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A decade survey of content based image retrieval using deep learning
SR Dubey - IEEE Transactions on Circuits and Systems for …, 2021 - ieeexplore.ieee.org
The content based image retrieval aims to find the similar images from a large scale dataset
against a query image. Generally, the similarity between the representative features of the …
against a query image. Generally, the similarity between the representative features of the …
Compressed video action recognition
CY Wu, M Zaheer, H Hu, R Manmatha… - Proceedings of the …, 2018 - openaccess.thecvf.com
Training robust deep video representations has proven to be much more challenging than
learning deep image representations. This is in part due to the enormous size of raw video …
learning deep image representations. This is in part due to the enormous size of raw video …
Adaptive quantization for deep neural network
Y Zhou, SM Moosavi-Dezfooli, NM Cheung… - Proceedings of the …, 2018 - ojs.aaai.org
Abstract In recent years Deep Neural Networks (DNNs) have been rapidly developed in
various applications, together with increasingly complex architectures. The performance …
various applications, together with increasingly complex architectures. The performance …
Fda: Feature disruptive attack
A Ganeshan, V BS, RV Babu - Proceedings of the IEEE/CVF …, 2019 - openaccess.thecvf.com
Abstract Though Deep Neural Networks (DNN) show excellent performance across various
computer vision tasks, several works show their vulnerability to adversarial samples, ie …
computer vision tasks, several works show their vulnerability to adversarial samples, ie …
Dist-gan: An improved gan using distance constraints
We introduce effective training algorithms for Generative Adversarial Networks (GAN) to
alleviate mode collapse and gradient vanishing. In our system, we constrain the generator …
alleviate mode collapse and gradient vanishing. In our system, we constrain the generator …
Efficient and deep person re-identification using multi-level similarity
Abstract Person Re-Identification (ReID) requires comparing two images of person captured
under different conditions. Existing work based on neural networks often computes the …
under different conditions. Existing work based on neural networks often computes the …
Attention-based pyramid aggregation network for visual place recognition
Visual place recognition is challenging in the urban environment and is usually viewed as a
large scale image retrieval task. The intrinsic challenges in place recognition exist that the …
large scale image retrieval task. The intrinsic challenges in place recognition exist that the …
Combination of multiple global descriptors for image retrieval
Recent studies in image retrieval task have shown that ensembling different models and
combining multiple global descriptors lead to performance improvement. However, training …
combining multiple global descriptors lead to performance improvement. However, training …
Saliency inside: Learning attentive CNNs for content-based image retrieval
In content-based image retrieval (CBIR), one of the most challenging and ambiguous tasks
is to correctly understand the human query intention and measure its semantic relevance …
is to correctly understand the human query intention and measure its semantic relevance …
Unsupervised adversarial instance-level image retrieval
With the wide use of visual sensors in the Internet of Things (IoT) in the past decades, huge
amounts of images are captured in people's daily lives, which poses challenges to …
amounts of images are captured in people's daily lives, which poses challenges to …