메뉴 건너뛰기




Volumn 87, Issue 3, 2018, Pages 533-545

A computer vision for animal ecology

Author keywords

automation; camera traps; ecological monitoring; images; unmanned aerial vehicles

Indexed keywords

AUTOMATION; COMPUTER VISION; ENVIRONMENTAL MONITORING; EQUIPMENT; IMAGE ANALYSIS; POPULATION BOTTLENECK; SPATIOTEMPORAL ANALYSIS; UNMANNED VEHICLE;

EID: 85036508051     PISSN: 00218790     EISSN: 13652656     Source Type: Journal    
DOI: 10.1111/1365-2656.12780     Document Type: Review
Times cited : (299)

References (96)
  • 2
    • 77954560622 scopus 로고    scopus 로고
    • Automating image matching, cataloging, and analysis for photo-identification research
    • Adams, J. D., Speakman, T., Zolman, E., & Schwacke, L. H. (2006). Automating image matching, cataloging, and analysis for photo-identification research. Aquatic Mammals, 32, 374–384. https://doi.org/10.1578/AM.32.3.2006.374
    • (2006) Aquatic Mammals , vol.32 , pp. 374-384
    • Adams, J.D.1    Speakman, T.2    Zolman, E.3    Schwacke, L.H.4
  • 3
    • 38949156211 scopus 로고    scopus 로고
    • Identifying elephant photos by multi-curve matching
    • Ardovini, A., Cinque, L., & Sangineto, E. (2008). Identifying elephant photos by multi-curve matching. Pattern Recognition, 41, 1867–1877. https://doi.org/10.1016/j.patcog.2007.11.010
    • (2008) Pattern Recognition , vol.41 , pp. 1867-1877
    • Ardovini, A.1    Cinque, L.2    Sangineto, E.3
  • 4
    • 31344449844 scopus 로고    scopus 로고
    • An astronomical pattern-matching algorithm for computer-aided identification of whale sharks Rhincodon typus
    • Arzoumanian, Z., Holmberg, J., & Norman, B. (2005). An astronomical pattern-matching algorithm for computer-aided identification of whale sharks Rhincodon typus. Journal of Applied Ecology, 42, 999–1011. https://doi.org/10.1111/j.1365-2664.2005.01117.x
    • (2005) Journal of Applied Ecology , vol.42 , pp. 999-1011
    • Arzoumanian, Z.1    Holmberg, J.2    Norman, B.3
  • 5
    • 84941795876 scopus 로고    scopus 로고
    • Automatic classification of flying bird species using computer vision techniques
    • Atanbori, J., Duan, W., Murray, J., Appiah, K., & Dickinson, P. (2016). Automatic classification of flying bird species using computer vision techniques. Pattern Recognition Letters, 81, 53–62. https://doi.org/10.1016/j.patrec.2015.08.015
    • (2016) Pattern Recognition Letters , vol.81 , pp. 53-62
    • Atanbori, J.1    Duan, W.2    Murray, J.3    Appiah, K.4    Dickinson, P.5
  • 6
    • 34948910166 scopus 로고    scopus 로고
    • Estimating the relative abundance of emperor penguins at inaccessible colonies using satellite imagery
    • Barber-Meyer, S. M., Kooyman, G. L., & Ponganis, P. J. (2007). Estimating the relative abundance of emperor penguins at inaccessible colonies using satellite imagery. Polar Biology, 30, 1565–1570. https://doi.org/10.1007/s00300-007-0317-8
    • (2007) Polar Biology , vol.30 , pp. 1565-1570
    • Barber-Meyer, S.M.1    Kooyman, G.L.2    Ponganis, P.J.3
  • 7
    • 84978699318 scopus 로고    scopus 로고
    • Quick, accurate, smart: 3D computer vision technology helps assessing confined animals’ behaviour
    • Barnard, S., Calderara, S., Pistocchi, S., Cucchiara, R., Podaliri-Vulpiani, M., Messori, S., & Ferri, N. (2016). Quick, accurate, smart: 3D computer vision technology helps assessing confined animals’ behaviour. PLoS ONE, 11, 1–20. https://doi.org/10.1371/journal.pone.0158748
    • (2016) PLoS ONE , vol.11 , pp. 1-20
    • Barnard, S.1    Calderara, S.2    Pistocchi, S.3    Cucchiara, R.4    Podaliri-Vulpiani, M.5    Messori, S.6    Ferri, N.7
  • 9
    • 38949209605 scopus 로고    scopus 로고
    • Comparison of two computer-assisted photo-identification methods applied to sperm whales (Physeter macrocephalus)
    • Beekmans, B. W. P. M., Whitehead, H., Huele, R., Steiner, L., & Steenbeek, A. G. (2005). Comparison of two computer-assisted photo-identification methods applied to sperm whales (Physeter macrocephalus). Aquatic Mammals, 31, 243–247. https://doi.org/10.1578/AM.31.2.2005.243
