Improved YOLOv4-tiny based on attention mechanism for skin detection.
PeerJ. Computer science, ISSN: 2376-5992, Vol: 9, Page: e1288
2023
- 1Citations
- 7Captures
- 1Mentions
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations1
- Citation Indexes1
- Captures7
- Readers7
- Mentions1
- News Mentions1
- 1
Most Recent News
Reports Outline Computer Science Research from University of Shanghai for Science and Technology (Improved YOLOv4-tiny based on attention mechanism for skin detection)
2023 MAR 29 (NewsRx) -- By a News Reporter-Staff News Editor at Computer News Today -- New study results on computer science have been published.
Article Description
An automatic bathing robot needs to identify the area to be bathed in order to perform visually-guided bathing tasks. Skin detection is the first step. The deep convolutional neural network (CNN)-based object detection algorithm shows excellent robustness to light and environmental changes when performing skin detection. The one-stage object detection algorithm has good real-time performance, and is widely used in practical projects.
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