Titlebook: Marine Pollution and Microbial Remediation; Milind Mohan Naik,Santosh Kumar Dubey Book 2017 Springer Science+Business Media Singapore 2017

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P. V. Bramhachari,Ganji Purnachandra Nagarajubi-directional transport to align the target features with class prototypes by minimizing its expected cost. On top of that, a contrastive learning stage is further devised to utilize those pixels with unreliable predictions for a more compact target feature distribution. Extensive experiments on a

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Siddhardha Busi,Jobina Rajkumaries from different receptive fields that are complementary to each other to generate high-quality soft pseudo labels. For more stable unsupervised learning, we use voxel-wise uncertainty to rectify the soft pseudo labels and then supervise the outputs of each decoder. To further regularize the networ

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Teja Gaonkar,Sunita Borkarually have multiple sentences, each of which describes different findings, and therefore integrates sentence-level information to identify discriminative regions for mask generation. MedIM integrates both strategies by simultaneously restoring the images masked by KWM and SDM for a more robust and r

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Md Imran,Preethi B. Poduval,Sanjeev C. Ghadipatient yielded an individual lesion change class accuracy of 98% and 85%, and identification of patterns of lesion change with an accuracy of 96% and 76%, respectively. Highlighting unusual lesion labels and lesion change patterns in the graph helps radiologists identify overlooked or faintly visib

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