Journal articles on the topic 'Individual recognition'

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1

Yacoob, Sahal. "Individual recognition." Physics World 28, no. 10 (October 2015): 15. http://dx.doi.org/10.1088/2058-7058/28/10/26.

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Matsunaga, K., and K. Tanaka. "Individual Recognition via Brainprint." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2004 (2004): 93–94. http://dx.doi.org/10.1299/jsmermd.2004.93_4.

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3

Richler, Jennifer J., Andrew J. Tomarken, Mackenzie A. Sunday, Timothy J. Vickery, Kaitlin F. Ryan, R. Jackie Floyd, David Sheinberg, Alan C. N. Wong, and Isabel Gauthier. "Individual differences in object recognition." Psychological Review 126, no. 2 (March 2019): 226–51. http://dx.doi.org/10.1037/rev0000129.

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4

D'Ettorre, Patrizia, and Jürgen Heinze. "Individual Recognition in Ant Queens." Current Biology 15, no. 23 (December 2005): 2170–74. http://dx.doi.org/10.1016/j.cub.2005.10.067.

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5

Watanabe, Shigeru, and Youko Mori. "Individual recognition learning in mice." Journal of Ethology 8, no. 1 (June 1990): 29–32. http://dx.doi.org/10.1007/bf02350127.

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6

Van Ballegooij, Wouter, and Petra Bárd. "Mutual Recognition and Individual Rights." New Journal of European Criminal Law 7, no. 4 (December 2016): 439–64. http://dx.doi.org/10.1177/203228441600700405.

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This article focuses on the case-law of the Court of Justice and the dialogue it conducted with national apex courts when seeking to reconcile the ‘free movement of judicial decisions’, as facilitated by mutual recognition, and individual rights in its interpretation of the Framework Decision on the European Arrest Warrant. The present analysis shall concentrate on the recent judgment in Aranyosi and Căldăraru. The article concludes that for the sake of legal certainty, more guidance should be provided under EU legislation to make sure that judicial cooperation does not lead to disproportionate intrusions on individual rights or even violations of absolute rights. This should be accompanied by a permanent mechanism for monitoring and addressing Member State compliance with democracy, the rule of law and fundamental rights. Ultimately, however, the courts will have to play a crucial role in carving out and applying fundamental rights exceptions. In providing guidance to national courts, the Court of Justice needs to further clarify that the application of mutual recognition and fundamental rights exceptions are not in conflict and show proper deference to the norms developed by the European Court of Human Rights and national (constitutional) courts.
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Dhondt, AndréA, and Marcel M. Lambrechts. "Individual voice recognition in birds." Trends in Ecology & Evolution 7, no. 6 (June 1992): 178–79. http://dx.doi.org/10.1016/0169-5347(92)90068-m.

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8

Engelberg, Jonathan W. M., Jay W. Schwartz, and Harold Gouzoules. "Do human screams permit individual recognition?" PeerJ 7 (June 24, 2019): e7087. http://dx.doi.org/10.7717/peerj.7087.

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The recognition of individuals through vocalizations is a highly adaptive ability in the social behavior of many species, including humans. However, the extent to which nonlinguistic vocalizations such as screams permit individual recognition in humans remains unclear. Using a same-different vocalizer discrimination task, we investigated participants’ ability to correctly identify whether pairs of screams were produced by the same person or two different people, a critical prerequisite to individual recognition. Despite prior theory-based contentions that screams are not acoustically well-suited to conveying identity cues, listeners discriminated individuals at above-chance levels by their screams, including both acoustically modified and unmodified exemplars. We found that vocalizer gender explained some variation in participants’ discrimination abilities and response times, but participant attributes (gender, experience, empathy) did not. Our findings are consistent with abundant evidence from nonhuman primates, suggesting that both human and nonhuman screams convey cues to caller identity, thus supporting the thesis of evolutionary continuity in at least some aspects of scream function across primate species.
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Min, Huasong, Ziming Chen, Bin Fang, Ziwei Xia, Yixu Song, Zongtao Wang, Quan Zhou, Fuchun Sun, and Chunfang Liu. "Cross-Individual Gesture Recognition Based on Long Short-Term Memory Networks." Scientific Programming 2021 (July 6, 2021): 1–11. http://dx.doi.org/10.1155/2021/6680417.