    • (2005) Aquatic Mammals , vol.31 , pp. 243-247
    • Beekmans, B.W.P.M.1    Whitehead, H.2    Huele, R.3    Steiner, L.4    Steenbeek, A.G.5
  • 10
    • 84962476685 scopus 로고    scopus 로고
    • Improving automated annotation of benthic survey images using wide-band fluorescence
    • Beijboom, O., Treibitz, T., Kline, D. I., Eyal, G., Khen, A., Neal, B., … Kriegman, D. (2016). Improving automated annotation of benthic survey images using wide-band fluorescence. Scientific Reports, 6, 23166. https://doi.org/10.1038/srep23166
    • (2016) Scientific Reports , vol.6 , pp. 23166
    • Beijboom, O.1    Treibitz, T.2    Kline, D.I.3    Eyal, G.4    Khen, A.5    Neal, B.6    Kriegman, D.7
  • 11
    • 84961635328 scopus 로고    scopus 로고
    • Visipedia circa 2015
    • Belongie, S., & Perona, P. (2016). Visipedia circa 2015. Pattern Recognition Letters, 72, 15–24. https://doi.org/10.1016/j.patrec.2015.11.023
    • (2016) Pattern Recognition Letters , vol.72 , pp. 15-24
    • Belongie, S.1    Perona, P.2
  • 15
    • 84872498657 scopus 로고    scopus 로고
    • A computer-assisted system for photographic mark-recapture analysis
    • Bolger, D. T., Morrison, T. A., Vance, B., Lee, D., & Farid, H. (2012). A computer-assisted system for photographic mark-recapture analysis. Methods in Ecology and Evolution, 3, 813–822. https://doi.org/10.1111/j.2041-210X.2012.00212.x
    • (2012) Methods in Ecology and Evolution , vol.3 , pp. 813-822
    • Bolger, D.T.1    Morrison, T.A.2    Vance, B.3    Lee, D.4    Farid, H.5
  • 17
    • 0242483561 scopus 로고    scopus 로고
    • The OpenCV Library
    • Bradski, G. (2000). The OpenCV Library. Dr Dobbs Journal, 25, 120–126.
    • (2000) Dr Dobbs Journal , vol.25 , pp. 120-126
    • Bradski, G.1
  • 19
    • 78149300909 scopus 로고    scopus 로고
    • #x0026;,). Visual recognition with humans in the loop. In, Daniilidis K., Maragos P., Paragios N., (eds), Computer Vision - ECCV 2010. ECCV 2010, Lecture Notes in Computer Science, vol 6314., Berlin, Germany, Springer
    • Branson, S., Wah, C., Schroff, F., Babenko, B., Welinder, P., Perona, P., & Belongie, S. (2010). Visual recognition with humans in the loop. In Daniilidis K., Maragos P., Paragios N. (eds) Computer Vision - ECCV 2010. ECCV 2010. Lecture Notes in Computer Science, vol 6314. Berlin, Germany: Springer.
    • (2010)
    • Branson, S.1    Wah, C.2    Schroff, F.3    Babenko, B.4    Welinder, P.5    Perona, P.6    Belongie, S.7
  • 20
    • 84990188988 scopus 로고    scopus 로고
    • Computer-automated bird detection and counts in high-resolution aerial images: A review
    • Chabot, D., & Francis, C. M. (2016). Computer-automated bird detection and counts in high-resolution aerial images: A review. Journal of Field Ornithology, 87, 343–359. https://doi.org/10.1111/jofo.12171
    • (2016) Journal of Field Ornithology , vol.87 , pp. 343-359
    • Chabot, D.1    Francis, C.M.2
  • 22
    • 84995549583 scopus 로고    scopus 로고
    • DeepAnomaly: Combining background subtraction and deep learning for detecting obstacles and anomalies in an agricultural field
    • Christiansen, P., Nielsen, L., Steen, K., Jørgensen, R., & Karstoft, H. (2016). DeepAnomaly: Combining background subtraction and deep learning for detecting obstacles and anomalies in an agricultural field. Sensors, 16, 1904. https://doi.org/10.3390/s16111904
    • (2016) Sensors , vol.16 , pp. 1904
    • Christiansen, P.1    Nielsen, L.2    Steen, K.3    Jørgensen, R.4    Karstoft, H.5
  • 24
    • 84920995476 scopus 로고    scopus 로고
    • Pattern-recognition software as a supplemental method of identifying individual eastern box turtles (Terrapene c. carolina)
    • Cross, M. D., Lipps, G. J., Sapak, J. M., Tobin, E. J., & Root, K. V. (2014). Pattern-recognition software as a supplemental method of identifying individual eastern box turtles (Terrapene c. carolina). Herpetological Review, 45, 584–586.
