SEALNET: Facial recognition software for ecological studies of harbor seals

Methods for long-term monitoring of coastal species such as harbor seals, are often costly, time-consuming, and highly invasive, underscoring the need for improved techniques for data collection and analysis. Here, we propose the use of automated facial recognition technology for identification of individual seals and demonstrate its utility in ecological and population studies. We created a software package, SealNet, that automates photo identification of seals, using a graphical user interface (GUI) software to identify, align and chip seal faces from photographs and a deep convolutional neural network (CNN) suitable for small datasets (e.g., 100 seals with five photos per seal). We piloted the SealNet technology with a population of harbor seals located within Casco Bay on the coast of Maine, USA. Across two-years of sampling, 2019 and 2020, at seven haul-out sites in Middle Bay, we processed 1529 images representing 408 individual seals and achieved 88% (93%) rank-1 accuracy in closed set (open set) seal identification. We identified four seals that were photographed in both years at neighboring haul-out sites, suggesting that some harbor seals exhibit site fidelity within local bays across years, and that there may be evidence of spatial connectivity among haul-out sites. Using capture-mark-recapture (CMR) calculations, we obtained a rough preliminary population estimate of 4386 seals in the Middle Bay area. SealNet software outperformed a similar face recognition method developed for primates, PrimNet, in identifying seals following training on our seal dataset. The ease and wealth of image data that can be processed using SealNet software contributes a vital tool for ecological and behavioral studies of marine mammals in the emerging field of conservation technology.

Download Full-text

ON A NEW CLASS OF SEMI GENERALIZED CLOSED SETS IN STRONG GENERALIZED TOPOLOGICAL SPACES

Advances in Mathematics: Scientific Journal ◽

10.37418/amsj.9.11.41 ◽

2020 ◽

Vol 9 (11) ◽

pp. 9353-9360

Author(s):

G. Selvi ◽

I. Rajasekaran

Keyword(s):

Topological Spaces ◽

Closed Set ◽

Basic Properties ◽

Closed Sets ◽

New Class ◽

Open Set ◽

Continuous Maps

This paper deals with the concepts of semi generalized closed sets in strong generalized topological spaces such as $sg^{\star \star}_\mu$-closed set, $sg^{\star \star}_\mu$-open set, $g^{\star \star}_\mu$-closed set, $g^{\star \star}_\mu$-open set and studied some of its basic properties included with $sg^{\star \star}_\mu$-continuous maps, $sg^{\star \star}_\mu$-irresolute maps and $T_\frac{1}{2}$-space in strong generalized topological spaces.

Download Full-text

Distribution and Demographics of Marine Mammals in SOCAL through Photo-Identification, Genetics, and Satellite Telemetry: A Summary of Surveys Conducted 1 July 2011 - 15 June 2012

10.21236/ada567623 ◽

2012 ◽

Cited By ~ 2

Author(s):

Erin A. Falcone ◽

Gregory S. Schorr

Keyword(s):

Marine Mammals ◽

Satellite Telemetry ◽

Photo Identification

Download Full-text

Synthetic speech detection through short-term and long-term prediction traces

EURASIP Journal on Information Security ◽

10.1186/s13635-021-00116-3 ◽

2021 ◽

Vol 2021 (1) ◽

Author(s):

Clara Borrelli ◽

Paolo Bestagini ◽

Fabio Antonacci ◽

Augusto Sarti ◽

Stefano Tubaro

Keyword(s):

Deep Learning ◽

Speech Processing ◽

Synthetic Speech ◽

Opinion Formation ◽

Closed Set ◽

Speech Detection ◽

Open Set ◽

Technological Advances ◽

Speech Generation ◽

Long Term Prediction

AbstractSeveral methods for synthetic audio speech generation have been developed in the literature through the years. With the great technological advances brought by deep learning, many novel synthetic speech techniques achieving incredible realistic results have been recently proposed. As these methods generate convincing fake human voices, they can be used in a malicious way to negatively impact on today’s society (e.g., people impersonation, fake news spreading, opinion formation). For this reason, the ability of detecting whether a speech recording is synthetic or pristine is becoming an urgent necessity. In this work, we develop a synthetic speech detector. This takes as input an audio recording, extracts a series of hand-crafted features motivated by the speech-processing literature, and classify them in either closed-set or open-set. The proposed detector is validated on a publicly available dataset consisting of 17 synthetic speech generation algorithms ranging from old fashioned vocoders to modern deep learning solutions. Results show that the proposed method outperforms recently proposed detectors in the forensics literature.