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Gestures recognition based on surface electromyography (sEMG) has been widely used for human-computer interaction. However, there are few research studies on overcoming the influence of physiological factors among different individuals. In this paper, a cross-individual gesture recognition method based on long short-term memory (LSTM) networks is proposed, named cross-individual LSTM (CI-LSTM). CI-LSTM has a dual-network structure, including a gesture recognition module and an individual recognition module. By designing the loss function, the individual information recognition module assists the gesture recognition module to train, which tends to orthogonalize the gesture features and individual features to minimize the impact of individual information differences on gesture recognition. Through cross-individual gesture recognition experiments, it is verified that compared with other selected algorithm models, the recognition accuracy obtained by using the CI-LSTM model can be improved by an average of 9.15%. Compared with other models, CI-LSTM can overcome the influence of individual characteristics and complete the task of cross-individual hand gestures recognition. Based on the proposed model, online control of the prosthetic hand is realized.
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10

Jacot, Alain, Hendrik Reers, and Wolfgang Forstmeier. "Individual recognition and potential recognition errors in parent–offspring communication." Behavioral Ecology and Sociobiology 64, no. 10 (April 30, 2010): 1515–25. http://dx.doi.org/10.1007/s00265-010-0965-5.

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11

Chung, Myung, Mu‐Yun Wang, Ziyan Huang, and Teruhiro Okuyama. "Diverse sensory cues for individual recognition." Development, Growth & Differentiation 62, no. 9 (November 20, 2020): 507–15. http://dx.doi.org/10.1111/dgd.12697.

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12

Retter, Talia L., Caroline Michel, Fang Jiang, Michael A. Webster, and Bruno Rossion. "The speed of individual face recognition." Journal of Vision 19, no. 10 (September 6, 2019): 229c. http://dx.doi.org/10.1167/19.10.229c.

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13

Han, J., and Bir Bhanu. "Individual recognition using gait energy image." IEEE Transactions on Pattern Analysis and Machine Intelligence 28, no. 2 (February 2006): 316–22. http://dx.doi.org/10.1109/tpami.2006.38.

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14

Takahashi, Koichi, and Yasue Mitsukura. "Facial Expression Recognition with Individual Adjustment." IEICE Proceeding Series 1 (March 17, 2014): 78–81. http://dx.doi.org/10.15248/proc.1.78.

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15

Goldberg, Louis J. "Face Recognition and the Social Individual." Biosemiotics 6, no. 3 (September 27, 2013): 573–83. http://dx.doi.org/10.1007/s12304-013-9188-2.

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16

Tibbetts, Elizabeth A., Michael J. Sheehan, and James Dale. "A testable definition of individual recognition." Trends in Ecology & Evolution 23, no. 7 (July 2008): 356. http://dx.doi.org/10.1016/j.tree.2008.03.007.

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17

Crandell, Carl C. "Individual Differences in Speech Recognition Ability." Ear and Hearing 12, SUPPLEMENT (December 1991): 100S—108S. http://dx.doi.org/10.1097/00003446-199112001-00003.

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18

Gherardi, Francesca, and John Tiedemann. "Binary individual recognition in hermit crabs." Behavioral Ecology and Sociobiology 55, no. 6 (April 1, 2004): 524–30. http://dx.doi.org/10.1007/s00265-003-0734-9.

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19

O’Dwyer, Terence W., and Gabrielle A. Nevitt. "Individual Odor Recognition in Procellariiform Chicks." Annals of the New York Academy of Sciences 1170, no. 1 (July 2009): 442–46. http://dx.doi.org/10.1111/j.1749-6632.2009.03887.x.

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20

Kubo, Masao, Tatsuro Yoshimura, Akihiro Yamaguchi, and Hiroshi Sato. "Individual recognition-free target enclosure model." Artificial Life and Robotics 17, no. 1 (July 11, 2012): 11–16. http://dx.doi.org/10.1007/s10015-012-0010-z.

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21

Yorzinski, Jessica L. "The cognitive basis of individual recognition." Current Opinion in Behavioral Sciences 16 (August 2017): 53–57. http://dx.doi.org/10.1016/j.cobeha.2017.03.009.

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22

Schmidt,, Th, P. Hinterdorfer, and H. Schindler. "Microscopy for recognition of individual biomolecules." Microscopy Research and Technique 44, no. 5 (March 1, 1999): 339–46. http://dx.doi.org/10.1002/(sici)1097-0029(19990301)44:5<339::aid-jemt4>3.0.co;2-6.

