[HTML][HTML] An overview of deep learning in medical imaging focusing on MRI
AS Lundervold, A Lundervold - Zeitschrift für Medizinische Physik, 2019 - Elsevier
What has happened in machine learning lately, and what does it mean for the future of
medical image analysis? Machine learning has witnessed a tremendous amount of attention …
medical image analysis? Machine learning has witnessed a tremendous amount of attention …
SIFT meets CNN: A decade survey of instance retrieval
In the early days, content-based image retrieval (CBIR) was studied with global features.
Since 2003, image retrieval based on local descriptors (de facto SIFT) has been extensively …
Since 2003, image retrieval based on local descriptors (de facto SIFT) has been extensively …
R2former: Unified retrieval and reranking transformer for place recognition
Abstract Visual Place Recognition (VPR) estimates the location of query images by matching
them with images in a reference database. Conventional methods generally adopt …
them with images in a reference database. Conventional methods generally adopt …
Opengan: Open-set recognition via open data generation
Real-world machine learning systems need to analyze novel testing data that differs from the
training data. In K-way classification, this is crisply formulated as open-set recognition, core …
training data. In K-way classification, this is crisply formulated as open-set recognition, core …
D2-net: A trainable cnn for joint description and detection of local features
In this work we address the problem of finding reliable pixel-level correspondences under
difficult imaging conditions. We propose an approach where a single convolutional neural …
difficult imaging conditions. We propose an approach where a single convolutional neural …
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 …
Fixing the train-test resolution discrepancy
Data-augmentation is key to the training of neural networks for image classification. This
paper first shows that existing augmentations induce a significant discrepancy between the …
paper first shows that existing augmentations induce a significant discrepancy between the …
Visual place recognition: A survey from deep learning perspective
Visual place recognition has attracted widespread research interest in multiple fields such
as computer vision and robotics. Recently, researchers have employed advanced deep …
as computer vision and robotics. Recently, researchers have employed advanced deep …
Unifying deep local and global features for image search
Image retrieval is the problem of searching an image database for items that are similar to a
query image. To address this task, two main types of image representations have been …
query image. To address this task, two main types of image representations have been …
Dolg: Single-stage image retrieval with deep orthogonal fusion of local and global features
Image Retrieval is a fundamental task of obtaining images similar to the query one from a
database. A common image retrieval practice is to firstly retrieve candidate images via …
database. A common image retrieval practice is to firstly retrieve candidate images via …