scholarly journals Photo-identification as a technique for recognition of individual fish: a test with the freshwater armored catfish Rineloricaria aequalicuspis Reis & Cardoso, 2001 (Siluriformes: Loricariidae)

2016 ◽  
Vol 14 (1) ◽  
Author(s):  
Renato B. Dala-Corte ◽  
Júlia B. Moschetta ◽  
Fernando G. Becker
Keyword(s):  
Individual Recognition ◽  
Field Conditions ◽  
Computer Assisted ◽  
Photo Identification ◽  
Naked Eye ◽  
Behavioral Studies ◽  
Feasible Alternative ◽  
Intraspecific Recognition ◽  
Potential Use ◽  
Natural Marks

Abstract Photo-identification allows individual recognition of animal species based on natural marks, being an alternative to other more stressful artificial tagging/marking techniques. An increasing number of studies with different animal groups has shown that photo-identification can successfully be used in several situations, but its feasibility to study freshwater fishes is yet to be explored. We demonstrate the potential use of photo-identification for intraspecific recognition of individuals in the stream-dwelling loricariid Rineloricaria aequalicuspis . We tested photo-identification in laboratory and field conditions based on the interindividual variability in abdominal bony plates. Our test yielded high correct matches in both laboratory (100%) and field conditions (> 97%), comparable to other reliable techniques and to studies that successfully used photo-identification in other animals. In field conditions, the number of correct matches did not differ statistically between computer-assisted and naked-eye identification. However, the average time expended to conclude computer-assisted photo evaluations was about half of the time expended to conclude naked-eye evaluations. This result may be exacerbated when using database with large number of images. Our results indicate that photo-identification can be a feasible alternative technique to study freshwater fish species, allowing for a wider use of mark-recapture in ecological and behavioral studies.

Can ventral pattern be used for individual recognition of the vulnerable Pyrenean brook newt (Calotriton asper)?

2021 ◽  
pp. 99-110
Author(s):  
Manon Dalibard
Keyword(s):  
Individual Recognition ◽  
Rejection Rate ◽  
Poor Quality ◽  
Error Rates ◽  
Acceptance Rate ◽  
Computer Assisted ◽  
Photo Identification ◽  
Passive Integrated Transponders ◽  
Reference Images ◽  
Colour Patterns

Individual recognition of animal species is a prerequisite for capture-mark-recapture (CMR) studies. For amphibians, photoidentification of body pattern is a non-invasive and less expensive alternative than classical marking methods (e.g. passive integrated transponder). However, photo-identification is effective only if the patterns are (i) sufficiently variable between individuals, and (ii) stable over time. This method also depends on the observer’s judgment. In the present study, we assessed the effectiveness of an automatic algorithm (AmphIdent) to recognise ventral colour patterns of the Pyrenean brook newt (Calotrion asper), endemic to the Pyrenees Mountains of France. To assess the performance of the tested method, 113 individuals from two different streams were marked with passive integrated transponders (PIT-tags). We used false rejection rate (FRR), false acceptance rate (FAR) and true acceptance rate (TAR) as metrics to evaluate performances of photoidentification. Mean FRR was 7.3 %, FAR was 5.2 %, and TAR was 92 % across both streams, both sexes and all the observers. FAR was significantly different between sexes, while FRR and TAR were significantly influenced by the interaction between the sex and the stream. Despite these differences, our error rates are among the lowest values found in the literature for both amphibian and non-amphibian computer-assisted photo-identification. We found that poor-quality reference pictures could lead to an increasing difficulty to achieve a correct match when time since first capture rose. Consequently, individual photo-identification using AmphIdent software is a reliable tool to aid in the monitoring the Pyrenean brook newts, provided that pictures are taken with care, reference images are regularly updated and observers are properly trained to use the software and interpret images.

scholarly journals Photo-identification of horseshoe whip snakes (Hemorrhois hippocrepis, Linnaeus, 1758) by a semi-automatic procedure applied to wildlife management