    • (2014) Herpetological Review , vol.45 , pp. 584-586
    • Cross, M.D.1    Lipps, G.J.2    Sapak, J.M.3    Tobin, E.J.4    Root, K.V.5
  • 25
    • 85016400118 scopus 로고    scopus 로고
    • The future of UAVs in ecology: An insider perspective from the Silicon Valley drone industry
    • Crutsinger, G. M., Short, J., & Sollenberger, R. (2016). The future of UAVs in ecology: An insider perspective from the Silicon Valley drone industry. Journal of Unmanned Vehicle Systems, 4, 161–168. https://doi.org/10.1139/juvs-2016-0008
    • (2016) Journal of Unmanned Vehicle Systems , vol.4 , pp. 161-168
    • Crutsinger, G.M.1    Short, J.2    Sollenberger, R.3
  • 26
    • 84962361060 scopus 로고    scopus 로고
    • Photo-identification as a technique for recognition of individual fish: A test with the freshwater armored catfish Rineloricaria aequalicuspis Reis & Cardoso, 2001 (Siluriformes: Loricariidae)
    • Dala-Corte, R. B., Moschetta, J. B., & Becker, F. G. (2016). Photo-identification as a technique for recognition of individual fish: A test with the freshwater armored catfish Rineloricaria aequalicuspis Reis & Cardoso, 2001 (Siluriformes: Loricariidae). Neotropical Ichthyology, 14, e150074.
    • (2016) Neotropical Ichthyology , vol.14
    • Dala-Corte, R.B.1    Moschetta, J.B.2    Becker, F.G.3
  • 28
    • 79961099231 scopus 로고    scopus 로고
    • An automatic counter for aerial images of aggregations of large birds
    • Descamps, S., Béchet, A., Descombes, X., Arnaud, A., & Zerubia, J. (2011). An automatic counter for aerial images of aggregations of large birds. Bird Study, 58, 302–308. https://doi.org/10.1080/00063657.2011.588195
    • (2011) Bird Study , vol.58 , pp. 302-308
    • Descamps, S.1    Béchet, A.2    Descombes, X.3    Arnaud, A.4    Zerubia, J.5
  • 30
    • 84920641210 scopus 로고    scopus 로고
    • Sloop: A pattern retrieval engine for individual animal identification
    • Duyck, J., Finn, C., Hutcheon, A., Vera, P., Salas, J., & Ravela, S. (2015). Sloop: A pattern retrieval engine for individual animal identification. Pattern Recognition, 48, 1055–1069.
    • (2015) Pattern Recognition , vol.48 , pp. 1055-1069
    • Duyck, J.1    Finn, C.2    Hutcheon, A.3    Vera, P.4    Salas, J.5    Ravela, S.6
  • 32
    • 84955103729 scopus 로고    scopus 로고
    • Machine vision automated species identification scaled towards production levels
    • Favret, C., & Sieracki, J. M. (2016). Machine vision automated species identification scaled towards production levels. Systematic Entomology, 41, 133–143. https://doi.org/10.1111/syen.12146
    • (2016) Systematic Entomology , vol.41 , pp. 133-143
    • Favret, C.1    Sieracki, J.M.2
  • 33
    • 84955740964 scopus 로고    scopus 로고
    • A software system for automated identification and retrieval of moth images based on wing attributes
    • Feng, L., Bhanu, B., & Heraty, J. (2016). A software system for automated identification and retrieval of moth images based on wing attributes. Pattern Recognition, 51, 225–241. https://doi.org/10.1016/j.patcog.2015.09.012
    • (2016) Pattern Recognition , vol.51 , pp. 225-241
    • Feng, L.1    Bhanu, B.2    Heraty, J.3
  • 34
    • 84895725448 scopus 로고    scopus 로고
    • Whales from space: Counting southern right whales by satellite
    • Fretwell, P. T., Staniland, I. J., & Forcada, J. (2014). Whales from space: Counting southern right whales by satellite. PLoS ONE, 9, 1–9. https://doi.org/10.1371/journal.pone.0088655
    • (2014) PLoS ONE , vol.9 , pp. 1-9
    • Fretwell, P.T.1    Staniland, I.J.2    Forcada, J.3
  • 38
    • 80052170423 scopus 로고    scopus 로고
    • Using object-based analysis of image data to count birds: Mapping of Lesser Flamingos at Kamfers Dam, Northern Cape, South Africa
