20.7.3.7.14 Wildlife Detection, Analysis

Chapter Contents (Back)
Wildlife. Animals. Application, Inspection.

Ardovini, A.[Alessandro], Cinque, L.[Luigi], Sangineto, E.[Enver],
Identifying elephant photos by multi-curve matching,
PR(41), No. 6, June 2008, pp. 1867-1877.
Elsevier DOI 0802
Elephant photo identification; Image retrieval by shape; Symmetric invariant multiple curve matching BibRef

Ardovini, A.[Alessandro], Cinque, L.[Luigi], Rocca, F.D.[Francesca Della], Sangineto, E.[Enver],
A Semi-automatic Approach to Photo Identification of Wild Elephants,
IbPRIA07(I: 225-232).
Springer DOI 0706
BibRef

Wawerla, J.[Jens], Marshall, S.[Shelley], Mori, G.[Greg], Rothley, K.[Kristina], Sabzmeydani, P.[Payam],
BearCam: automated wildlife monitoring at the arctic circle,
MVA(20), No. 5, July 2009, pp. xx-yy.
Springer DOI 0906
BibRef

Zhang, W.W.[Wei-Wei], Sun, J.[Jian], Tang, X.[Xiaoou],
From Tiger to Panda: Animal Head Detection,
IP(20), No. 6, June 2011, pp. 1696-1708.
IEEE DOI 1106
BibRef
Earlier:
Cat Head Detection: How to Effectively Exploit Shape and Texture Features,
ECCV08(IV: 802-816).
Springer DOI 0810
BibRef

Yong, S.P.[Suet-Peng], Deng, J.D.[Jeremiah D.], Purvis, M.K.[Martin K.],
Novelty detection in wildlife scenes through semantic context modelling,
PR(45), No. 9, September 2012, pp. 3439-3450.
Elsevier DOI 1206
BibRef
Earlier:
Modeling semantic context for key-frame extraction in wildlife video,
IVCNZ10(1-8).
IEEE DOI 1203
Novelty detection; Co-occurrence matrices; Semantic context; Multiple one-class models BibRef

Zeppelzauer, M.[Matthias],
Automated detection of elephants in wildlife video,
JIVP(2013), No. 1, 2013, pp. xx-yy.
DOI Link 1309
BibRef

Yu, X., Wang, J., Kays, R., Jansen, P.A., Wang, T., Huang, T.,
Automated identification of animal species in camera trap images,
JIVP(2013), No. 1, 2013, pp. 52.
DOI Link 1309
BibRef

Swanson, A.[Alexandra], Kosmala, M.[Margaret], Lintott, C.[Chris], Simpson, R.[Robert], Smith, A.[Arfon], Packer, C.[Craig],
Snapshot Serengeti, high-frequency annotated camera trap images of 40 mammalian species in an African savanna,
ScientificData(2), June 2015, Article 150026.
DOI Link 1506
Dataset, Animals. Covered by many news outlets. Thousands of pictures of animals from motion activated cameras planted in the Serengeti. Includes interface for people to identify, etc. A great resource for automated detection and identification. BibRef

Witharana, C.[Chandi], LaRue, M.A.[Michelle A.], Lynch, H.J.[Heather J.],
Benchmarking of data fusion algorithms in support of earth observation based Antarctic wildlife monitoring,
PandRS(113), No. 1, 2016, pp. 124-143.
Elsevier DOI 1602
Penguins BibRef

Le Blanc, G.[George], Francis, C.M.[Charles M.], Soffer, R.[Raymond], Kalacska, M.[Margaret], de Gea, J.[Julie],
Spectral Reflectance of Polar Bear and Other Large Arctic Mammal Pelts; Potential Applications to Remote Sensing Surveys,
RS(8), No. 4, 2016, pp. 273.
DOI Link 1604
BibRef

Wang, D.L.[Dong-Liang], Shao, Q.Q.[Quan-Qin], Yue, H.Y.[Huan-Yin],
Surveying Wild Animals from Satellites, Manned Aircraft and Unmanned Aerial Systems (UASs): A Review,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Giraldo-Zuluaga, J.H.[Jhony-Heriberto], Salazar, A.[Augusto], Gomez, A.[Alexander], Diaz-Pulido, A.[Angélica],
Camera-trap images segmentation using multi-layer robust principal component analysis,
VC(35), No. 3, March 2019, pp. 335-347.
Springer DOI 1906
Animal monitoring. BibRef