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23

Sheehan, Michael J., Michael A. Straub, and Elizabeth A. Tibbetts. "How Does Individual Recognition Evolve? Comparing Responses to Identity Information inPolistesSpecies with and Without Individual Recognition." Ethology 120, no. 2 (November 28, 2013): 169–79. http://dx.doi.org/10.1111/eth.12191.

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24

Bosen, Adam K., Victoria A. Sevich, and Shauntelle A. Cannon. "Forward Digit Span and Word Familiarity Do Not Correlate With Differences in Speech Recognition in Individuals With Cochlear Implants After Accounting for Auditory Resolution." Journal of Speech, Language, and Hearing Research 64, no. 8 (August 9, 2021): 3330–42. http://dx.doi.org/10.1044/2021_jslhr-20-00574.

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Purpose In individuals with cochlear implants, speech recognition is not associated with tests of working memory that primarily reflect storage, such as forward digit span. In contrast, our previous work found that vocoded speech recognition in individuals with normal hearing was correlated with performance on a forward digit span task. A possible explanation for this difference across groups is that variability in auditory resolution across individuals with cochlear implants could conceal the true relationship between speech and memory tasks. Here, our goal was to determine if performance on forward digit span and speech recognition tasks are correlated in individuals with cochlear implants after controlling for individual differences in auditory resolution. Method We measured sentence recognition ability in 20 individuals with cochlear implants with Perceptually Robust English Sentence Test Open-set sentences. Spectral and temporal modulation detection tasks were used to assess individual differences in auditory resolution, auditory forward digit span was used to assess working memory storage, and self-reported word familiarity was used to assess vocabulary. Results Individual differences in speech recognition were predicted by spectral and temporal resolution. A correlation was found between forward digit span and speech recognition, but this correlation was not significant after controlling for spectral and temporal resolution. No relationship was found between word familiarity and speech recognition. Forward digit span performance was not associated with individual differences in auditory resolution. Conclusions Our findings support the idea that sentence recognition in individuals with cochlear implants is primarily limited by individual differences in working memory processing, not storage. Studies examining the relationship between speech and memory should control for individual differences in auditory resolution.
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Kulahci, Ipek G., Christine M. Drea, Daniel I. Rubenstein, and Asif A. Ghazanfar. "Individual recognition through olfactory–auditory matching in lemurs." Proceedings of the Royal Society B: Biological Sciences 281, no. 1784 (June 7, 2014): 20140071. http://dx.doi.org/10.1098/rspb.2014.0071.

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Individual recognition can be facilitated by creating representations of familiar individuals, whereby information from signals in multiple sensory modalities become linked. Many vertebrate species use auditory–visual matching to recognize familiar conspecifics and heterospecifics, but we currently do not know whether representations of familiar individuals incorporate information from other modalities. Ring-tailed lemurs ( Lemur catta ) are highly visual, but also communicate via scents and vocalizations. To investigate the role of olfactory signals in multisensory recognition, we tested whether lemurs can recognize familiar individuals through matching scents and vocalizations. We presented lemurs with female scents that were paired with the contact call either of the female whose scent was presented or of another familiar female from the same social group. When the scent and the vocalization came from the same individual versus from different individuals, females showed greater interest in the scents, and males showed greater interest in both the scents and the vocalizations, suggesting that lemurs can recognize familiar females via olfactory–auditory matching. Because identity signals in lemur scents and vocalizations are produced by different effectors and often encountered at different times (uncoupled in space and time), this matching suggests lemurs form multisensory representations through a newly recognized sensory integration underlying individual recognition.
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Ruiz de la Hermosa, A., F. Truyols-Hermosa, and S. Pinya. "Individual photographic identification based on unique colour pattern of the thorax of Acherontia atropos (Linnaeus, 1758) (Lepidoptera: Sphingidae)." SHILAP Revista de lepidopterología 50, no. 197 (March 30, 2022): 33–41. http://dx.doi.org/10.57065/shilap.181.

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Natural marks have increasingly been used as a tool for individual identification. One of the most popular techniques used by natural marks as an individual recognition tool is photo-identification. Photo-identification is a non-invasive alternative to traditional marking, which allows individual recognition of species through time and space. In this study, the APHIS (Automatic Photo Identification Suite) software has been evaluated as software capable of identifying individuals of Acherontia atropos (Linnaeus, 1758). The SPM (Spot Pattern Matching) and ITM (Image Template Matching) procedures were tested and found to achieve 100% success of individuals recognition. Thus, for the first time in a Sphingidae, the colour pattern of the dorsal part of the thorax of A. atropos is demonstrated to represent a suitable natural mark for individual recognition.
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Chmielewski, Adam. "Two Concepts of Recognition." Studia Philosophica Wratislaviensia 14, no. 1 (January 29, 2019): 49–68. http://dx.doi.org/10.19195/1895-8001.14.1.4.