    • Groom, G., Krag Petersen, I., Anderson, M. D., & Fox, A. D. (2011). Using object-based analysis of image data to count birds: Mapping of Lesser Flamingos at Kamfers Dam, Northern Cape, South Africa. International Journal of Remote Sensing, 32, 4611–4639. https://doi.org/10.1080/01431161.2010.489068
    • (2011) International Journal of Remote Sensing , vol.32 , pp. 4611-4639
    • Groom, G.1    Krag Petersen, I.2    Anderson, M.D.3    Fox, A.D.4
  • 40
    • 84911367832 scopus 로고    scopus 로고
    • Automatic identification of species with neural networks
    • Hernández-Serna, A., & Jiménez-Segura, L. F. (2014). Automatic identification of species with neural networks. PeerJ, 2, e563. https://doi.org/10.7717/peerj.563
    • (2014) PeerJ , vol.2
    • Hernández-Serna, A.1    Jiménez-Segura, L.F.2
  • 41
    • 84891951996 scopus 로고    scopus 로고
    • Unmanned aerial vehicles (UAVs) for surveying Marine Fauna: A dugong case study
    • Hodgson, A., Kelly, N., & Peel, D. (2013). Unmanned aerial vehicles (UAVs) for surveying Marine Fauna: A dugong case study. PLoS ONE, 8, 1–15.
    • (2013) PLoS ONE , vol.8 , pp. 1-15
    • Hodgson, A.1    Kelly, N.2    Peel, D.3
  • 44
    • 48449104643 scopus 로고    scopus 로고
    • A 3D modeling method to calculate the surface areas of coral branches
    • Jones, A. M., Cantin, N. E., Berkelmans, R., Sinclair, B., & Negri, A. P. (2008). A 3D modeling method to calculate the surface areas of coral branches. Coral Reefs, 27, 521–526. https://doi.org/10.1007/s00338-008-0354-y
    • (2008) Coral Reefs , vol.27 , pp. 521-526
    • Jones, A.M.1    Cantin, N.E.2    Berkelmans, R.3    Sinclair, B.4    Negri, A.P.5
  • 45
    • 85016617280 scopus 로고    scopus 로고
    • Season spotter: Using citizen science to validate and scale plant phenology from near-surface remote sensing
    • Kosmala, M., Crall, A., Cheng, R., Hufkens, K., Henderson, S., & Richardson, A. (2016). Season spotter: Using citizen science to validate and scale plant phenology from near-surface remote sensing. Remote Sensing, 8, 726. https://doi.org/10.3390/rs8090726
    • (2016) Remote Sensing , vol.8 , pp. 726
    • Kosmala, M.1    Crall, A.2    Cheng, R.3    Hufkens, K.4    Henderson, S.5    Richardson, A.6
  • 46
    • 84879461913 scopus 로고    scopus 로고
    • Animal biometrics: Quantifying and detecting phenotypic appearance
    • Kühl, H. S., & Burghardt, T. (2013). Animal biometrics: Quantifying and detecting phenotypic appearance. Trends in Ecology and Evolution, 28, 432–441. https://doi.org/10.1016/j.tree.2013.02.013
    • (2013) Trends in Ecology and Evolution , vol.28 , pp. 432-441
    • Kühl, H.S.1    Burghardt, T.2
  • 47
    • 77949523520 scopus 로고    scopus 로고
    • Bisque: A platform for bioimage analysis and management
    • Kvilekval, K., Fedorov, D., Obara, B., Singh, A., & Manjunath, B. S. (2009). Bisque: A platform for bioimage analysis and management. Bioinformatics, 26, 544–552. https://doi.org/10.1093/bioinformatics/btp699
    • (2009) Bioinformatics , vol.26 , pp. 544-552
    • Kvilekval, K.1    Fedorov, D.2    Obara, B.3    Singh, A.4    Manjunath, B.S.5
  • 48
    • 84995799442 scopus 로고    scopus 로고
    • Feasibility of using high-resolution satellite imagery to assess vertebrate wildlife populations
    • LaRue, M. A., Stapleton, S., & Anderson, M. (2016). Feasibility of using high-resolution satellite imagery to assess vertebrate wildlife populations. Conservation Biology, 31, 213–220. https://doi.org/10.1111/cobi.12809
    • (2016) Conservation Biology , vol.31 , pp. 213-220
    • LaRue, M.A.1    Stapleton, S.2    Anderson, M.3
  • 49
    • 84962226538 scopus 로고    scopus 로고
    • Testing methods for using high-resolution satellite imagery to monitor polar bear abundance and distribution
    • LaRue, M. A., Stapleton, S., Porter, C., Atkinson, S., Atwood, T., Dyck, M., & Lecomte, N. (2015). Testing methods for using high-resolution satellite imagery to monitor polar bear abundance and distribution. Wildlife Society Bulletin, 39, 772–779. https://doi.org/10.1002/wsb.596