Peng, J.B.[Jin-Bang], Wang, D.L.[Dong-Liang], Liao, X.H.[Xiao-Han], Shao, Q.Q.[Quan-Qin], Sun, Z.G.[Zhi-Gang], Yue, H.Y.[Huan-Yin], Ye, H.[Huping],
Wild animal survey using UAS imagery and deep learning: modified Faster R-CNN for kiang detection in Tibetan Plateau,
PandRS(169), 2020, pp. 364-376.
Elsevier DOI 2011
Wild animal survey, Deep learning, Object detection, Unmanned aircraft systems (UAS) BibRef

Orusa, T.[Tommaso], Orusa, R.[Riccardo], Viani, A.[Annalisa], Carella, E.[Emanuele], Mondino, E.B.[Enrico Borgogno],
Geomatics and EO Data to Support Wildlife Diseases Assessment at Landscape Level: A Pilot Experience to Map Infectious Keratoconjunctivitis in Chamois and Phenological Trends in Aosta Valley (NW Italy),
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Venkitasubramanian, A.N.[Aparna Nurani], Tuytelaars, T.[Tinne], Moens, M.F.[Marie-Francine],
Wildlife recognition in nature documentaries with weak supervision from subtitles and external data,
PRL(81), No. 1, 2016, pp. 63-70.
Elsevier DOI 1609
Wildlife recognition BibRef

Fudala, K.[Katarzyna], Bialik, R.J.[Robert Józef],
Breeding Colony Dynamics of Southern Elephant Seals at Patelnia Point, King George Island, Antarctica,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef
And: Correction: RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Zhu, P.F.[Peng-Fei], Peng, T.[Tao], Du, D.W.[Da-Wei], Yu, H.T.[Hong-Tao], Zhang, L.[Libo], Hu, Q.H.[Qing-Hua],
Graph Regularized Flow Attention Network for Video Animal Counting From Drones,
IP(30), 2021, pp. 5339-5351.
IEEE DOI 2106
Animals, Drones, Annotations, Wildlife, Image resolution, Agriculture, Optical losses, Animal counting, drone, multi-granularity loss BibRef

Lee, S.[Seunghyeon], Song, Y.[Youngkeun], Kil, S.H.[Sung-Ho],
Feasibility Analyses of Real-Time Detection of Wildlife Using UAV-Derived Thermal and RGB Images,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Morgan, L.R.[Laura R.], Marsh, K.J.[Karen J.], Tolleson, D.R.[Douglas R.], Youngentob, K.N.[Kara N.],
The Application of NIRS to Determine Animal Physiological Traits for Wildlife Management and Conservation,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Wang, L., Ding, R., Zhai, Y., Zhang, Q., Tang, W., Zheng, N., Hua, G.,
Giant Panda Identification,
IP(30), 2021, pp. 2837-2849.
IEEE DOI 2102
Task analysis, Detectors, Feature extraction, Annotations, Visualization, Face recognition, Convolution, fine-grained recognition BibRef

Baralle, G.[Guillaume], Marchal, A.F.J.[Antoine F. J.], Lejeune, P.[Philippe], Michez, A.[Adrien],
Individual Identification of Cheetah (Acinonyx jubatus) Based on Close-Range Remote Sensing: First Steps of a New Monitoring Technique,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Kim, M.Y.[Min-Young], Chung, O.S.[Ok-Sik], Lee, J.K.[Jong-Koo],
A Manual for Monitoring Wild Boars (Sus scrofa) Using Thermal Infrared Cameras Mounted on an Unmanned Aerial Vehicle (UAV),
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Fischbach, A.S.[Anthony S.], Douglas, D.C.[David C.],
Evaluation of Satellite Imagery for Monitoring Pacific Walruses at a Large Coastal Haulout,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Williamson, S.D.[Sandra D.], van Dongen, R.[Richard], Trotter, L.[Lewis], Palmer, R.[Russell], Robinson, T.P.[Todd P.],
Fishing for Feral Cats in a Naturally Fragmented Rocky Landscape Using Movement Data,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Mohammadi, A.[Ahmad], Park, P.Y.[Peter Y.], Mukherjee, A.[Abir], Liu, X.[Xia],
Developing a situation and threat assessment framework for a next generation roadside animal detection system,
IET-ITS(16), No. 1, 2022, pp. 71-84.
DOI Link 2112
BibRef

