Heading Severity
Heading Severity is a methodological construct within pruning techniques in machine learning that quantifies the extent of structural reduction applied to a model's architecture by measuring the depth and breadth of node or layer removal relative to its original topology.
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2017–2026
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R. H. Elliott, Leslie Mann · The Canadian Entomologist · 1996 · 39 citations
Parisa Soleimani, Gholamhossein Mosahebi, Mina Koohi Habibi · African Journal of Agricultural Research · 2011 · 10 citations · Full text
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Japan International Research Center for Agricultural Sciences
Tsukuba, Japan
1 h-index
5 publications
50 citations

Okayama University
Okayama, Japan
1 h-index
1 publications
10 citations
Shenyang Agricultural University
Shenyang, China
1 h-index
6 publications
168 citations
Agriculture and Agri-Food Canada
Ottawa, Canada
1 h-index
2 publications
78 citations
Hokkaido Agricultural Research Center
Sapporo, Japan
1 h-index
4 publications
40 citations
Western Region Agricultural Research Center
Hiroshima, Japan
1 h-index
1 publications
10 citations
Chungnam National University
Daejeon, South Korea
1 h-index
3 publications
84 citations
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1 publications · 28 citations
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1 publications · 39 citations
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1 publications · 10 citations
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AJAR · 1 publications · 10 citations
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