The research field concerned with the digital restoration of degraded written heritage lacks a quantitative metric for evaluating its results, which prevents comparison relevant methods on large datasets. Thus, we introduce novel dataset Subjective Assessments Legibility in Ancient Manuscript Images (SALAMI) to serve as ground truth development evaluation metrics text restoration. This consists...

In this study, the performance of popular convolution architectures against an imbalanced dataset is analyzed in detail with a multi-classing medical image processing application. Our selection for dermoscopic images large-scale and consisting 10,015 colored lesion belonging to 7 different skin diseases, was used as benchmark. Images without pathological testing are labeled by specialist dermat...

William C. Chueh, Anthony H. McDaniel, Michael E. Grass, Yong Hao, Naila Jabeen, Zhi Liu, Sossina M. Haile, Kevin F. McCarty, Hendrik Bluhm, Farid El Gabaly Sandia National Laboratories, Livermore, California 94551, United States Materials Science, California Institute of Technology, Pasadena, California 91125, United States Advanced Light Source, Lawrence Berkley National Laboratory, Berkeley,...

This paper proposes an efficient approach for managing the security in WSN. Our approach uses the notion of public key cryptography in which two different keys are used for encryption and decryption of data. Our analysis and performance evaluations show that, our approach is viable with the specifications of today's Berkley/Crossbow MICA2dot motes.

Luis Sambo, Margaret Chan, Steve Davis, Anthony Lake, Seth Berkley, Cyrus Poonawalla, and Christopher J. Elias World Health Organization, Regional Office for Africa, Brazzaville, Republic of Congo; World Health Organization, Geneva, Switzerland; PATH, Seattle, Washington; United Nations Children’s Fund, New York, New York; Gavi, Geneva, Switzerland; Serum Institute of India Ltd, Pune; and Bill ...

The work presented in this paper is unique in several points with respect to prior work. We report results from the largest experimental dataset to date, in terms of number of persons or number of images or number of algorithms considered. Ours is the first work to consider ICP-based recognition on a large dataset with 404 subjects. Also because we use a large experimental dataset, we are able ...