Wang, S.H.[Shuai-Hang], Hu, C.[Cheng], Cui, K.[Kai], Wang, R.[Rui], Mao, H.F.[Hua-Feng], Wu, D.L.[Dong-Li],
Animal Migration Patterns Extraction Based on Atrous-Gated CNN Deep Learning Model,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Kyaw, P.P.[Pyae Phyoe], Macdonald, D.W.[David W.], Penjor, U.[Ugyen], Htun, S.[Saw], Naing, H.[Hla], Burnham, D.[Dawn], Kaszta, Z.[Zaneta], Cushman, S.A.[Samuel A.],
Investigating Carnivore Guild Structure: Spatial and Temporal Relationships amongst Threatened Felids in Myanmar,
IJGI(10), No. 12, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Christie, A.I.[Anna I.], Colefax, A.P.[Andrew P.], Cagnazzi, D.[Daniele],
Feasibility of Using Small UAVs to Derive Morphometric Measurements of Australian Snubfin (Orcaella heinsohni) and Humpback (Sousa sahulensis) Dolphins,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Connor, T.[Thomas], Division, W.[Wildlife], Tripp, E.[Emilio], Bean, W.T.[William T.], Saxon, B.J., Camarena, J.[Jessica], Donahue, A.[Asa], Sarna-Wojcicki, D.[Daniel], Macaulay, L.[Luke], Tripp, W.[William], Brashares, J.[Justin],
Estimating Wildlife Density as a Function of Environmental Heterogeneity Using Unmarked Data,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
BibRef

Feng, J.F.[Jiang-Fan], Li, J.C.[Jun-Cai],
An Adaptive Embedding Network with Spatial Constraints for the Use of Few-Shot Learning in Endangered-Animal Detection,
IJGI(11), No. 4, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Lu, L.H.[Long-Hui], Sun, Z.X.[Zhong-Xiang], Qimuge, E.[Eerdeng], Ye, H.[Huichun], Huang, W.J.[Wen-Jiang], Nie, C.[Chaojia], Wang, K.[Kun], Zhou, Y.[Yantao],
Using Remote Sensing Data and Species-Environmental Matching Model to Predict the Potential Distribution of Grassland Rodents in the Northern China,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Gedeon, C.I.[Csongor I.], Árvai, M.[Mátyás], Szatmári, G.[Gábor], Brevik, E.C.[Eric C.], Takáts, T.[Tünde], Kovács, Z.A.[Zsófia A.], Mészáros, J.[János],
Identification and Counting of European Souslik Burrows from UAV Images by Pixel-Based Image Analysis and Random Forest Classification: A Simple, Semi-Automated, yet Accurate Method for Estimating Population Size,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Winsen, M.[Megan], Denman, S.[Simon], Corcoran, E.[Evangeline], Hamilton, G.[Grant],
Automated Detection of Koalas with Deep Learning Ensembles,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Avots, E.[Egils], Vecvanags, A.[Alekss], Filipovs, J.[Jevgenijs], Brauns, A.[Agris], Skudrins, G.[Gundars], Done, G.[Gundega], Ozolins, J.[Janis], Anbarjafari, G.[Gholamreza], Jakovels, D.[Dainis],
Towards Automated Detection and Localization of Red Deer Cervus elaphus Using Passive Acoustic Sensors during the Rut,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Fu, Y.W.[Yan-Wen], Xu, G.C.[Guang-Cai], Gao, S.[Shang], Feng, L.M.[Li-Min], Guo, Q.H.[Qing-Hua], Yang, H.T.[Hai-Tao],
LiDAR Reveals the Process of Vision-Mediated Predator-Prey Relationships,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Roberts, K.E.[Kelsey E.], Garrison, L.P.[Lance P.], Ortega-Ortiz, J.[Joel], Hu, C.M.[Chuan-Min], Zhang, Y.J.[Ying-Jun], Sasso, C.R.[Christopher R.], Lamont, M.[Margaret], Hart, K.M.[Kristen M.],
The Influence of Satellite-Derived Environmental and Oceanographic Parameters on Marine Turtle Time at Surface in the Gulf of Mexico,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Gonçalves, B.C.[Bento C.], Wethington, M.[Michael], Lynch, H.J.[Heather J.],
SealNet 2.0: Human-Level Fully-Automated Pack-Ice Seal Detection in Very-High-Resolution Satellite Imagery with CNN Model Ensembles,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Paulsen, I.M.G.[Ingrid Marie Garfelt], Pedersen, Ĺ.Ř.[Ĺshild Řnvik], Hann, R.[Richard], Blanchet, M.A.[Marie-Anne], Eischeid, I.[Isabell], van Hazendonk, C.[Charlotte], Ravolainen, V.T.[Virve Tuulia], Stien, A.[Audun], Moullec, M.L.[Mathilde Le],
How Many Reindeer? UAV Surveys as an Alternative to Helicopter or Ground Surveys for Estimating Population Abundance in Open Landscapes,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Delplanque, A.[Alexandre], Foucher, S.[Samuel], Théau, J.[Jérôme], Bussičre, E.[Elsa], Vermeulen, C.[Cédric], Lejeune, P.[Philippe],
From crowd to herd counting: How to precisely detect and count African mammals using aerial imagery and deep learning?,
PandRS(197), 2023, pp. 167-180.
Elsevier DOI 2303
Deep learning, Livestock, Herd, Convolutional neural networks, Aerial survey, Protected area BibRef

