20.7.3.7.11 Plankton Analysis, Extraction, Features, Small Scale and Large Scale

Alfano, P.D.[Paolo Didier], Rando, M.[Marco], Letizia, M.[Marco], Odone, F.[Francesca], Rosasco, L.[Lorenzo], Pastore, V.P.[Vito Paolo],
Efficient Unsupervised Learning for Plankton Images,
ICPR22(1314-1321)
IEEE DOI 2212
Image segmentation, Microorganisms, Pipelines, Neural networks, Sociology, Feature extraction BibRef

Pastore, V.P.[Vito Paolo], Megiddo, N.[Nimrod], Bianco, S.[Simone],
An Anomaly Detection Approach for Plankton Species Discovery,
CIAP22(II:599-609).
Springer DOI 2205
BibRef

Liu, Y.[Yiran], Qiao, X.[Xu], Gao, R.[Rui],
Plankton Classification on Imbalanced Dataset via Hybrid Resample Method with LightBGM,
ICIVC21(191-195)
IEEE DOI 2112
Dimensionality reduction, Deep learning, Technological innovation, Image recognition, LightBGM BibRef

Pu, Y.C.[Yu-Chun], Feng, Z.H.[Zheng-Hui], Wang, Z.L.[Zhong-Lei], Yang, Z.Y.[Zhen-Yu], Li, J.P.[Jian-Ping],
Anomaly Detection for In situ Marine Plankton Images,
OceanVision21(3654-3664)
IEEE DOI 2112
Training, Machine learning algorithms, Face recognition, Pipelines, Observers, Robustness, Task analysis BibRef

Walker, J.L.[Joseph L.], Orenstein, E.C.[Eric C.],
Improving Rare-Class Recognition of Marine Plankton with Hard Negative Mining,
OceanVision21(3665-3675)
IEEE DOI 2112
Training, Oceans, Sociology, Machine learning, Biology BibRef

Ma, W.Q.[Wen-Qi], Chen, T.[Tao], Zhang, Z.G.[Zhen-Gwen], Yang, Z.Y.[Zhen-Yu], Dong, C.[Chao], Qiao, J.P.[Jian-Ping], Li, J.P.[Jian-Ping],
Super-resolution for in situ Plankton Images,
OceanVision21(3676-3685)
IEEE DOI 2112
Deep learning, Visualization, Image registration, Instruments, Biological system modeling, Superresolution, Pipelines BibRef

Bureš, J.[Jaroslav], Eerola, T.[Tuomas], Lensu, L.[Lasse], Kälviäinen, H.[Heikki], Zemcík, P.[Pavel],
Plankton Recognition in Images with Varying Size,
MAES20(110-120).
Springer DOI 2103
BibRef

Shunmugapandi, R., Gedam, S., Inamdar, A.B.,
Study on Cyclone Induced Phytoplankton Bloom In the Arabian Sea Through Gap-free Reconstructed Chlorophyll-a Data,
ISPRS20(B3:1391-1396).
DOI Link 2012
BibRef

Schröder, S.M.[Simon-Martin], Kiko, R.[Rainer], Irisson, J.O.[Jean-Olivier], Koch, R.[Reinhard],
Low-Shot Learning of Plankton Categories,
GCPR18(391-404).
Springer DOI 1905
BibRef

Bochinski, E.[Erik], Bacha, G.[Ghassen], Eiselein, V.[Volker], Walles, T.J.W.[Tim J. W.], Nejstgaard, J.C.[Jens C.], Sikora, T.[Thomas],
Deep Active Learning for In Situ Plankton Classification,
CVAUI18(5-15).
Springer DOI 1901
BibRef

Zelenka, C.[Claudius], Koch, R.[Reinhard],
Single Image Plankton 3D Reconstruction from Extended Depth of Field Shadowgraph,
CVAUI18(76-85).
Springer DOI 1901
BibRef

Wang, C., Yu, Z., Zheng, H., Wang, N., Zheng, B.,
CGAN-plankton: Towards large-scale imbalanced class generation and fine-grained classification,
ICIP17(855-859)
IEEE DOI 1803
Computational modeling, Data models, Kernel, Oceans, Task analysis, Training, GAN, adversarial training, class imbalance, samples generation BibRef

Orenstein, E.C., Beijbom, O.,
Transfer Learning and Deep Feature Extraction for Planktonic Image Data Sets,
WACV17(1082-1088)
IEEE DOI 1609
Cameras, Data mining, Feature extraction, Oceans, Training BibRef