2019 ◽  
pp. 304-307
Author(s):  
Andreu Rotger
Keyword(s):  
Wildlife Management ◽  
Traditional Method ◽  
Large Scale ◽  
Individual Recognition ◽  
Photo Identification ◽  
Animal Populations ◽  
Wildlife Control ◽  
Capture Recapture ◽  
Control Study ◽  
Natural Marks

Photo-identification is an increasingly used method for the study of animal populations. Natural marks such as coloration or scale pattern to identify individuals provide an inexpensive and less invasive alternative to conventional tagging methods. Photo-identification has previously been used to distinguish individual snakes, usually by comparing the pileus region. Nevertheless, this method is seldom used in capture-recapture studies. We show the effectiveness of photo-identification in snakes using specific software for individual recognition applied to a wildlife control study of horseshoe whip snakes. Photos were analysed with Automatic Photo Identification Suite (APHIS), which allowed us to compare the variability of head scale patterns surrounding the parietal shields instead of the traditional method of using large scale groups of the pileus. APHIS correctly identified 100 % of recaptures of snakes. Although further studies are needed, the variability of the surrounding scales of the pileus region seems a robust method to identify and differentiate individuals.

Computer-assisted photo-identification of individual marine vertebrates: a multi-species system

2003 ◽  
Vol 29 (1) ◽  
pp. 117-123 ◽  
Author(s):  
G. R. Hillman ◽  
B. Würsig ◽  
G. A. Gailey ◽  
N. Kehtarnavaz ◽  
A. Drobyshevsky ◽  
...  
Keyword(s):  
Computer Assisted ◽  
Photo Identification ◽  
Marine Vertebrates

Computer-Assisted Photo-Identification of Narwhals

ARCTIC ◽  
2011 ◽  
Vol 64 (3) ◽  
Author(s):  
Marie Auger-Méthé ◽  
Marianne Marcoux ◽  
Hal Whitehead
Keyword(s):  
Computer Assisted ◽  
Photo Identification

scholarly journals Social Sensors for Wildlife: Ecological Opportunities in the Era of Camera Ubiquity

2021 ◽  
Vol 8 ◽  
Author(s):  
Alex Borowicz ◽  
Heather J. Lynch ◽  
Tyler Estro ◽  
Catherine Foley ◽  
Bento Gonçalves ◽  
...  
Keyword(s):  
Ad Hoc ◽  
Individual Recognition ◽  
Image Data ◽  
Weddell Seal ◽  
Science Data ◽  
Photo Identification ◽  
Mobile Species ◽  
Community Science ◽  
The Antarctic ◽  
Social Sensors

Expansive study areas, such as those used by highly-mobile species, provide numerous logistical challenges for researchers. Community science initiatives have been proposed as a means of overcoming some of these challenges but often suffer from low uptake or limited long-term participation rates. Nevertheless, there are many places where the public has a much higher visitation rate than do field researchers. Here we demonstrate a passive means of collecting community science data by sourcing ecological image data from the digital public, who act as “eco-social sensors,” via a public photo-sharing platform—Flickr. To achieve this, we use freely-available Python packages and simple applications of convolutional neural networks. Using the Weddell seal (Leptonychotes weddellii) on the Antarctic Peninsula as an example, we use these data with field survey data to demonstrate the viability of photo-identification for this species, supplement traditional field studies to better understand patterns of habitat use, describe spatial and sex-specific signals in molt phenology, and examine behavioral differences between the Antarctic Peninsula’s Weddell seal population and better-studied populations in the species’ more southerly fast-ice habitat. While our analyses are unavoidably limited by the relatively small volume of imagery currently available, this pilot study demonstrates the utility an eco-social sensors approach, the value of ad hoc wildlife photography, the role of geographic metadata for the incorporation of such imagery into ecological analyses, the remaining challenges of computer vision for ecological applications, and the viability of pelage patterns for use in individual recognition for this species.