Dong, G.[Guang], Xian, W.[Wei], Shao, H.Y.[Huai-Yong], Shao, Q.[Qiufang], Qi, J.G.[Jia-Guo],
Performance of Multiple Models for Estimating Rodent Activity Intensity in Alpine Grassland Using Remote Sensing,
RS(15), No. 5, 2023, pp. xx-yy.
DOI Link 2303
BibRef

Kim, D.J.[Dong-Jin], Miao, Z.Q.[Zhong-Qi], Guo, Y.H.[Yun-Hui], Yu, S.X.[Stella X.],
Modeling Semantic Correlation and Hierarchy for Real-World Wildlife Recognition,
SPLetters(30), 2023, pp. 259-263.
IEEE DOI 2303
Wildlife, Training, Neural networks, Semantics, Correlation, Data models, Birds, Wildlife recognition, active learning, class imbalance BibRef

Yang, X.Y.[Xin-Yu], Burghardt, T.[Tilo], Mirmehdi, M.[Majid],
Dynamic Curriculum Learning for Great Ape Detection in the Wild,
IJCV(131), No. 5, May 2023, pp. 1163-1181.
Springer DOI 2305
BibRef

Wich, S.A.[Serge A.], Bonnin, N.[Noémie], Hutschenreiter, A.[Anja], Piel, A.K.[Alex K.], Chitayat, A.[Adrienne], Stewart, F.A.[Fiona A.], Pintea, L.[Lilian], Kerby, J.T.[Jeffrey T.],
Using Drones to Determine Chimpanzee Absences at the Edge of Their Distribution in Western Tanzania,
RS(15), No. 8, 2023, pp. 2019.
DOI Link 2305
BibRef

Fergus, P.[Paul], Chalmers, C.[Carl], Longmore, S.[Steven], Wich, S.[Serge], Warmenhove, C.[Carmen], Swart, J.[Jonathan], Ngongwane, T.[Thuto], Burger, A.[André], Ledgard, J.[Jonathan], Meijaard, E.[Erik],
Empowering Wildlife Guardians: An Equitable Digital Stewardship and Reward System for Biodiversity Conservation Using Deep Learning and 3/4G Camera Traps,
RS(15), No. 11, 2023, pp. 2730.
DOI Link 2306
BibRef

Mounir, R.[Ramy], Shahabaz, A.[Ahmed], Gula, R.[Roman], Theuerkauf, J.[Jörn], Sarkar, S.[Sudeep],
Towards Automated Ethogramming: Cognitively-Inspired Event Segmentation for Streaming Wildlife Video Monitoring,
IJCV(131), No. 9, September 2023, pp. 2267-2297.
Springer DOI 2308
BibRef
And: Correction: IJCV(131), No. 1, January 2023, pp. 3118-3118.
Springer DOI 2310
BibRef

