Ashwin: Plug-and-Play System for Machine-Human Image Annotation

Fuzzy Neighbor Voting for Automatic Image Annotation

With quick development of digital images and the availability of imaging tools, massive amounts of images are created. Therefore, efficient management and suitable retrieval, especially by computers, is one of themost challenging fields in image processing. Automatic image annotation (AIA) or refers to attaching words, keywords or comments to an image or to a selected part of it. In this paper,...

Tags Re-ranking Using Multi-level Features in Automatic Image Annotation

Automatic image annotation is a process in which computer systems automatically assign the textual tags related with visual content to a query image. In most cases, inappropriate tags generated by the users as well as the images without any tags among the challenges available in this field have a negative effect on the query's result. In this paper, a new method is presented for automatic image...

A CAD System Framework for the Automatic Diagnosis and Annotation of Histological and Bone Marrow Images

Due to ever increasing of medical images data in the world’s medical centers and recent developments in hardware and technology of medical imaging, necessity of medical data software analysis is needed. Equipping medical science with intelligent tools in diagnosis and treatment of illnesses has resulted in reduction of physicians’ errors and physical and financial damages. In this article we pr...

Improving Patient Safety With X-Ray and Anesthesia Machine Ventilator Synchronization: A Medical Device Interoperability Case Study

When a x-ray image is needed during surgery, clinicians may stop the anesthesia machine ventilator while the exposure is made. If the ventilator is not restarted promptly, the patient may experience severe complications. This paper explores the interconnection of a ventilator and simulated x-ray into a prototype plug-and-play medical device system. This work assists ongoing interoperability fra...

Semantic-Based Image Retrial in the VQ Compressed Domain using Image Annotation Statistical Models