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在“SpringerLink电子期刊”中，命中：22条，耗时：0.0109827 秒

在所有数据库中总计命中：46条

1. Near-Duplicate Video Retrieval by Aggregating Intermediate CNN Layers

关键词：Near ; duplicate ; Video retrieval ; CNNs ; Bag of keyframes

刊名：Lecture Notes in Computer Science

出版年：2017

2. On the Exploration of Convolutional Fusion Networks for Visual Recognition

关键词：Multi ; scale deep representations ; Locally ; connected fusion module ; Transferring deep features ; Visual recognition

刊名：Lecture Notes in Computer Science

出版年：2017

3. FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-Based CNN Architecture

刊名：Lecture Notes in Computer Science

出版年：2017

4. Bi-Level Multi-column Convolutional Neural Networks for Facial Landmark Point Detection

关键词：Bi ; Level Multi ; column CNNs ; Facial landmark points detection ; Global CNNs ; Local CNNs

刊名：Lecture Notes in Computer Science

出版年：2016

5. Adaptive Convolutional Neural Network and Its Application in Face Recognition

作者： Yuanyuan Zhang ; Dong Zhao ; Jiande Sun ; Guofeng Zou ; Wentao Li

关键词：Convolutional neural network ; Network construction ; Adaptive convolutional neural network ; Global expansion ; Local expansion ; Incremental learning

刊名：Neural Processing Letters

出版年：2016

6. Retinal Image Quality Classification Using Saliency Maps and CNNs

刊名：Lecture Notes in Computer Science

出版年：2016

7. LSTM-CF: Unifying Context Modeling and Fusion with LSTMs for RGB-D Scene Labeling

关键词：RGB ; D scene labeling ; Image context modeling ; Long short ; term memory ; Depth and photometric data fusion

刊名：Lecture Notes in Computer Science

出版年：2016

8. Face Landmark Localization Using a Single Deep Network

关键词：DCNN ; Face landmark localization ; SDN

刊名：Lecture Notes in Computer Science

出版年：2016

9. VLAD Is not Necessary for CNN

关键词：CNN ; Multi ; scale ; Deep learning ; VLAD ; Transfer learning

刊名：Lecture Notes in Computer Science

出版年：2016

10. Joint Event Extraction Based on Skip-Window Convolutional Neural Networks

刊名：Lecture Notes in Computer Science

出版年：2016

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