Ho, K.[Katherine], Loraamm, R.[Rebecca],
Using a Cost-Distance Time-Geographic Approach to Identify Red Deer Habitat Use in Banff National Park, Alberta, Canada,
IJGI(12), No. 8, 2023, pp. 339.
DOI Link 2309
BibRef

McCraine, D.[Daniel], Samiappan, S.[Sathishkumar], Kohler, L.[Leon], Sullivan, T.[Timo], Will, D.J.[David J.],
Automated Hyperspectral Feature Selection and Classification of Wildlife Using Uncrewed Aerial Vehicles,
RS(16), No. 2, 2024, pp. 406.
DOI Link 2402
BibRef

Attard, M.R.G.[Marie R. G.], Phillips, R.A.[Richard A.], Bowler, E.[Ellen], Clarke, P.J.[Penny J.], Cubaynes, H.[Hannah], Johnston, D.W.[David W.], Fretwell, P.T.[Peter T.],
Review of Satellite Remote Sensing and Unoccupied Aircraft Systems for Counting Wildlife on Land,
RS(16), No. 4, 2024, pp. 627.
DOI Link 2402
BibRef

Malmström, M.[Magnus], Kullberg, A.[Anton], Skog, I.[Isaac], Axehill, D.[Daniel], Gustafsson, F.[Fredrik],
Extended Target Tracking Utilizing Machine-Learning Software-With Applications to Animal Classification,
SPLetters(31), 2024, pp. 376-380.
IEEE DOI 2402
Signal processing algorithms, Classification algorithms, Cameras, Target tracking, Filtering algorithms, Standards, Loss measurement, Kalman filters BibRef


Prins, F.L.[Fabian L.], Tomanin, D.[Dario], Kamenz, J.[Julia], Azzopardi, G.[George],
Biometric Recognition of African Clawed Frogs,
CAIP23(II:151-161).
Springer DOI 2312
BibRef

Wu, S.Z.[Shang-Zhe], Li, R.N.[Rui-Ning], Jakab, T.[Tomas], Rupprecht, C.[Christian], Vedaldi, A.[Andrea],
MagicPony: Learning Articulated 3D Animals in the Wild,
CVPR23(8792-8802)
IEEE DOI 2309
BibRef

Rubio, Y.[Yoshio], Contreras-Cruz, M.A.[Marco A.],
Wildlife Image Generation from Scene Graphs,
LXCV23(305-314)
IEEE DOI 2309
BibRef

Chen, J.[Jun], Hu, M.[Ming], Coker, D.J.[Darren J.], Berumen, M.L.[Michael L.], Costelloe, B.[Blair], Beery, S.[Sara], Rohrbach, A.[Anna], Elhoseiny, M.[Mohamed],
MammalNet: A Large-Scale Video Benchmark for Mammal Recognition and Behavior Understanding,
CVPR23(13052-13061)
IEEE DOI 2309
BibRef

Chen, Z.Y.[Zi-Yue], Gao, Y.Y.[Yuan-Yuan],
Primate Recognition System Design Based on Deep Learning Model VGG16,
ICIVC22(605-610)
IEEE DOI 2301
Training, Deep learning, Visualization, Analytical models, Image recognition, Animals, Neural networks, primates, VGG16, visualization BibRef

Kim, J.[Jeongsoo], Woo, S.[Sangmin], Park, B.[Byeongjun], Kim, C.[Changick],
Temporal Flow Mask Attention for Open-Set Long-Tailed Recognition of Wild Animals in Camera-Trap Images,
ICIP22(2152-2156)
IEEE DOI 2211
Image motion analysis, Image recognition, Wildlife, Tail, Feature extraction, Cameras, Open-set Long-tailed Recognition, Camera Trap BibRef

Estrada, D.N.D.[David Norman Díaz], Goyal, U.[Utkarsh], Ullah, M.[Mohib], Cheikh, F.A.[Faouzi Alaya],
Psi-NET: A Novel Encoder-Decoder Architecture for Animal Segmentation,
IPTA22(1-5)
IEEE DOI 2206
Training, Image segmentation, Animals, Cognition, Decoding, Data mining, Task analysis, Animal segmentation, pig segmentation, feature learning BibRef