Computer-Assisted Instruction in Industrial Relations Teaching

1988 ◽  
Vol 30 (2) ◽  
pp. 215-229
Author(s):  
R.E. Fells ◽  
J.R. Weaver
Keyword(s):  
Professional Development ◽  
Low Cost ◽  
Industrial Relations ◽  
Health And Safety ◽  
Computer Assisted Instruction ◽  
Computer Assisted ◽  
Government Agencies ◽  
The Subject ◽  
Assisted Instruction ◽  
Potential Use

The teaching of industrial relations in Australia is a fairly recent phenomenon, principally developing over the last twenty years. Consequently it is only recently that the 'academic infrastructure'—viable industrial relations departments, a range of literature, a choice of texts and journals—has developed to enable the subject to become an identifiable area of teaching. As a result it is not surprising that the use of computers in teaching industrial relations is not well developed when compared with other disciplines, such as economics, management and accounting where games, simulations and question testing banks are available. However, the use of computer-assisted instruction (CAI) is not confined to academic institutions: it has the potential to be a low-cost delivery system for training within other organizations. Employers, employer organizations and unions all engage in training and, therefore, all have a potential use for CAI. A number of government agencies are examining the use of computer- assisted instruction in training staff in, for example, occupational health and safety, and it has potential as a tool in professional development programmes. With the development of microcomputers the costs of using CAI are declining.

scholarly journals Photo-identification of individual Southern Hemisphere humpback whales (Megaptera novaeangliae) using all available natural marks:

2020 ◽  
Vol 21 (1) ◽  
pp. 71-83
Author(s):  
Wally Franklin ◽  
Trish Franklin ◽  
Peter Harrison ◽  
Lyndon Brooks
Keyword(s):  
Poor Quality ◽  
Megaptera Novaeangliae ◽  
Humpback Whales ◽  
Parameter Estimates ◽  
Photo Identification ◽  
Dorsal Fin ◽  
Matching Process ◽  
Lateral Body ◽  
Logistic Mixed Effects Model ◽  
Natural Marks

Misidentification errors in capture-mark recapture studies of humpback whales (Megaptera novaeangliae) related to poor quality of photographs as well as changes in natural marks can seriously affect population dynamics parameter estimates and derived estimates of population size when using sophisticated modelling techniques. In this study we used an innovative photo-identification matching system to investigate and examine the long-term stability and/or changes in natural marks on ventral-tail flukes, dorsal fin shapes and lateral body marks from a sample of 79 individual humpback whales, resighted in 2 to 11 years over timespans ranging from 2 to 21 years. A binary logistic mixed effects model, on a pair-matched sample of the 79 individual whales, found no significant differences in the proportions of ventral-tail fluke marks, dorsal fin shapes and lateral body marks, that displayed changes in primary and/or secondary characteristics over years (F=0.939, df=1/156, p =0.334). The results of this study substantiate the value and reliability of using primary and secondary natural marks on the ventral-tail flukes, in conjunction with dorsal fin shapes and secondary lateral body marks as double-tags. This provides a means of maximising observations of individual humpback whales over years, while minimising and managing misidentification errors in the photo-identification matching process, thus significantly improving modelling outcomes.

scholarly journals SEALNET: Facial recognition software for ecological studies of harbor seals

2022 ◽  
Author(s):  
Zachary Birenbaum ◽  
Hieu Do ◽  
Lauren Horstmeyer ◽  
Hailey Orff ◽  
Krista Ingram ◽  
...  
Keyword(s):  
Marine Mammals ◽  
Facial Recognition ◽  
Image Data ◽  
Harbor Seals ◽  
Closed Set ◽  
Photo Identification ◽  
Bay Area ◽  
Open Set ◽  
Coastal Species ◽  
Behavioral Studies

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.

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