Download Full-text

Mosquito species identification using convolutional neural networks with a multitiered ensemble model for novel species detection

Scientific Reports ◽

10.1038/s41598-021-92891-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Adam Goodwin ◽

Sanket Padmanabhan ◽

Sanchit Hira ◽

Margaret Glancey ◽

Monet Slinowsky ◽

...

Keyword(s):

Neural Networks ◽

Species Identification ◽

Convolutional Neural Networks ◽

Novel Species ◽

Novelty Detection ◽

Mosquito Species ◽

Image Database ◽

Closed Set ◽

Open Set

AbstractWith over 3500 mosquito species described, accurate species identification of the few implicated in disease transmission is critical to mosquito borne disease mitigation. Yet this task is hindered by limited global taxonomic expertise and specimen damage consistent across common capture methods. Convolutional neural networks (CNNs) are promising with limited sets of species, but image database requirements restrict practical implementation. Using an image database of 2696 specimens from 67 mosquito species, we address the practical open-set problem with a detection algorithm for novel species. Closed-set classification of 16 known species achieved 97.04 ± 0.87% accuracy independently, and 89.07 ± 5.58% when cascaded with novelty detection. Closed-set classification of 39 species produces a macro F1-score of 86.07 ± 1.81%. This demonstrates an accurate, scalable, and practical computer vision solution to identify wild-caught mosquitoes for implementation in biosurveillance and targeted vector control programs, without the need for extensive image database development for each new target region.

Download Full-text

EvidentialMix: Learning with Combined Open-set and Closed-set Noisy Labels

2021 IEEE Winter Conference on Applications of Computer Vision (WACV) ◽

10.1109/wacv48630.2021.00365 ◽

2021 ◽

Author(s):

Ragav Sachdeva ◽

Filipe R. Cordeiro ◽

Vasileios Belagiannis ◽

Ian Reid ◽

Gustavo Carneiro

Keyword(s):

Closed Set ◽

Open Set ◽

Noisy Labels

Download Full-text

On topological properties of weakly m-convex sets

Proceedings of the Institute of Applied Mathematics and Mechanics NAS of Ukraine ◽

10.37069/1683-4720-2020-34-8 ◽

2021 ◽

Vol 34 ◽

pp. 75-84

Author(s):

Tetiana Osipchuk

Keyword(s):

Convex Sets ◽

Convex Set ◽

Topological Classification ◽

Connected Components ◽

Topological Properties ◽

Convex Domains ◽

Closed Set ◽

Dimensional Plane ◽

Open Set ◽

Plane Passing

The topological properties of classes of generally convex sets in multidimensional real Euclidean space $\mathbb{R}^n$, $n\ge 2$, known as $m$-convex and weakly $m$-convex, $1\le m<n$, are studied in the present work. A set of the space $\mathbb{R}^n$ is called \textbf{\emph{$m$-convex}} if for any point of the complement of the set to the whole space there is an $m$-dimensional plane passing through this point and not intersecting the set. An open set of the space is called \textbf{\emph{weakly $m$-convex}}, if for any point of the boundary of the set there exists an $m$-dimensional plane passing through this point and not intersecting the given set. A closed set of the space is called \textbf{\emph{weakly $m$-convex}} if it is approximated from the outside by a family of open weakly $m$-convex sets. These notions were proposed by Professor Yuri Zelinskii. It is known the topological classification of (weakly) $(n-1)$-convex sets in the space $\mathbb{R}^n$ with smooth boundary. Each such a set is convex, or consists of no more than two unbounded connected components, or is given by the Cartesian product $E^1\times \mathbb{R}^{n-1}$, where $E^1$ is a subset of $\mathbb{R}$. Any open $m$-convex set is obviously weakly $m$-convex. The opposite statement is wrong in general. It is established that there exist open sets in $\mathbb{R}^n$ that are weakly $(n-1)$-convex but not $(n-1)$-convex, and that such sets consist of not less than three connected components. The main results of the work are two theorems. The first of them establishes the fact that for compact weakly $(n-1)$-convex and not $(n-1)$-convex sets in the space $\mathbb{R}^n$, the same lower bound for the number of their connected components is true as in the case of open sets. In particular, the examples of open and closed weakly $(n-1)$-convex and not $(n-1)$-convex sets with three and more connected components are constructed for this purpose. And it is also proved that any compact weakly $m$-convex and not $m$-convex set of the space $\mathbb{R}^n$, $n\ge 2$, $1\le m<n$, can be approximated from the outside by a family of open weakly $m$-convex and not $m$-convex sets with the same number of connected components as the closed set has. The second theorem establishes the existence of weakly $m$-convex and not $m$-convex domains, $1\le m<n-1$, $n\ge 3$, in the spaces $\mathbb{R}^n$. First, examples of weakly $1$-convex and not $1$-convex domains $E^p\subset\mathbb{R}^p$ for any $p\ge3$, are constructed. Then, it is proved that the domain $E^p\times\mathbb{R}^{m-1}\subset\mathbb{R}^n$, $n\ge 3$, $1\le m<n-1$, is weakly $m$-convex and not $m$-convex.

