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| author | Jules Laplace <julescarbon@gmail.com> | 2018-11-25 22:19:15 +0100 |
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| committer | Jules Laplace <julescarbon@gmail.com> | 2018-11-25 22:19:15 +0100 |
| commit | ee3d0d98e19f1d8177d85af1866fd0ee431fe9ea (patch) | |
| tree | 41372528e78d4328bc2a47bbbabac7e809c58894 /scraper/datasets/scholar/entries/Large Age-Gap Face Verification by Feature Injection in Deep Networks.csv | |
| parent | 255b8178af1e25a71fd23703d30c0d1f74911f47 (diff) | |
moving stuff
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| -rw-r--r-- | scraper/datasets/scholar/entries/Large Age-Gap Face Verification by Feature Injection in Deep Networks.csv | 1 |
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diff --git a/scraper/datasets/scholar/entries/Large Age-Gap Face Verification by Feature Injection in Deep Networks.csv b/scraper/datasets/scholar/entries/Large Age-Gap Face Verification by Feature Injection in Deep Networks.csv new file mode 100644 index 00000000..9cd388eb --- /dev/null +++ b/scraper/datasets/scholar/entries/Large Age-Gap Face Verification by Feature Injection in Deep Networks.csv @@ -0,0 +1 @@ +Large age-gap face verification by feature injection in deep networks|http://scholar.google.com/https://www.sciencedirect.com/science/article/pii/S0167865517300727|2017|12|8|6980699793307007950|None|http://scholar.google.com/scholar?cites=6980699793307007950&as_sdt=2005&sciodt=0,5&hl=en|http://scholar.google.com/scholar?cluster=6980699793307007950&hl=en&as_sdt=0,5|None|This paper introduces a new method for face verification across large age gaps and also a dataset containing variations of age in the wild, the Large Age-Gap (LAG) dataset, with images ranging from child/young to adult/old. The proposed method exploits a deep convolutional neural network (DCNN) pre-trained for the face recognition task on a large dataset and then fine-tuned for the large age-gap face verification task. Fine-tuning is performed in a Siamese architecture using a contrastive loss function. A feature injection … |