    • (2015) Wildlife Society Bulletin , vol.39 , pp. 772-779
    • LaRue, M.A.1    Stapleton, S.2    Porter, C.3    Atkinson, S.4    Atwood, T.5    Dyck, M.6    Lecomte, N.7
  • 50
    • 84929311154 scopus 로고    scopus 로고
    • A quick, easy and non-intrusive method for underwater volume and surface area evaluation of benthic organisms by 3D computer modelling
    • Lavy, A., Eyal, G., Neal, B., Keren, R., Loya, Y., & Ilan, M. (2015). A quick, easy and non-intrusive method for underwater volume and surface area evaluation of benthic organisms by 3D computer modelling. Methods in Ecology and Evolution, 6, 521–531. https://doi.org/10.1111/2041-210X.12331
    • (2015) Methods in Ecology and Evolution , vol.6 , pp. 521-531
    • Lavy, A.1    Eyal, G.2    Neal, B.3    Keren, R.4    Loya, Y.5    Ilan, M.6
  • 51
    • 84930630277 scopus 로고    scopus 로고
    • Deep learning
    • LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521, 436–444. https://doi.org/10.1038/nature14539
    • (2015) Nature , vol.521 , pp. 436-444
    • LeCun, Y.1    Bengio, Y.2    Hinton, G.3
  • 52
    • 84979211514 scopus 로고    scopus 로고
    • Mate choice and body pattern variations in the Crown Butterfly fish Chaetodon paucifasciatus (Chaetodontidae)
    • Levy, K., Lerner, A., & Shashar, N. (2014). Mate choice and body pattern variations in the Crown Butterfly fish Chaetodon paucifasciatus (Chaetodontidae). Biology Open, 3, 1245–1251. https://doi.org/10.1242/bio.20149175
    • (2014) Biology Open , vol.3 , pp. 1245-1251
    • Levy, K.1    Lerner, A.2    Shashar, N.3
  • 53
    • 84945901544 scopus 로고    scopus 로고
    • Supporting the annual international black-faced spoonbill census with a low-cost unmanned aerial vehicle
    • Liu, C. C., Chen, Y. H., & Wen, H. L. (2015). Supporting the annual international black-faced spoonbill census with a low-cost unmanned aerial vehicle. Ecological Informatics, 30, 170–178. https://doi.org/10.1016/j.ecoinf.2015.10.008
    • (2015) Ecological Informatics , vol.30 , pp. 170-178
    • Liu, C.C.1    Chen, Y.H.2    Wen, H.L.3
  • 54
    • 84860215915 scopus 로고    scopus 로고
    • Detection, differentiation, and abundance estimation of penguin species by high-resolution satellite imagery
    • Lynch, H. J., White, R., Black, A. D., & Naveen, R. (2012). Detection, differentiation, and abundance estimation of penguin species by high-resolution satellite imagery. Polar Biology, 35, 963–968. https://doi.org/10.1007/s00300-011-1138-3
    • (2012) Polar Biology , vol.35 , pp. 963-968
    • Lynch, H.J.1    White, R.2    Black, A.D.3    Naveen, R.4
  • 57
    • 85036462657 scopus 로고    scopus 로고
    • Classification of wild animals based on SVM and local descriptors
    • Matuska, S., Hudec, R., Kamencay, P., Benco, M., & Zachariasova, M. (2014). Classification of wild animals based on SVM and local descriptors. AASRI Procedia, 9, 25–30. https://doi.org/10.1016/j.aasri.2014.09.006
    • (2014) AASRI Procedia , vol.9 , pp. 25-30
    • Matuska, S.1    Hudec, R.2    Kamencay, P.3    Benco, M.4    Zachariasova, M.5
  • 58
    • 85009423566 scopus 로고    scopus 로고
    • Ultra-fine scale spatially-integrated mapping of habitat and occupancy using structure
    • McDowall, P., & Lynch, H. J. (2017). Ultra-fine scale spatially-integrated mapping of habitat and occupancy using structure. PLoS ONE, 12, 1–16. https://doi.org/10.1371/journal.pone.0166773
    • (2017) PLoS ONE , vol.12 , pp. 1-16
    • McDowall, P.1    Lynch, H.J.2
  • 59
    • 84988564472 scopus 로고    scopus 로고
    • Using deep learning for image-based plant disease detection
    • Mohanty, S. P., Hughes, D. P., & Salathé, M. (2016). Using deep learning for image-based plant disease detection. Frontiers in Plant Science, 7, 1–7. https://doi.org/10.3389/fpls.2016.01419
    • (2016) Frontiers in Plant Science , vol.7 , pp. 1-7
