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06/01/2022
Fair Comparison between Efficient Attentions
Transformers have been successfully used in various fields and are becom...
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11/19/2021
Rethinking Query, Key, and Value Embedding in Vision Transformer under Tiny Model Constraints
A vision transformer (ViT) is the dominant model in the computer vision ...
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05/31/2021
Training Domain-invariant Object Detector Faster with Feature Replay and Slow Learner
In deep learning-based object detection on remote sensing domain, nuisan...
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03/05/2021
Extending Contrastive Learning to Unsupervised Coreset Selection
Self-supervised contrastive learning offers a means of learning informat...
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11/18/2020
FixBi: Bridging Domain Spaces for Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) methods for learning domain invaria...
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09/24/2019
Fast and Accurate Convolutional Object Detectors for Real-time Embedded Platforms
With the improvements in the object detection networks, several variatio...
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02/20/2018
Co-occurrence matrix analysis-based semi-supervised training for object detection
One of the most important factors in training object recognition network...
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11/16/2017
Less-forgetful Learning for Domain Expansion in Deep Neural Networks
Expanding the domain that deep neural network has already learned withou...
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09/12/2017
Can Deep Neural Networks Match the Related Objects?: A Survey on ImageNet-trained Classification Models
Deep neural networks (DNNs) have shown the state-of-the-art level of per...
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12/20/2016
End-to-End Pedestrian Collision Warning System based on a Convolutional Neural Network with Semantic Segmentation
Traditional pedestrian collision warning systems sometimes raise alarms ...
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03/05/2015