scholarly journals I3S Classic and Insect Species Identification of Diptera and Hymenoptera (Mosquitoes and Bees)

2016 ◽  
Author(s):  
Nayna Vyas-Patel ◽  
John D Mumford
Keyword(s):  
Apis Mellifera ◽  
Image Recognition ◽  
Bombus Terrestris ◽  
Individual Recognition ◽  
Sensu Stricto ◽  
Individual Identification ◽  
Insect Species ◽  
Identification System ◽  
Accurate Identification ◽  
The Individual

AbstractA number of image recognition systems have been specifically formulated for the individual recognition of large animals. These programs are versatile and can easily be adapted for the identification of smaller individuals such as insects. The Interactive Individual Identification System, I3S Classic, initially produced for the identification of individual whale sharks was employed to distinguish between different species of mosquitoes and bees, utilising the distinctive vein pattern present on insect wings. I3S Classic proved to be highly effective and accurate in identifying different species and sexes of mosquitoes and bees, with 80% to100% accuracy for the majority of the species tested. The sibling species Apis mellifera and Apis mellifera carnica were both identified with100% accuracy. Bombus terrestris terrestris and Bombus terrestris audax; were also identified and separated with high degrees of accuracy (90% to 100% respectively for the fore wings and 100% for the hind wings). When both Anopheles gambiae sensu stricto and Anopheles arabiensis were present in the database, they were identified with 94% and 100% accuracy respectively, allowing for a morphological and non-molecular method of sorting between these members of the sibling complex. Flat, not folded and entire, rather than broken, wing specimens were required for accurate identification. Only one wing image of each sex was required in the database to retrieve high levels of accurate results in the majority of species tested. The study describes how I3S was used to identify different insect species and draws comparisons with the use of the CO1 algorithm. As with CO1, I3S Classic proved to be suitable software which could reliably be used to aid the accurate identification of insect species. It is emphasised that image recognition for insect species should always be used in conjunction with other identifying characters in addition to the wings, as is the norm when identifying species using traditional taxonomic keys.

scholarly journals Research on emitter individual identification technology based on Automatic Dependent Surveillance–Broadcast signal

2021 ◽  
Vol 17 (2) ◽  
pp. 155014772199262
Author(s):  
Shiwen Chen ◽  
Junjian Yuan ◽  
Xiaopeng Xing ◽  
Xin Qin
Keyword(s):  
Individual Recognition ◽  
Evidence Theory ◽  
Field Measurements ◽  
Training Data ◽  
Individual Identification ◽  
Identification System ◽  
Individual Feature ◽  
Data Set ◽  
Theoretical Simulation ◽  
The Individual

Aiming at the shortcomings of the research on individual identification technology of emitters, which is primarily based on theoretical simulation and lack of verification equipment to conduct external field measurements, an emitter individual identification system based on Automatic Dependent Surveillance–Broadcast is designed. On one hand, the system completes the individual feature extraction of the signal preamble. On the other hand, it realizes decoding of the transmitter’s individual identity information and generates an individual recognition training data set, on which we can train the recognition network to achieve individual signal recognition. For the collected signals, six parameters were extracted as individual features. To reduce the feature dimensions, a Bessel curve fitting method is used for four of the features. The spatial distribution of the Bezier curve control points after fitting is taken as an individual feature. The processed features are classified with multiple classifiers, and the classification results are fused using the improved Dempster–Shafer evidence theory. Field measurements show that the average individual recognition accuracy of the system reaches 88.3%, which essentially meets the requirements.

Iris photo-identification: A new methodology for the individual recognition of Tarentola geckos

2013 ◽  
Vol 34 (4) ◽  
pp. 590-596 ◽  
Author(s):  
Ricardo Rocha ◽  
Tiago Carrilho ◽  
Rui Rebelo
Keyword(s):  
Pattern Matching ◽  
Individual Recognition ◽  
Field Studies ◽  
Individual Identification ◽  
Identification System ◽  
Correct Identification ◽  
Photo Identification ◽  
Horizontal Angle ◽  
The Individual

Gekkonid field studies are hampered by the difficulty to individually recognize individuals. In this study we assess the feasibility of using their variegated iris pattern to photo-identify Tarentola boettgeri bischoffi, a threatened Macaronesian endemic. Using a library of 924 photos taken over a 9-month period we also evaluate the use of the pattern matching software Interactive Individual Identification System (I3S) to match photos of known specimens. Individuals were clearly recognized by their iris pattern with no misidentifications, and using I3S lead to a correct identification of 95% of the recaptures in a shorter time than the same process when conducted visually by an observer. The method’s feasibility was improved by increasing the number of images of each animal in the library and hindered by photos that deviate from a horizontal angle.

scholarly journals Cow Rump Identification Based on Lightweight Convolutional Neural Networks