    • Mohanty, S.P.1    Hughes, D.P.2    Salathé, M.3
  • 60
    • 59449092318 scopus 로고    scopus 로고
    • Coral surface area quantification-evaluation of established techniques by comparison with computer tomography
    • Naumann, M. S., Niggl, W., Laforsch, C., Glaser, C., & Wild, C. (2009). Coral surface area quantification-evaluation of established techniques by comparison with computer tomography. Coral Reefs, 28, 109–117. https://doi.org/10.1007/s00338-008-0459-3
    • (2009) Coral Reefs , vol.28 , pp. 109-117
    • Naumann, M.S.1    Niggl, W.2    Laforsch, C.3    Glaser, C.4    Wild, C.5
  • 61
    • 84925270506 scopus 로고    scopus 로고
    • StereoMorph: An R package for the collection of 3D landmarks and curves using a stereo camera set-up
    • Olsen, A. M., & Westneat, M. W. (2015). StereoMorph: An R package for the collection of 3D landmarks and curves using a stereo camera set-up. Methods in Ecology and Evolution, 6, 351–356. https://doi.org/10.1111/2041-210X.12326
    • (2015) Methods in Ecology and Evolution , vol.6 , pp. 351-356
    • Olsen, A.M.1    Westneat, M.W.2
  • 62
    • 84877910050 scopus 로고    scopus 로고
    • Implementing image analysis in laboratory-based experimental systems for ecology and evolution: A hands-on guide
    • Pennekamp, F., & Schtickzelle, N. (2013). Implementing image analysis in laboratory-based experimental systems for ecology and evolution: A hands-on guide. Methods in Ecology and Evolution, 4, 483–492. https://doi.org/10.1111/2041-210X.12036
    • (2013) Methods in Ecology and Evolution , vol.4 , pp. 483-492
    • Pennekamp, F.1    Schtickzelle, N.2
  • 65
    • 84949678222 scopus 로고    scopus 로고
    • DeepFish: Accurate underwater live fish recognition with a deep architecture
    • Qin, H., Li, X., Liang, J., Peng, Y., & Zhang, C. (2016). DeepFish: Accurate underwater live fish recognition with a deep architecture. Neurocomputing, 187, 49–58. https://doi.org/10.1016/j.neucom.2015.10.122
    • (2016) Neurocomputing , vol.187 , pp. 49-58
    • Qin, H.1    Li, X.2    Liang, J.3    Peng, Y.4    Zhang, C.5
  • 66
    • 84894337235 scopus 로고    scopus 로고
    • A human-computer collaborative workflow for the acquisition and analysis of terrestrial insect movement in behavioral field studies
    • Reda, K., Mateevitsi, V., & Offord, C. (2013). A human-computer collaborative workflow for the acquisition and analysis of terrestrial insect movement in behavioral field studies. EURASIP Journal on Image and Video Processing, 2013, 48. https://doi.org/10.1186/1687-5281-2013-48
    • (2013) EURASIP Journal on Image and Video Processing , vol.2013 , pp. 48
    • Reda, K.1    Mateevitsi, V.2    Offord, C.3
  • 69
    • 85016136995 scopus 로고    scopus 로고
    • Automated detection and enumeration of marine wildlife using unmanned aircraft systems (UAS) and thermal imagery
    • Seymour, A. C., Dale, J., Hammill, M., Halpin, P. N., & Johnston, D. W. (2017). Automated detection and enumeration of marine wildlife using unmanned aircraft systems (UAS) and thermal imagery. Scientific Reports, 7, 1–10. https://doi.org/10.1038/srep45127
    • (2017) Scientific Reports , vol.7 , pp. 1-10
    • Seymour, A.C.1    Dale, J.2    Hammill, M.3    Halpin, P.N.4    Johnston, D.W.5
  • 70
    • 84898063054 scopus 로고    scopus 로고
    • A comprehensive review of background subtraction algorithms evaluated with synthetic and real videos
    • Sobral, A., & Vacavant, A. (2014). A comprehensive review of background subtraction algorithms evaluated with synthetic and real videos. Computer Vision and Image Understanding, 122, 4–21. https://doi.org/10.1016/j.cviu.2013.12.005
    • (2014) Computer Vision and Image Understanding , vol.122 , pp. 4-21
    • Sobral, A.1    Vacavant, A.2
  • 71
    • 0032634283 scopus 로고    scopus 로고
    • #x0026;, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE Comput. Soc.