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The aim of this paper is to submit the doctrine of methodological individualism to a reconsideration from the point of view of the arguments formulated by contemporary communitarian philosophy. I propose to approach the opposition between the individual and the community, constitutive for the liberal– communitarian debate, by means of two concepts, i.e. those of recognition and order. I argue that for the individualists a social order emerges through a process of mutual recognition of the pre-existing individuals and their interests, while the communitarians claim that the task of individuals is to recognize values and norms of a pre-existing social order which is to become their own. The difference between them thus resides primarily in the ontological distinction between the respective objects of these two divergent concepts of recognition. The argument is developed through an analysis of David Hume’s concept of the individual. In opposition to some communitarian claims, I maintain that his approach may be interpreted as an antecedent of the communitarian views on the subject. I also outline a view of moral rules as neither universal, absolutist, nor purely emotivist in character, but as social constructions endowed with the status of “contingent permanence.”
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Webster, Mike M., and Kevin N. Laland. "No evidence for individual recognition in threespine or ninespine sticklebacks ( Gasterosteus aculeatus or Pungitius pungitius )." Royal Society Open Science 7, no. 7 (July 2020): 191703. http://dx.doi.org/10.1098/rsos.191703.

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Recognition plays an important role in the formation and organization of animal groups. Many animals are capable of class-level recognition, discriminating, for example, on the basis of species, kinship or familiarity. Individual recognition requires that animals recognize distinct cues, and learn to associate these with the specific individual from which they are derived. In this study, we asked whether sticklebacks ( Gasterosteus aculeatus and Pungitius pungitius ) were capable of learning to recognize individual conspecifics. We have used these fish as model organisms for studying selective social learning, and demonstrating a capacity for individual recognition in these species would provide an exciting opportunity for studying how biases for copying specific individuals shape the dynamics of information transmission. To test for individual recognition, we trained subjects to associate green illumination with the provision of a food reward close to one of two conspecifics, and, for comparison, one of two physical landmarks. Both species were capable of recognizing the rewarded landmark, but neither showed a preference for associating with the rewarded conspecific. Our study provides no evidence for individual recognition in either species. We speculate that the fission–fusion structure of their social groups may not favour a capacity for individual recognition.
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Salthouse, Timothy A., and Karen L. Siedlecki. "An Individual Difference Analysis of False Recognition." American Journal of Psychology 120, no. 3 (October 1, 2007): 429. http://dx.doi.org/10.2307/20445413.

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Yom-Tov, Yoram. "Seemingly Maladaptive Behaviours, Individual Recognition and Hierarchy." Ornis Scandinavica 20, no. 2 (May 1989): 159. http://dx.doi.org/10.2307/3676886.

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Li, Jingguang, Moqian Tian, Huizhen Fang, Miao Xu, He Li, and Jia Liu. "Extraversion predicts individual differences in face recognition." Communicative & Integrative Biology 3, no. 4 (July 2010): 295–98. http://dx.doi.org/10.4161/cib.3.4.12093.

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Hirvonen, Onni. "Democratic institutions and recognition of individual identities." Thesis Eleven 134, no. 1 (June 2016): 28–41. http://dx.doi.org/10.1177/0725513616646023.

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Palermo, Romina, Marianne Thorburn, Ellen Bothe, Laura Engfors, Amber King, Kaitlyn Turbett, Xujia Wang, Prue Watson, and Linda Jeffery. "Individual differences in children's face recognition abilities." Journal of Vision 17, no. 10 (August 31, 2017): 996. http://dx.doi.org/10.1167/17.10.996.

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King, Sandra, and Dave M. Nicol. "Organizational enhancement through recognition of individual spirituality." Journal of Organizational Change Management 12, no. 3 (June 1999): 234–43. http://dx.doi.org/10.1108/09534819910274026.

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Crook †, R., B. W. Patullo, and D. L. Macmillan. "Multimodal individual recognition in the crayfishcherax destructor." Marine and Freshwater Behaviour and Physiology 37, no. 4 (December 2004): 271–85. http://dx.doi.org/10.1080/10236240400016595.