Rumiano, F., Gaucherel, C., Degenne, P., Miguel, E., Chamaillé-Jammes, S., Valls-Fox, H., Cornélis, D., de Garine-Wichatitsky, M., Fritz, H., Caron, A., Tran, A.,
Combined Use of Remote Sensing and Spatial Modelling: When Surface Water Impacts Buffalo (Syncerus Caffer Caffer) Movements In Savanna Environments,
ISPRS21(B3-2021: 631-638).
DOI Link 2201
BibRef

Parvin, N.[Nahida], Awrangjeb, M.[Mohammad], Irvin, M.[Marc], Florentine, S.[Singarayer], Murshed, M.[Manzur], Lu, G.J.[Guo-Jun],
Detection of Malleefowl Mounds from Point Cloud Data,
DICTA21(1-7)
IEEE DOI 2201
Point cloud compression, Laser radar, Shape, Digital images, Sociology, Manuals, Feature extraction BibRef

Go, H.[Hyojun], Byun, J.[Junyoung], Park, B.[Byeongjun], Choi, M.A.[Myung-Ae], Yoo, S.[Seunghwa], Kim, C.[Changick],
Fine-Grained Multi-Class Object Counting,
ICIP21(509-513)
IEEE DOI 2201
Cranes, Image processing, Wildlife, Sociology, Network architecture, Benchmark testing, Multi-class object counting, Counting with classification BibRef

McEwen, B.[Ben], Green, R.[Richard], Gutschmidt, S.[Stefanie], Ryan, G.[Grant],
Predictive State Estimation of Invasive Predators using Low Resolution Thermal Cameras,
IVCNZ21(1-6)
IEEE DOI 2201
Visualization, Tracking, Animals, Cameras, Particle filters, Kalman filters, Noise measurement, State Estimation, Occlusion BibRef

Zheng, X.C.[Xiao-Chen], Kellenberger, B.[Benjamin], Gong, R.[Rui], Hajnsek, I.[Irena], Tuia, D.[Devis],
Self-Supervised Pretraining and Controlled Augmentation Improve Rare Wildlife Recognition in UAV Images,
LUAI21(732-741)
IEEE DOI 2112
Training, Deep learning, Image recognition, Annotations, Wildlife, Supervised learning BibRef

Cunha, F.[Fagner], dos Santos, E.M.[Eulanda M.], Barreto, R.[Raimundo], Colonna, J.G.[Juan G.],
Filtering Empty Camera Trap Images in Embedded Systems,
MAI21(2438-2446)
IEEE DOI 2109
Training, Performance evaluation, Quantization (signal), Image edge detection, Computational modeling, Wildlife, Detectors BibRef

Weideman, H.J., Stewart, C.V., Parham, J.R., Holmberg, J., Flynn, K., Calambokidis, J., Paul, D.B., Bedetti, A., Henley, M., Lepirei, J., Pope, F.G.,
Extracting identifying contours for African elephants and humpback whales using a learned appearance model,
WACV20(1265-1274)
IEEE DOI 2006
Training data, Ear, Training, Whales, Image edge detection, Data mining BibRef

Cheng, X., Zhu, J., Zhang, N., Wang, Q., Zhao, Q.,
Detection Features as Attention (Defat): A Keypoint-Free Approach to Amur Tiger Re-Identification,
ICIP20(2231-2235)
IEEE DOI 2011
Feature extraction, Pipelines, Cameras, Training, Animals, Probes, Additives, animal re-identification, keypoint-free, attention BibRef

Singh, P., Lindshield, S.M., Zhu, F., Reibman, A.R.,
Animal Localization in Camera-Trap Images with Complex Backgrounds,
SSIAI20(66-69)
IEEE DOI 2009
biology computing, convolutional neural nets, image motion analysis, principal component analysis, zoology, Animal localization BibRef

Zuffi, S., Kanazawa, A., Berger-Wolf, T., Black, M.,
Three-D Safari: Learning to Estimate Zebra Pose, Shape, and Texture From Images 'In the Wild',
ICCV19(5358-5367)
IEEE DOI 2004
biology computing, image capture, image texture, Computational modeling, learning (artificial intelligence), natural scenes, optimisation. BibRef