    • Stauffer, C., & Grimson, W. E. L. (1999). Adaptive background mixture models for real-time tracking. Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 246–252. IEEE Comput. Soc.
    • (1999) Adaptive background mixture models for real-time tracking , pp. 246-252
    • Stauffer, C.1    Grimson, W.E.L.2
  • 72
    • 84910094067 scopus 로고    scopus 로고
    • Video-surveillance system for remote long-term in situ observations: Recording diel cavity use and behaviour of wild European lobsters (Homarus gammarus)
    • Steen, R., & Ski, S. (2014). Video-surveillance system for remote long-term in situ observations: Recording diel cavity use and behaviour of wild European lobsters (Homarus gammarus). Marine and Freshwater Research, 65, 1094–1101. https://doi.org/10.1071/MF13139
    • (2014) Marine and Freshwater Research , vol.65 , pp. 1094-1101
    • Steen, R.1    Ski, S.2
  • 73
    • 84902846907 scopus 로고    scopus 로고
    • Pattern recognition algorithm reveals how birds evolve individual egg pattern signatures
    • Stoddard, M. C., Kilner, R. M., & Town, C. (2014). Pattern recognition algorithm reveals how birds evolve individual egg pattern signatures. Nature Communications, 5, 4117.
    • (2014) Nature Communications , vol.5 , pp. 4117
    • Stoddard, M.C.1    Kilner, R.M.2    Town, C.3
  • 76
    • 84964474236 scopus 로고    scopus 로고
    • A generalized approach for producing, quantifying, and validating citizen science data from wildlife images
    • Swanson, A., Kosmala, M., Lintott, C., & Packer, C. (2016). A generalized approach for producing, quantifying, and validating citizen science data from wildlife images. Conservation Biology, 30, 520–531. https://doi.org/10.1111/cobi.12695
    • (2016) Conservation Biology , vol.30 , pp. 520-531
    • Swanson, A.1    Kosmala, M.2    Lintott, C.3    Packer, C.4
  • 77
    • 84937632029 scopus 로고    scopus 로고
    • Snapshot Serengeti, high-frequency annotated camera trap images of 40 mammalian species in an African savanna
    • Swanson, A., Kosmala, M., Lintott, C., Simpson, R., Smith, A., & Packer, C. (2015). Snapshot Serengeti, high-frequency annotated camera trap images of 40 mammalian species in an African savanna. Scientific Data, 2, 150026. https://doi.org/10.1038/sdata.2015.26
    • (2015) Scientific Data , vol.2 , pp. 150026
    • Swanson, A.1    Kosmala, M.2    Lintott, C.3    Simpson, R.4    Smith, A.5    Packer, C.6
  • 79
    • 84971475819 scopus 로고    scopus 로고
    • Assessing rotation-invariant feature classification for automated wildebeest population counts
    • Torney, C. J., Dobson, A. P., Borner, F., Lloyd-Jones, D. J., Moyer, D., Maliti, H. T., … Hopcraft, J. G. C. (2016). Assessing rotation-invariant feature classification for automated wildebeest population counts. PLoS ONE, 11, e0156342. https://doi.org/10.1371/journal.pone.0156342
    • (2016) PLoS ONE , vol.11
    • Torney, C.J.1    Dobson, A.P.2    Borner, F.3    Lloyd-Jones, D.J.4    Moyer, D.5    Maliti, H.T.6    Hopcraft, J.G.C.7
  • 80
    • 84886294712 scopus 로고    scopus 로고
    • Manta matcher: Automated photographic identification of manta rays using keypoint features
    • Town, C., Marshall, A., & Sethasathien, N. (2013). Manta matcher: Automated photographic identification of manta rays using keypoint features. Ecology and Evolution, 3, 1902–1914. https://doi.org/10.1002/ece3.587
    • (2013) Ecology and Evolution , vol.3 , pp. 1902-1914
    • Town, C.1    Marshall, A.2    Sethasathien, N.3
  • 81
    • 85009948953 scopus 로고    scopus 로고
    • Quantifying camouflage: How to predict detectability from appearance
    • Troscianko, J., Skelhorn, J., & Stevens, M. (2017). Quantifying camouflage: How to predict detectability from appearance. BMC Evolutionary Biology, 17, 7. https://doi.org/10.1186/s12862-016-0854-2
    • (2017) BMC Evolutionary Biology , vol.17 , pp. 7
    • Troscianko, J.1    Skelhorn, J.2    Stevens, M.3
  • 85
    • 84994409131 scopus 로고    scopus 로고
    • Coral reef fish detection and recognition in underwater videos by supervised machine learning: Comparison between deep learning and HOG+SVM methods
    • #x0026;, In, Blanc-Talon J., Distante C., Philips W., Popescu D., Scheunders P., (eds), Lecture Notes in Computer Science, vol 10016., Cham, Switzerland, Springer
    • Villon, S., Chaumont, M., Subsol, G., Villéger, S., Claverie, T., & Mouillot, D. (2016). Coral reef fish detection and recognition in underwater videos by supervised machine learning: Comparison between deep learning and HOG+SVM methods. In Blanc-Talon J., Distante C., Philips W., Popescu D., Scheunders P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2016. Lecture Notes in Computer Science, vol 10016. Cham, Switzerland: Springer.