Download Full-text

Auditory Training and Speech Discrimination

Journal of Speech and Hearing Research ◽

10.1044/jshr.1304.839 ◽

1970 ◽

Vol 13 (4) ◽

pp. 839-855 ◽

Cited By ~ 18

Author(s):

Daniel L. Bode ◽

Herbert J. Oyer

Keyword(s):

Auditory Discrimination ◽

Auditory Training ◽

Speech Discrimination ◽

Training Material ◽

Closed Set ◽

Open Set ◽

Speech Reception ◽

Hearing Aid Use ◽

Response Formats ◽

Respective Type

Thirty-two adults with sensorineural hearing loss participated in a short-term auditory training program. The listeners were assigned to one of four matched groups which were equivalent in pure-tone sensitivity, speech-reception threshold, PB discrimination in quiet and in noise, intelligence, age, education, duration of loss, sex, and hearing-aid use. Each group responded during training to a different combination of listening condition (S/N varied or S/N-constant) and speech material (closed-set or open-set response formats). Statistically significant increase in auditory discrimination was shown on the W-22 and Rhyme tests, while the increase revealed by the Semi-Diagnostic test was not significant. Results indicated that the two listening conditions were equally effective. Similarly, the two types of training material brought about equivalent increases in overall speech discrimination. Trends suggested that open-set and closed-set training each had most effect on the respective type of speech discrimination. In addition, improvement in auditory discrimination was associated with those individuals who were oldest, with those who had highest intelligence, and with those who responded to training material at the most intense presentation level. Finally, listeners who reported the most hearing handicap also tended to show the greatest loss in speech reception and in speech discrimination in noise.

Download Full-text

Age determination of common bottlenose dolphins (Tursiops truncatus) using dental radiography pulp:tooth area ratio measurements

PLoS ONE ◽

10.1371/journal.pone.0242273 ◽

2020 ◽

Vol 15 (11) ◽

pp. e0242273

Author(s):

Jean M. Herrman ◽

Jeanine S. Morey ◽

Ryan Takeshita ◽

Sylvain De Guise ◽

Randall S. Wells ◽

...

Keyword(s):

Life Histories ◽

Marine Mammals ◽

Bottlenose Dolphins ◽

Age Determination ◽

Area Ratio ◽

Dental Radiography ◽

Ratio Method ◽

Data Sets ◽

Photo Identification ◽

Development And Validation

Age is an important parameter to better understand wildlife populations, and is especially relevant for interpreting data for fecundity, health, and survival assessments. Estimating ages for marine mammals presents a particular challenge due to the environment they inhabit: accessibility is limited and, when temporarily restrained for assessment, the window of opportunity for data collection is relatively short. For wild dolphins, researchers have described a variety of age-determination techniques, but the gold-standard relies upon photo-identification to establish individual observational life histories from birth. However, there are few populations with such long-term data sets, therefore alternative techniques for age estimation are required for individual animals without a known birth period. While there are a variety of methods to estimate ages, each involves some combination of drawbacks, including a lack of precision across all ages, weeks-to-months of analysis time, logistical concerns for field applications, and/or novel techniques still in early development and validation. Here, we describe a non-invasive field technique to determine the age of small cetaceans using periapical dental radiography and subsequent measurement of pulp:tooth area ratios. The technique has been successfully applied for bottlenose dolphins briefly restrained during capture-release heath assessments in various locations in the Gulf of Mexico. Based on our comparisons of dental radiography data to life history ages, the pulp:tooth area ratio method can reliably provide same-day estimates for ages of dolphins up to about 10 years old.

Download Full-text