Titlebook: Marine Resource Conservation and Poverty Reduction Strategies in Tanzania; Jennifer K. Sesabo Book 2007 Springer-Verlag Berlin Heidelberg

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d explicitly for every image, making this solution increasingly tedious with higher data size. In this work, we propose AdaptiveSAM - an adaptive modification of SAM that can adjust to new datasets quickly and efficiently, while enabling text-prompted segmentation. For finetuning AdaptiveSAM, we pro

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sformer Network (STN) inspired convolutional neural network (CNN) architecture to perform supervised registration of bSSFP cine CMR and LGE CMR images. We evaluate our proposed method on the 2019 Multi-Sequence Cardiac Magnetic Resonance Segmentation Challenge (MS-CMRSeg) dataset and use several eva

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Book 2007fficiency and attitudes towards conservation initiatives. Thus, attention to differential patterns of rural coastal households presents more viable possibilities for coastal villages to have conservation-development policies/programs that lead to poverty reduction..

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Book 2007n and degradation of their habitats. Using the data from two coastal villages and econometric methods as well as Stochastic Production Frontier techniques, the book demonstrates the extent which various socio-economic dimensions of rural coastal households influence livelihood pathways, production e

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1614-2462 coastal households presents more viable possibilities for coastal villages to have conservation-development policies/programs that lead to poverty reduction..978-3-540-69941-5978-3-540-69943-9Series ISSN 1614-2462 Series E-ISSN 1867-9587