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{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/7782580","sourcedb":"PMC","sourceid":"7782580","source_url":"https://www.ncbi.nlm.nih.gov/pmc/7782580","text":"The CNNRF is a modular framework consisting of one stage II sub-framework and one regressor block to handle the regression task. In the regressor block, we used skip connections that consisted of a convolution layer with multiple 1 × 1 convolution kernels for retaining the features extracted by the stage II sub-framework while improving the non-linear representation ability of the regressor block. We made use of flexible blocks to achieve good performance for the classification and regression tasks, unlike traditional machine learning methods, which are commonly used for either of these tasks.","tracks":[{"project":"LitCovid-sentences","denotations":[{"id":"T262","span":{"begin":0,"end":128},"obj":"Sentence"},{"id":"T263","span":{"begin":129,"end":400},"obj":"Sentence"},{"id":"T264","span":{"begin":401,"end":600},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"attributes":[{"subj":"T262","pred":"source","obj":"LitCovid-sentences"},{"subj":"T263","pred":"source","obj":"LitCovid-sentences"},{"subj":"T264","pred":"source","obj":"LitCovid-sentences"}]}],"config":{"attribute types":[{"pred":"source","value type":"selection","values":[{"id":"LitCovid-sentences","color":"#ece493","default":true}]}]}}