Invention Grant
- Patent Title: Filter design for small target detection on infrared imagery using normalized-cross-correlation layer in neural networks
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Application No.: US17046355Application Date: 2018-04-10
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Publication No.: US11775837B2Publication Date: 2023-10-03
- Inventor: Erdem Akagunduz , Huseyin Seckin Demir
- Applicant: ASELSAN ELEKTRONIK SANAYI VE TICARET ANONIM SIRKETI
- Applicant Address: TR Ankara
- Assignee: ASELSAN ELEKTRONIK SANAYI VE TICARET ANONIM SIRKETI
- Current Assignee: ASELSAN ELEKTRONIK SANAYI VE TICARET ANONIM SIRKETI
- Current Assignee Address: TR Ankara
- Agency: Bayramoglu Law Offices LLC
- International Application: PCT/TR2018/050156 2018.04.10
- International Announcement: WO2019/199244A 2019.10.17
- Date entered country: 2020-10-09
- Main IPC: G06V10/32
- IPC: G06V10/32 ; G06V10/75 ; G06V10/82 ; G06N3/084 ; G06F18/2113 ; G06N3/045

Abstract:
A filter design method for a small target detection on infrared imagery using a normalized-cross-correlation layer in neural networks, including the steps of: Normalizing inputs and filters of a convolutional neural network, wherein normalizing inputs and filters of the convolutional neural network provides faster convergence in a limited database. Defining a forward function of a normalization layer in the convolutional neural network, wherein the forward function of the normalization layer in the convolutional neural network is used for training a neural network. Defining a derivative function of the normalization layer for a back propagation in a neural network training phase. Training created neural networks with datasets, wherein the datasets consist of target and background views and using trained neural networks in the small target detection.
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