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Takaragi, K., M. Usami, R. Imura, R. Itsuki, and T. Satoh. "An ultra small individual recognition security chip." IEEE Micro 21, no. 6 (2001): 43–49. http://dx.doi.org/10.1109/40.977757.

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Han, Joong Soo, and Eul Gyu Im. "Implementation of Individual Gait Recognition using RNN." KIISE Transactions on Computing Practices 24, no. 7 (July 31, 2018): 358–62. http://dx.doi.org/10.5626/ktcp.2018.24.7.358.

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Han, Ju, and Bir Bhanu. "Performance prediction for individual recognition by gait." Pattern Recognition Letters 26, no. 5 (April 2005): 615–24. http://dx.doi.org/10.1016/j.patrec.2004.09.011.

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39

Crowley, Philip H., Louis Provencher, Sarah Sloane, Lee Alan Dugatkin, Bryan Spohn, Lock Rogers, and Michael Alfieri. "Evolving cooperation: the role of individual recognition." Biosystems 37, no. 1-2 (January 1996): 49–66. http://dx.doi.org/10.1016/0303-2647(95)01546-9.

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Haines, Maresah. "Call for team recognition of individual merit." Primary Health Care 2, no. 2 (February 1992): 6. http://dx.doi.org/10.7748/phc.2.2.6.s7.

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41

Brennan, Peter A., and Keith M. Kendrick. "Mammalian social odours: attraction and individual recognition." Philosophical Transactions of the Royal Society B: Biological Sciences 361, no. 1476 (November 8, 2006): 2061–78. http://dx.doi.org/10.1098/rstb.2006.1931.

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Mammalian social systems rely on signals passed between individuals conveying information including sex, reproductive status, individual identity, ownership, competitive ability and health status. Many of these signals take the form of complex mixtures of molecules sensed by chemosensory systems and have important influences on a variety of behaviours that are vital for reproductive success, such as parent–offspring attachment, mate choice and territorial marking. This article aims to review the nature of these chemosensory cues and the neural pathways mediating their physiological and behavioural effects. Despite the complexities of mammalian societies, there are instances where single molecules can act as classical pheromones attracting interest and approach behaviour. Chemosignals with relatively high volatility can be used to signal at a distance and are sensed by the main olfactory system. Most mammals also possess a vomeronasal system, which is specialized to detect relatively non-volatile chemosensory cues following direct contact. Single attractant molecules are sensed by highly specific receptors using a labelled line pathway. These act alongside more complex mixtures of signals that are required to signal individual identity. There are multiple sources of such individuality chemosignals, based on the highly polymorphic genes of the major histocompatibility complex (MHC) or lipocalins such as the mouse major urinary proteins. The individual profile of volatile components that make up an individual odour signature can be sensed by the main olfactory system, as the pattern of activity across an array of broadly tuned receptor types. In addition, the vomeronasal system can respond highly selectively to non-volatile peptide ligands associated with the MHC, acting at the V2r class of vomeronasal receptor. The ability to recognize individuals or their genetic relatedness plays an important role in mammalian social behaviour. Thus robust systems for olfactory learning and recognition of chemosensory individuality have evolved, often associated with major life events, such as mating, parturition or neonatal development. These forms of learning share common features, such as increased noradrenaline evoked by somatosensory stimulation, which results in neural changes at the level of the olfactory bulb. In the main olfactory bulb, these changes are likely to refine the pattern of activity in response to the learned odour, enhancing its discrimination from those of similar odours. In the accessory olfactory bulb, memory formation is hypothesized to involve a selective inhibition, which disrupts the transmission of the learned chemosignal from the mating male. Information from the main olfactory and vomeronasal systems is integrated at the level of the corticomedial amygdala, which forms the most important pathway by which social odours mediate their behavioural and physiological effects. Recent evidence suggests that this region may also play an important role in the learning and recognition of social chemosignals.
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Fischer, Julia. "Emergence of individual recognition in young macaques." Animal Behaviour 67, no. 4 (April 2004): 655–61. http://dx.doi.org/10.1016/j.anbehav.2003.08.006.

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Cotton, Samuel. "Individual Recognition: Mice, MUPs and the MHC." Current Biology 17, no. 22 (November 2007): R971—R973. http://dx.doi.org/10.1016/j.cub.2007.09.024.