Information ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 361
Author(s):  
Handan Hou ◽  
Wei Shi ◽  
Jinyan Guo ◽  
Zhe Zhang ◽  
Weizheng Shen ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Dairy Cow ◽  
Individual Recognition ◽  
Animal Husbandry ◽  
Identification Accuracy ◽  
Individual Identification ◽  
Production Environment ◽  
Accurate Identification ◽  
Computing Device

Individual identification of dairy cows based on computer vision technology shows strong performance and practicality. Accurate identification of each dairy cow is the prerequisite of artificial intelligence technology applied in smart animal husbandry. While the rump of each dairy cow also has lots of important features, so do the back and head, which are also important for individual recognition. In this paper, we propose a non-contact cow rump identification method based on convolutional neural networks. First, the rump image sequences of the cows while feeding were collected. Then, an object detection model was applied to detect the cow rump object in each frame of image. Finally, a fine-tuned convolutional neural network model was trained to identify cow rumps. An image dataset containing 195 different cows was created to validate the proposed method. The method achieved an identification accuracy of 99.76%, which showed a better performance compared to other related methods and a good potential in the actual production environment of cow husbandry, and the model is light enough to be deployed in an edge-computing device.

scholarly journals Individual identification of Crocodylus intermedius (Orinoco crocodile) using tail spot patterns

2020 ◽  
Vol 12 (2) ◽  
pp. e3140
Author(s):  
Alvaro Velasco Barbieri
Keyword(s):  
Action Plan ◽  
Natural Habitat ◽  
Individual Identification ◽  
Dark Spot ◽  
Identification System ◽  
Conservation Action ◽  
Accurate Identification ◽  
The One ◽  
The Right ◽  
Conservation Action Plan

Introduction: The Conservation Action Plan of the Orinoco crocodile (Crocodylus intermedius) includes in its activities the release of captive-bred specimens back into the wild. By monitoring these specimens in their natural habitat their adaptability is assessed. However, an accurate identification system is necessary to recognize the individuals when they are recaptured. Objetive: Determinate if Swanepoel or Boucher et al. for crocodile identification for the Orinoco crocodile is useful.  Methods: A total of 543 Orinoco crocodiles were photographed and each photo was vectorized by drawing dark spots greater than 25% for each scute, in the first 10 lines of double caudal scales of the tail on the right side. Two system codes were evaluated, one is a numeric code described by Swanepoel and the other is an additive code described by Boucher et al. Results: A total of 464 Swanepoel codes and 537 Boucher et al. codes based on the dark spot pattern of the scales on the right side of the tails were generated for the 543 specimens. Both methods yielded high code values, however, the one developed by Boucher et al., with a 98.90% differentiation of the analyzed specimens, worked better. Conclusion: The study confirms that using the method of spots in the tail of crocodiles is an effective tool for identifying individual crocodiles.

Individual Identification Using Images of Eyes

1997 ◽  
Vol 9 (1) ◽  
pp. 41-45
Author(s):  
Satoshi Tanigawa ◽  
◽  
Masafumi Uchida ◽  
Hideto Ide
Keyword(s):  
Individual Identification ◽  
Identification System ◽  
Information Industry ◽  
Business Information ◽  
Crime Investigation ◽  
Security Business ◽  
The Individual ◽  
Business Security

Individual identification is required in various fields such as credit business, security business, information industry and crime investigation. This paper describes the individual identification system using images of eyes. With this system having used images data of 20 registered persons and 20 unregistered persons, we could obtain a high recogniniton rate and showing how efficient this system is.

scholarly journals Shot the spots: A reliable field method for individual identification of Amolops formosus (Anura, Ranidae)

Herpetozoa ◽  
2020 ◽  
Vol 33 ◽  
pp. 7-15
Author(s):  
Naitik G. Patel ◽  
Abhijit Das
Keyword(s):  
Image Quality ◽  
Individual Recognition ◽  
Field Method ◽  
Individual Identification ◽  
Abundance Estimate ◽  
Recognition Efficiency ◽  
The Difference ◽  
Body Patterns ◽  
The Individual ◽  
User Review

Natural body patterns in amphibians are widely used for individual recognition. In this study, we photographed individuals of Amolops formosus for four days of sampling without handling them. We processed 301 photographs of dorsal blotch pattern in HotSpotter software and verified them visually for confirmation. We identified 160 unique individuals of A. formosus based on the images taken in the field, resulting in an abundance estimate of 180 individuals. The success rate in identifying individuals of A. formosus using the HotSpotter software was 94.3%. We tested the effect of image quality and distance on recognition efficiency. Poor image quality reduced the recognition efficiency of the software but with a careful user review it was possible to identify the individual. The difference between using only the software and software plus human confirmation was very small. This protocol is useful for rapid population estimation of frogs with natural body patterns.

scholarly journals A Novel Two-Level Fusion Feature for Mixed ECG Identity Recognition

