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Titlebook: Marine Resource Damage Assessment; Liability and Compen Frank Maes Book 2005 Springer Science+Business Media B.V. 2005 Compensation.Conting

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樓主: Iodine
21#
發(fā)表于 2025-3-25 04:28:27 | 只看該作者
22#
發(fā)表于 2025-3-25 08:15:06 | 只看該作者
23#
發(fā)表于 2025-3-25 14:42:43 | 只看該作者
24#
發(fā)表于 2025-3-25 18:34:33 | 只看該作者
25#
發(fā)表于 2025-3-25 21:48:43 | 只看該作者
Laurent Proot,Hubert Bocken. Each segment, i.e., splat, contains pixels with similar color and spatial location. A novel method for automated generalised generation of splat is presented in this paper and further marking of the diseased splats is also proposed. The proposed method is tested on DIARETDB1 dataset, achieving acc
26#
發(fā)表于 2025-3-26 01:01:52 | 只看該作者
Laila Medin LMM using .10–15 patients for training. Best results were found for LDC, QDC and RF. Intraplaque haemorrhage was most accurately classified in both protocols, and lowest accuracy was found for the lipid-rich necrotic core. Secondly, for LDC and RF it was shown that leaving out different MRI sequences u
27#
發(fā)表于 2025-3-26 04:44:21 | 只看該作者
mages and found to outperform three publicly available OCT segmentation software. The average unsigned boundary localization error is . pixels for segmentation of 8 boundaries on the Normal dataset and . pixels for 3 boundaries on the combined AMD and Normal dataset establishing the robustness of th
28#
發(fā)表于 2025-3-26 09:25:18 | 只看該作者
Joe Nichols We find that both cellular and architectural morphology features are required to achieve the best performance. Therefore, we propose using multi-resolution deep CNN for growth pattern classification in lung adenocarcinoma. Our preliminarily results show an increase in the overall classification acc
29#
發(fā)表于 2025-3-26 13:43:11 | 只看該作者
K. A. Mac Innis QC machine-learning approach to the assessment of three-dimensional SPECT data. The system extracts intensity and shape information from the data following binarisation which utilises an experimental approach towards the identification of an optimal threshold. The striatal binding ratio is calculated
30#
發(fā)表于 2025-3-26 20:19:45 | 只看該作者
Gwendoline Gonsaeles LL.M We find that both cellular and architectural morphology features are required to achieve the best performance. Therefore, we propose using multi-resolution deep CNN for growth pattern classification in lung adenocarcinoma. Our preliminarily results show an increase in the overall classification acc
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