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KARAVANICH, CHRISTA, and JELLE ATEMA. "Individual recognition and memory in lobster dominance." Animal Behaviour 56, no. 6 (December 1998): 1553–60. http://dx.doi.org/10.1006/anbe.1998.0914.

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Jenkins, Ryan, Josh P. Davis, Claire Monks, and Stella Tsermentseli. "Individual differences in face and voice recognition." Cognitive Psychology Bulletin 1, no. 6 (2021): 60–62. http://dx.doi.org/10.53841/bpscog.2021.1.6.60.

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46

Wang, Qi, and Changchun Bao. "Individual Violin Recognition Method Combining Tonal and Nontonal Features." Electronics 9, no. 6 (June 8, 2020): 950. http://dx.doi.org/10.3390/electronics9060950.

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Individual recognition among instruments of the same type is a challenging problem and it has been rarely investigated. In this study, the individual recognition of violins is explored. Based on the source–filter model, the spectrum can be divided into tonal content and nontonal content, which reflects the timbre from complementary aspects. The tonal/nontonal gammatone frequency cepstral coefficients (GFCC) are combined to describe the corresponding spectrum contents in this study. In the recognition system, Gaussian mixture models–universal background model (GMM–UBM) is employed to parameterize the distribution of the combined features. In order to evaluate the recognition task of violin individuals, a solo dataset including 86 violins is developed in this study. Compared with other features, the combined features show a better performance in both individual violin recognition and violin grade classification. Experimental results also show the GMM–UBM outperforms the CNN, especially when the training data are limited. Finally, the effect of players on the individual violin recognition is investigated.
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47

Townsend, Simon W., Colin Allen, and Marta B. Manser. "A simple test of vocal individual recognition in wild meerkats." Biology Letters 8, no. 2 (October 12, 2011): 179–82. http://dx.doi.org/10.1098/rsbl.2011.0844.

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Individual recognition is thought to be a crucial ability facilitating the evolution of animal societies. Given its central importance, much research has addressed the extent of this capacity across the animal kingdom. Recognition of individuals vocally has received particular attention due, in part, to the insights it provides regarding the cognitive processes that underlie this skill. While much work has focused on vocal individual recognition in primates, there is currently very little data showing comparable skills in non-primate mammals under natural conditions. This may be because non-primate mammal societies do not provide obvious contexts in which vocal individual recognition can be rigorously tested. We addressed this gap in understanding by designing an experimental paradigm to test for individual recognition in meerkats ( Suricata suricatta ) without having to rely on naturally occurring social contexts. Results suggest that when confronted with a physically impossible scenario—the presence of the same conspecific meerkat in two different places—subjects responded more strongly than during the control, a physically possible setup. We argue that this provides the first clear evidence for vocal individual recognition in wild non-primate mammals and hope that this novel experimental design will allow more systematic cross-species comparisons of individual recognition under natural settings.
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48

Ardila, A. "People Recognition: A Historical/Anthropological Perspective." Behavioural Neurology 6, no. 2 (1993): 99–105. http://dx.doi.org/10.1155/1993/169342.

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Using current neurological and neuropsychological literature, and the analysis of different cultural and historical conditions, people recognition is analyzed. Different “subsystems” or “modules” could be involved in individuals' recognition: living versus non-living, own species versus other species, familiar versus non-familiar, males versus females, and individual identification versus emotional identification. Not only visual, but also auditory and even olfactory information may be involved in people recognition. Visual information involved in people recognition is proposed to include not only the perception of faces, but also the perception of whole body and gait, clothes, emotional expressions, and individual marks.
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Tibbetts, Elizabeth A., Christian Cely Ortiz, Giorgia G. Auteri, Meagan Simons, Michelle L. Fearon, and L. Lacey Knowles. "Individual recognition and individual identity signals in Polistes fuscatus wasps vary geographically." Animal Behaviour 176 (June 2021): 87–98. http://dx.doi.org/10.1016/j.anbehav.2021.03.018.

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Zhang, Tianxiang, and Gentiane Venture. "Individual Recognition from Gait Using Feature Value Method." Cybernetics and Information Technologies 12, no. 3 (September 1, 2012): 86–95. http://dx.doi.org/10.2478/cait-2012-0024.

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Abstract:
Abstract We propose a novel framework to recognize individuals from gait, in order to improve HRI. We collected the motion data of the torso from 13 persons’ gait, using 2 IMU sensors. We developed Feature Value Method which is a PCA based classifier and we achieved an average individual recognition rate of 94% through cross-validation.
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