Showing results 16073 to 16092 of 105287
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| Issue Date | Title | Author(s) |
| 2017-09-01 | Classification of high-dimensional evolving data streams via a resource-efficient online ensemble | Zhai, T; Gao, Y; Wang, H; Cao, L |
| 2010-12-01 | Classification of hypoglycemic episodes for type 1 diabetes mellitus based on neural networks | Chan, KY; Ling, SH; Dillon, TS; Nguyen, H |
| 2023-12-11 | Classification of inattentional blindness using brain dynamics of ERPs | Tian, Y; Zhang, L; Do, TT-T; Liu, J; Wang, Y-K; Lin, C-T |
| 2023-01-01 | Classification of lattice defects and the microscopic origin of p-type conductivity of Sb<inf>2</inf>Se<inf>3</inf> solar cell absorber with varying Al<inf>2</inf>O<inf>3</inf>-layer thicknesses | Guo, H; Jia, X; Liu, J; Feng, Z; Zhang, S; Chen, Z; Tian, H; Qiu, J; Yuan, N; Ding, J |
| 2020-08-04 | Classification of Load Balancing in the Internet | Almeida, R; Cunha, I; Teixeira, R; Veitch, D; Diot, C |
| 2010-10-01 | Classification of low level surface electromyogram using independent component analysis | Naik, GR; Kumar, DK; Palaniswami, M |
| 2020-01 | Classification of Lung Nodules Based on Deep Residual Networks and Migration Learning. | Wu, P; Sun, X; Zhao, Z; Wang, H; Pan, S; Schuller, B |
| 2013 | Classification of Malignant Melanoma and Benign Nevi from Skin Lesions Based on Support Vector Machine | Abu Mahmoud, MK; Al-Jumaily, A; Maali, Y; Anam, K; CIMSim2013 |
| 2013-01 | Classification of Malignant Melanoma and Benign Nevi from Skin Lesions based on Support Vector Machine | Abu Mahmoud, M; Al-Jumaily, A; Maali, Y; Anam, K; Eduard babulak, SKKU |
| 2015-09-28 | Classification of migraine stages based on resting-state EEG power | Cao, ZH; Ko, LW; Lai, KL; Huang, SB; Wang, SJ; Lin, CT |
| 2020-01-01 | Classification of Neuroblastoma Histopathological Images Using Machine Learning | Panta, A; Khushi, M; Naseem, U; Kennedy, P; Catchpoole, D |
| 2021-01-01 | Classification of pilot attentional behavior using ocular measures | Kilingaru, K; Nedic, Z; Jain, LC; Tweedale, J; Thatcher, S |
| 2018-01-02 | Classification of playing position in elite junior Australian football using technical skill indicators | Woods, CT; Veale, J; Fransen, J; Robertson, S; Collier, NF |
| 2003-03-12 | Classification of premium and regular gasoline by gas chromatography/mass spectrometry, principal component analysis and artificial neural networks | Doble, P; Sandercock, M; Du Pasquier, E; Petocz, P; Roux, C; Dawson, M |
| 2018-02-01 | CLASSIFICATION OF REFLECTION SUBGROUPS MINIMALLY CONTAINING p-SYLOW SUBGROUPS | Townsend, KD |
| 2018-07-02 | A Classification of Single-Phase Transformerless Inverter Topologies for Photovoltaic Applications | Khan, MNH; Forouzesh, M; Siwakoti, YP; Li, L; Kerekes, T; Blaabjerg, F |
| 2019-03-01 | Classification of stomach cancer gene expression data using CNN algorithm of deep learning | Shon, HS; Yi, Y; Kim, KO; Cha, E-J; Kim, K-A |
| 2020 | Classification of stroke disease using machine learning algorithms | Govindarajan, P; Soundarapandian, RK; Gandomi, AH; Patan, R; Jayaraman, P; Manikandan, R |
| 2020-09-01 | Classification of Sylow classes of parabolic and reflection subgroups in unitary reflection groups | Townsend, KD |
| 2003-09-01 | Classification of the biopolymer sodium pentosan polysulfate by infrared spectroscopy | Foot, M; Mulholland, M; Kirkup, L |