Körschens, M., Denzler, J.,
ELPephants: A Fine-Grained Dataset for Elephant Re-Identification,
CVWC19(263-270)
IEEE DOI 2004
feature extraction, image classification, image colour analysis, image segmentation, re-identification BibRef

Yang, X., Mirmehdi, M., Burghardt, T.,
Great Ape Detection in Challenging Jungle Camera Trap Footage via Attention-Based Spatial and Temporal Feature Blending,
CVWC19(255-262)
IEEE DOI 2004
cameras, feature extraction, image classification, image motion analysis, image segmentation, image sequences, Video Object Detection BibRef

Liu, N., Zhao, Q., Zhang, N., Cheng, X., Zhu, J.,
Pose-Guided Complementary Features Learning for Amur Tiger Re-Identification,
CVWC19(286-293)
IEEE DOI 2004
Code, Recognition.
WWW Link. ecology, environmental science computing, feature extraction, image classification, Wildlife Conservation BibRef

Yu, J., Su, H., Liu, J., Yang, Z., Zhang, Z., Zhu, Y., Yang, L., Jiao, B.,
A Strong Baseline for Tiger Re-ID and its Bag of Tricks,
CVWC19(302-309)
IEEE DOI 2004
Code, Recognition.
WWW Link. feature extraction, image matching, image sampling, learning (artificial intelligence), object detection, flip as new id BibRef

Kupyn, O., Pranchuk, D.,
Fast and Efficient Model for Real-Time Tiger Detection In The Wild,
CVWC19(310-314)
IEEE DOI 2004
biology computing, cameras, object detection, supervised learning, zoology, Amur Tiger Detection, edge devices, smart cameras, tigers BibRef

Liu, C., Zhang, R., Guo, L.,
Part-Pose Guided Amur Tiger Re-Identification,
CVWC19(315-322)
IEEE DOI 2004
Code, Recognition.
WWW Link. inference mechanisms, learning (artificial intelligence), pose estimation, PlainID competitions, WildID competitions, Pose Alignment BibRef

Shukla, A., Anderson, C., Cheema, G.S.[G. Sigh], Gao, P., Onda, S., Anshumaan, D., Anand, S., Farrell, R.,
A Hybrid Approach to Tiger Re-Identification,
CVWC19(294-301)
IEEE DOI 2004
Code, Recognition.
WWW Link. data analysis, entropy, feature extraction, image classification, image matching, image representation, tigers BibRef

Wang, H., Song, Y., Li, S., Dai, W., Liu, J.,
Transfer Learning Based Wildlife Recognition for Tele-Observation in Field Occlusion Environment,
ICIP19(3392-3396)
IEEE DOI 1910
customized loss function, anti-occlusion, wildlife monitoring, transfer learning, CNN BibRef

Agarwal, M., Sinha, S., Singh, M., Nagpal, S., Singh, R., Vatsa, M.,
Triplet Transform Learning for Automated Primate Face Recognition,
ICIP19(3462-3466)
IEEE DOI 1910
Animal Biometrics, Transform Learning, Triplet Loss, Primate Face Recognition BibRef

Matkowski, W.M., Kong, A.W.K., Su, H., Chen, P., Hou, R., Zhang, Z.,
Giant Panda Face Recognition Using Small Dataset,
ICIP19(1680-1684)
IEEE DOI 1910
biometrics, face recognition, giant panda, individual identification BibRef

Yoshida, K.[Kumiko], Kawasue, K.[Kikuhito],
Robust 3D Pig Measurement in Pig Farm,
3D-Wild18(I:387-400).
Springer DOI 1905
BibRef

Popova, A.[Anastasia], Eerola, T.[Tuomas], Kälviäinen, H.[Heikki],
Comparison of Co-segmentation Methods for Wildlife Photo-identification,
ACIVS18(139-149).
Springer DOI 1810
BibRef

Zhu, C., Li, T.H., Li, G.,
Towards Automatic Wild Animal Detection in Low Quality Camera-Trap Images Using Two-Channeled Perceiving Residual Pyramid Networks,
Wildlife17(2860-2864)
IEEE DOI 1802
Cameras, Feature extraction, Image segmentation, Training, Wildlife BibRef

