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1.
PLoS One ; 15(10): e0237570, 2020.
Article in English | MEDLINE | ID: mdl-33044975

ABSTRACT

Photo-identification (photo-id) is a method used in field studies by biologists to monitor animals according to their density, movement patterns and behavior, with the aim of predicting and preventing ecological risks. However, these methods can introduce subjectivity when manually classifying an individual animal, creating uncertainty or inaccuracy in the data as a result of the human criteria involved. One of the main objectives in photo-id is to implement an automated mechanism that is free of biases, portable, and easy to use. The main aim of this work is to develop an autonomous and portable photo-id system through the optimization of image classification algorithms that have high statistical dependence, with the goal of classifying dorsal fin images of the blue whale through offline information processing on a mobile platform. The new proposed methodology is based on the Scale Invariant Feature Transform (SIFT) that, in conjunction with statistical discriminators such as the variance and the standard deviation, fits the extracted data and selects the closest pixels that comprise the edges of the dorsal fin of the blue whale. In this way, we ensure the elimination of the most common external factors that could affect the quality of the image, thus avoiding the elimination of relevant sections of the dorsal fin. The photo-id method presented in this work has been developed using blue whale images collected off the coast of Baja California Sur. The results shown have qualitatively and quantitatively validated the method in terms of its sensitivity, specificity and accuracy on the Jetson Tegra TK1 mobile platform. The solution optimizes classic SIFT, balancing the results obtained with the computational cost, provides a more economical form of processing and obtains a portable system that could be beneficial for field studies through mobile platforms, making it available to scientists, government and the general public.


Subject(s)
Animal Fins/anatomy & histology , Balaenoptera/anatomy & histology , Mobile Applications , Photography/methods , Algorithms , Animals , Databases, Factual , Image Processing, Computer-Assisted/methods , Image Processing, Computer-Assisted/statistics & numerical data , Pattern Recognition, Automated/methods , Pattern Recognition, Automated/statistics & numerical data , Photography/statistics & numerical data
2.
Opt Express ; 16(20): 16166-71, 2008 Sep 29.
Article in English | MEDLINE | ID: mdl-18825254

ABSTRACT

We demonstrate simultaneous NRZ-to-RZ conversion for 16 DWDM channels, using a single SOA and a subsequent delay interferometer (DI) acting as a comb-like filter to control the obtained pulse-width for all of the channels. The SOA is operated in deep saturation, resulting in weak cross gain modulation and cross phase modulation induced crosstalk between different NRZ channels. By adjusting the detuning between the peaks in the DI spectrum and each corresponding carrier, good quality RZ signals with different duty cycles can be achieved. Bit-error-rate measurements show negative power penalties for the obtained RZ signals with different duty cycles. Significant timing jitter reductions for all channels show the good regenerative performance of the proposed converter.

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