represented in the form of order-less histogram of visual words. The image classification performance suffers due to the order-less representation of image.

Content Based Image Retrieval by Using Color Descriptor and Discrete Wavelet Transform.

Due to recent development in technology, the complexity of multimedia is significantly increased and the retrieval of similar multimedia content is a open research problem. Content-Based Image Retrieval (CBIR) is a process that provides a framework for image search and low-level visual features are commonly used to retrieve the images from the image database. The basic requirement in any image retrieval process is to sort the images with a close similarity in term of visually appearance.