Weideman, H.J., Jablons, Z.M., Holmberg, J., Flynn, K., Calambokidis, J., Tyson, R.B., Allen, J.B., Wells, R.S., Hupman, K., Urian, K., Stewart, C.V.,
Integral Curvature Representation and Matching Algorithms for Identification of Dolphins and Whales,
Wildlife17(2831-2839)
IEEE DOI 1802
Dolphins, Image edge detection, Indexing, Robustness, Shape, Whales BibRef

Brust, C.A., Burghardt, T., Groenenberg, M., Kading, C., Kühl, H.S., Manguette, M.L., Denzler, J.,
Towards Automated Visual Monitoring of Individual Gorillas in the Wild,
Wildlife17(2820-2830)
IEEE DOI 1802
Biodiversity, Biological system modeling, Cameras, Monitoring, Sociology, Statistics BibRef

Gomez, A.[Alexander], Diez, G.[German], Salazar, A.[Augusto], Diaz, A.[Angelica],
Animal Identification in Low Quality Camera-Trap Images Using Very Deep Convolutional Neural Networks and Confidence Thresholds,
ISVC16(I: 747-756).
Springer DOI 1701
BibRef

Du, S.Z.[Sheng-Zhi], Du, C.L.[Chun-Ling], Abdoola, R.[Rishaad], van Wyk, B.J.[Barend Jacobus],
A Gaussian Mixture Model Feature for Wildlife Detection,
ISVC16(I: 757-765).
Springer DOI 1701
BibRef

Freytag, A.[Alexander], Rodner, E.[Erik], Simon, M.[Marcel], Loos, A.[Alexander], Kühl, H.S.[Hjalmar S.], Denzler, J.[Joachim],
Chimpanzee Faces in the Wild: Log-Euclidean CNNs for Predicting Identities and Attributes of Primates,
GCPR16(51-63).
Springer DOI 1611
BibRef

Zhang, H.P.[Hong-Ping], Jiang, J.[Jie], Wei, D.[Dong], Jiang, J.[Jie],
A Wildlife Monitoring System Based On Tianditu And Beidou: In Case Of The Tibetan Antelope,
ISPRS16(B4: 259-262).
DOI Link 1610
BibRef

Parham, J., Stewart, C.,
Detecting plains and Grevy's Zebras in the realworld,
AAVWS16(1-9)
IEEE DOI 1606
Hough transforms BibRef

Linchant, J., Lhoest, S., Quevauvillers, S., Semeki, J., Lejeune, P., Vermeulen, C.,
WIMUAS: Developing a Tool to Review Wildlife Data from Various UAS Flight Plans,
GeoUAV15(379-384).
DOI Link 1602
BibRef

Lhoest, S., Linchant, J., Quevauvillers, S., Vermeulen, C., Lejeune, P.,
How Many Hippos (HOMHIP): Algorithm for Automatic Counts of Animals with Infra-Red Thermal Imagery From UAV,
GeoUAV15(355-362).
DOI Link 1602
BibRef

Chrétien, L.P., Théau, J., Ménard, P.,
Wildlife Multispecies Remote Sensing Using Visible and Thermal Infrared Imagery Acquired from an Unmanned Aerial Vehicle (UAV),
UAV-g15(241-248).
DOI Link 1512
BibRef

Zmarz, A., Korczak-Abshire, M., Storvold, R., Rodzewicz, M., Kedzierska, I.,
Indicator Species Population Monitoring in Antarctica with UAV,
UAV-g15(189-193).
DOI Link 1512
BibRef

Figueroa, K.[Karina], Camarena-Ibarrola, A.[Antonio], García, J.[Jonathan], Villela, H.T.[Héctor Tejeda],
Fast Automatic Detection of Wildlife in Images from Trap Cameras,
CIARP14(940-947).
Springer DOI 1411
BibRef

Lahiri, M.[Mayank], Tantipathananandh, C.[Chayant], Warungu, R.[Rosemary], Rubenstein, D.I.[Daniel I.], Berger-Wolf, T.Y.[Tanya Y.],
Biometric animal databases from field photographs: Identification of individual zebra in the wild,
ICMR11(6).
DOI Link 1301
a database of noisy photographs taken in the wild BibRef

Chapter on Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection continues in
Agriculture, Inspection -- Meat .


Last update:Mar 16, 2024 at 20:36:19