Electronics ◽  
2021 ◽  
Vol 10 (17) ◽  
pp. 2052
Author(s):  
Xin Liu ◽  
Yujuan Si ◽  
Weiyi Yang
Keyword(s):  
Principal Component ◽  
Individual Identification ◽  
Support Vector ◽  
Identification System ◽  
Identity Recognition ◽  
Deep Feature ◽  
Single Feature ◽  
The Individual ◽  
Fusion Feature ◽  
Level Fusion

In recent years, with the increasing standard of biometric identification, it is difficult to meet the requirements of data size and accuracy in practical application for training a single ECG (electrocardiogram) database. The paper aims to construct a recognition model for processing multi-source data and proposes a novel ECG identification system based on two-level fusion features. Firstly, the features of Hilbert transform and power spectrum are extracted from the segmented heartbeat data, then two features are combined into a set and normalized to obtain the elementary fusion feature. Secondly, PCANet (Principal Component Analysis Network) is used to extract the discriminative deep feature of signal, and MF (MaxFusion) algorithm is proposed to fuse and compress the two layers learning features. Finally, a linear support vector machine (SVM) is used to obtain labels of single feature classification and complete the individual identification. The recognition results of the proposed two-level fusion PCANet deep recognition network achieve more than 95% on ECG-ID, MIT-BIH, and PTB public databases. Most importantly, the recognition accuracy of the mixed database can reach 99.77%, which includes 426 individuals.

scholarly journals Gene Sequencing and Phylogenetic Analysis: Powerful Tools for an Improved Diagnosis of Fish Mycobacteriosis Caused by Mycobacterium fortuitum Group Members

2021 ◽  
Vol 9 (4) ◽  
pp. 797
Author(s):  
Davide Mugetti ◽  
Mattia Tomasoni ◽  
Paolo Pastorino ◽  
Giuseppe Esposito ◽  
Vasco Menconi ◽  
...  
Keyword(s):  
Phylogenetic Analysis ◽  
Gene Sequencing ◽  
Diagnostic Techniques ◽  
Individual Species ◽  
Identification System ◽  
Mycobacterium Fortuitum ◽  
Biochemical Tests ◽  
Species Determination ◽  
Gene Encoding ◽  
The Individual

The Mycobacterium fortuitum group (MFG) consists of about 15 species of fast-growing nontuberculous mycobacteria (NTM). These globally distributed microorganisms can cause diseases in humans and animals, especially fish. The increase in the number of species belonging to MFG and the diagnostic techniques panel do not allow to clarify their real clinical significance. In this study, biomolecular techniques were adopted for species determination of 130 isolates derived from fish initially identified through biochemical tests as NTM belonging to MFG. Specifically, gene sequencing and phylogenetic analysis were used based on a fragment of the gene encoding the 65 KDa heat shock protein (hsp65). The analyzes made it possible to confirm that all the isolates belong to MFG, allowing to identify the strains at species level. Phylogenetic analysis substantially confirmed what was obtained by gene sequencing, except for six strains; this is probably due to the sequences present in NCBI database. Although the methodology used cannot represent a univocal identification system, this study has allowed us to evaluate its effectiveness as regards the species of MFG. Future studies will be necessary to apply these methods with other gene fragments and to clarify the real pathogenic significance of the individual species of this group of microorganisms.

scholarly journals Intra-Colonial Viral Infections in Western Honey Bees (Apis mellifera)

2021 ◽  
Vol 9 (5) ◽  
pp. 1087
Author(s):  
Loreley Castelli ◽  
María Laura Genchi García ◽  
Anne Dalmon ◽  
Daniela Arredondo ◽  
Karina Antúnez ◽  
...  
Keyword(s):  
Apis Mellifera ◽  
Honey Bee ◽  
Viral Infections ◽  
Sampling Period ◽  
Virus Genome ◽  
The Individual ◽  
Bee Virus ◽  
Insight Into ◽  
Bee Viruses

RNA viruses play a significant role in the current high losses of pollinators. Although many studies have focused on the epidemiology of western honey bee (Apis mellifera) viruses at the colony level, the dynamics of virus infection within colonies remains poorly explored. In this study, the two main variants of the ubiquitous honey bee virus DWV as well as three major honey bee viruses (SBV, ABPV and BQCV) were analyzed from Varroa-destructor-parasitized pupae. More precisely, RT-qPCR was used to quantify and compare virus genome copies across honey bee pupae at the individual and subfamily levels (i.e., patrilines, sharing the same mother queen but with different drones as fathers). Additionally, virus genome copies were compared in cells parasitized by reproducing and non-reproducing mite foundresses to assess the role of this vector. Only DWV was detected in the samples, and the two variants of this virus significantly differed when comparing the sampling period, colonies and patrilines. Moreover, DWV-A and DWV-B exhibited different infection patterns, reflecting contrasting dynamics. Altogether, these results provide new insight into honey bee diseases and stress the need for more studies about the mechanisms of intra-colonial disease variation in social insects.

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