A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit <a rel="external noopener" href="https://ieeexplore.ieee.org/ielx7/6287639/8600701/08895799.pdf">the original URL</a>. The file type is <code>application/pdf</code>.
<i title="Institute of Electrical and Electronics Engineers (IEEE)">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a>
In recent years, deep neural networks (DNNs) have been widely applied in many areas, such as computer vision and pattern recognition. However, we observe that most of the DNNs include redundant layers. Hence, in this paper, we introduce a novel method named incremental layers resection (ILR) to resect the redundant layers in DNNs, while preserving their learning performances. ILR uses a multistage learning strategy to incrementally resect the inconsequential layers. In each stage, it preserves<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2019.2952615">doi:10.1109/access.2019.2952615</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ipm6yjvhkzfvzcmmyavm2wxgoq">fatcat:ipm6yjvhkzfvzcmmyavm2wxgoq</a> </span>
more »... he data representations learned by the original network, while connecting the two nearby layers of each resected one. Particularly, based on a teacher-student knowledge transfer framework, we have designed the layer-level learning and overall learning procedures to enforce the resected network performing similarly with the original one. Extensive experiments demonstrate that, compared to the original networks, the compressed ones by ILR need only about half of the storage space and have higher inference speed. More importantly, they even deliver higher classification accuracy than the original networks.
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210429060049/https://ieeexplore.ieee.org/ielx7/6287639/8600701/08895799.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/6e/77/6e77646e12850fcb0a1ce1088de073b6a0ed37c6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2019.2952615"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>