One of the fundamental problems in Content-Based Image Retrieval (CBIR) has been the gap between low-level visual features and high-level semantic concepts. To narrow down this gap...
We present a system capable of interpreting speech commands given by a radiologist in order to accurately diagnose a set of findings and impressions for medical images, such as M...
Tim Weninger, Daniel Greene, Jack Hart, William H....
This paper presents a Bayesian Network model for ContentBased Image Retrieval (CBIR). In the explanation and test of this work, only two images features (semantic evidences) are i...
Paulo S. Rodrigues, Gilson A. Giraldi, Ade A. Arau...
This paper presents a detailed comparative study of 4 rotation invariant texture analysis methods. Human subjects are included as a benchmark for the computational methods. Experi...
Traditional image retrieval techniques search for images without considering the query context. When they are applied to applications like annotating text with images, the results...