Dai, J.L.[Jia-Lun], Yu, Z.B.[Zhi-Bin], Zheng, H.Y.[Hai-Yong], Zheng, B.[Bing], Wang, N.[Nan],
A Hybrid Convolutional Neural Network for Plankton Classification,
MCBMIIA16(III: 102-114).
Springer DOI 1704
BibRef

Hirata, N.S.T., Fernandez, M.A., Lopes, R.M.,
Plankton Image Classification Based on Multiple Segmentations,
CVAUI16(55-60)
IEEE DOI 1701
Algorithm design and analysis BibRef

Lee, H., Park, M., Kim, J.,
Plankton classification on imbalanced large scale database via convolutional neural networks with transfer learning,
ICIP16(3713-3717)
IEEE DOI 1610
Data models BibRef

Gao, G.M.[Guo-Ming], Liu, H.[Huan], Gu, Y.F.[Yan-Feng], Jia, X.P.[Xiu-Ping],
Normalized difference phytoplankton index (NDPI) and spatio-temporal cloud filtering for multitemporal cyanobacteria pollution analysis on Erie Lake in 2014,
MultiTemp15(1-4)
IEEE DOI 1511
lakes BibRef

Rahimi, A.M., Miller, R.J., Fedorov, D.V., Sunderrajan, S., Doheny, B.M., Page, H.M., Manjunath, B.S.,
Marine Biodiversity Classification Using Dropout Regularization,
CVAUI14(80-87)
IEEE DOI 1412
Biodiversity BibRef

Mazzei, L.[Luca], Marini, S.[Simone], Craig, J.[Jessica], Aguzzi, J.[Jacopo], Fanelli, E.[Emanuela], Priede, I.G.[Imants G.],
Automated Video Imaging System for Counting Deep-Sea Bioluminescence Organisms Events,
CVAUI14(57-64)
IEEE DOI 1412
Ash BibRef

Corgnati, L.[Lorenzo], Mazzei, L.[Luca], Marini, S.[Simone], Aliani, S.[Stefano], Conversi, A.[Alessandra], Griffa, A.[Annalisa], Isoppo, B.[Bruno], Ottaviani, E.[Ennio],
Automated Gelatinous Zooplankton Acquisition and Recognition,
CVAUI14(1-8)
IEEE DOI 1412
Feature extraction BibRef

Matuszewski, D.J.[Damian J.], Martins, C.I.O.[C. Iury O.], Cesar, Jr., R.M.[Roberto M.], Strickler, J.R.[J. Rudi], Lopes, R.M.[Rubens M.],
Visual rhythm-based plankton detection method for ballast water quality assessment,
ICIP12(1009-1012).
IEEE DOI 1302
BibRef

Zhao, F.[Feng], Lin, F.[Feng], Seah, H.S.[Hock Soon],
Bagging based plankton image classification,
ICIP09(2081-2084).
IEEE DOI 0911
BibRef

Alarcon, V.J., van der Zwaag, J., Moorhead, R.,
Estimation of Estuary Phytoplankton using a Web-based Tool for Visualization of Hyper-spectral Images,
AIPR06(25-25).
IEEE DOI 0610
BibRef

Alarcon, V.J., O'Hara, C.G.,
Advanced Techniques for Watershed Visualization,
AIPR06(30-30).
IEEE DOI 0610
BibRef

Luo, T.[Tong], Kramer, K., Samson, S., Remsen, A.,
Active learning to recognize multiple types of plankton,
ICPR04(III: 478-481).
IEEE DOI 0409
BibRef

Zhao, F.[Feng], Tang, X.[Xiaoou], Lin, F.[Feng], Samson, S., Remsen, A.,
Binary Plankton Image Classification Using Random Subspace,
ICIP05(I: 357-360).
IEEE DOI 0512
BibRef

Blaschko, M.B.[Matthew B.], Holness, G.[Gary], Mattar, M.A.[Marwan A.], Lisin, D.A.[Dimitri A.], Utgoff, P.E.[Paul E.], Hanson, A.R.[Allen R.], Schultz, H.[Howard], Riseman, E.M.[Edward M.], Sieracki, M.E.[Michael E.], Balch, W.M.[William M.], Tupper, B.[Ben],
Automatic In Situ Identification of Plankton,
WACV05(I: 79-86).
IEEE DOI 0502
BibRef

Lisin, D.A., Mattar, M.A., Blaschko, M.B., Learned-Miller, E.G., Benfield, M.C.,
Combining Local and Global Image Features for Object Class Recognition,
LCV05(III: 47-47).
IEEE DOI 0507
BibRef

Thonnat, M., Gandelin, M.,
An expert system for the automatic classification and description of zooplanktons from monocular images,
ICPR88(I: 114-118).
IEEE DOI 8811
BibRef

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

Last update:Sep 28, 2024 at 17:47:54