    • (2016) Advanced Concepts for Intelligent Vision Systems. ACIVS 2016
    • Villon, S.1    Chaumont, M.2    Subsol, G.3    Villéger, S.4    Claverie, T.5    Mouillot, D.6
  • 86
    • 84925258744 scopus 로고    scopus 로고
    • MotionMeerkat: Integrating motion video detection and ecological monitoring
    • Weinstein, B. G. (2015). MotionMeerkat: Integrating motion video detection and ecological monitoring. Methods in Ecology and Evolution, 6, 357–362. https://doi.org/10.1111/2041-210X.12320
    • (2015) Methods in Ecology and Evolution , vol.6 , pp. 357-362
    • Weinstein, B.G.1
  • 87
    • 85045334242 scopus 로고    scopus 로고
    • Data from: A computer vision for animal ecology
    • Weinstein, B. G. (2017). Data from: A computer vision for animal ecology. Dryad Digital Repository, https://doi.org/10.5061/dryad.b700h
    • (2017) Dryad Digital Repository
    • Weinstein, B.G.1
  • 88
    • 85011700172 scopus 로고    scopus 로고
    • Persistent bill and corolla matching despite shifting temporal resources in tropical hummingbird-plant interactions
    • Weinstein, B. G., & Graham, C. H. (2017). Persistent bill and corolla matching despite shifting temporal resources in tropical hummingbird-plant interactions. Ecology Letters, 20, 326–335. https://doi.org/10.1111/ele.12730
    • (2017) Ecology Letters , vol.20 , pp. 326-335
    • Weinstein, B.G.1    Graham, C.H.2
  • 90
    • 84971489762 scopus 로고    scopus 로고
    • An object-based image analysis approach for detecting penguin guano in very high spatial resolution satellite images
    • Witharana, C., & Lynch, H. J. (2016). An object-based image analysis approach for detecting penguin guano in very high spatial resolution satellite images. Remote Sensing, 8, 375. https://doi.org/10.3390/rs8050375
    • (2016) Remote Sensing , vol.8 , pp. 375
    • Witharana, C.1    Lynch, H.J.2
  • 91
    • 84958768070 scopus 로고    scopus 로고
    • Do common cuckoos (Cuculus canorus) possess an optimal laying behaviour to match their own egg phenotype to that of their Oriental reed warbler (Acrocephalus orientalis) hosts?
    • Yang, C., Wang, L., Liang, W., & Møller, A. P. (2016). Do common cuckoos (Cuculus canorus) possess an optimal laying behaviour to match their own egg phenotype to that of their Oriental reed warbler (Acrocephalus orientalis) hosts? Biological Journal of the Linnean Society, 117, 422–427. https://doi.org/10.1111/bij.12690
    • (2016) Biological Journal of the Linnean Society , vol.117 , pp. 422-427
    • Yang, C.1    Wang, L.2    Liang, W.3    Møller, A.P.4
  • 94
    • 84938641231 scopus 로고    scopus 로고
    • Automated detection of elephants in wildlife video
    • Zeppelzauer, M. (2013). Automated detection of elephants in wildlife video. EURASIP Journal on Image and Video Processing, 2013, 46. https://doi.org/10.1186/1687-5281-2013-46
    • (2013) EURASIP Journal on Image and Video Processing , vol.2013 , pp. 46
    • Zeppelzauer, M.1
  • 95
    • 84988807081 scopus 로고    scopus 로고
    • Animal detection from highly cluttered natural scenes using spatiotemporal object region proposals and patch verification
    • Zhang, Z., He, Z., Cao, G., & Cao, W. (2016). Animal detection from highly cluttered natural scenes using spatiotemporal object region proposals and patch verification. IEEE Transactions on Multimedia, 18, 2079–2092. https://doi.org/10.1109/TMM.2016.2594138
    • (2016) IEEE Transactions on Multimedia , vol.18 , pp. 2079-2092
    • Zhang, Z.1    He, Z.2    Cao, G.3    Cao, W.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.