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Automatic matching of poor quality latent fingerprints to rolled/slap fingerprints using an Automated Fingerprint Identification System (AFIS) is still far from satisfactory. Therefore, it is a common practice to have a latent examiner mark features on a latent for improving the hit rate of the AFIS. We propose a synergistic crowd powered latent identification framework where multiple latent examiners...
One of the major goals of most national, international and non-governmental health organizations is to eradicate the occurrence of vaccine-preventable childhood diseases (e.g., polio). Without a high vaccination coverage in a country or a geographical region, these deadly diseases take a heavy toll on children. Therefore, it is important for an effective immunization program to keep track of children...
Latent fingerprints serve as an important source of forensic evidence in a court of law. Automatic matching of latent fingerprints to rolled/plain (exemplar) fingerprints with high accuracy is quite vital for such applications. However, latent impressions are typically of poor quality with complex background noise which makes feature extraction and matching of latents a significantly challenging problem...
Latent fingerprints are of critical value in forensic science because they serve as an important source of evidence in a court of law. Automatic matching of latent fingerprints to rolled/plain (exemplar) fingerprints with high accuracy is quite vital for such applications. However, due to poor latent image quality in general, latent fingerprint matching accuracy is far from satisfactory. In this research,...
With the advancements in iris matching and growing number of system deployments, a wide variety of iris cameras are now being manufactured. These cameras differ in manufacturing technology, including image acquisition spectrum and illumination settings. For large scale applications (e.g. UID system in India) where cameras from several vendors are likely to be used for iris enrollment and authentication,...
Iris recognition has been used mainly to recognize cooperative subjects in controlled environments. With the continuing improvements in iris matching performance and reduction in the cost of iris scanners, the technology will witness broader applications and may be confronted with newer challenges. In this research, we have investigated one such challenge, namely matching iris images captured before...
In this paper, we utilize the frequency domain representation of electrocardiogram (ECG) signals for the training of auto-associative neural networks. Since ECG signals, when taken over shorter duration, are almost periodic; so they can be considered to be short term stationary. We use the harmonics of individual ECG beats, as input to train the auto-associative neural network (AANN). For the purpose...
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