[PDF] Top 20 Local Convolutional Features with Unsupervised Training for Image Retrieval
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Local Convolutional Features with Unsupervised Training for Image Retrieval
... of convolutional architectures for patch ...2 for each input type. Comparative results. We compare the convolutional ar- chitectures on our three patch datasets: RomePatches-train, ... Voir le document complet
10
Satellite image retrieval with pattern spectra descriptors
... Image retrieval is typically achieved by means of computing descriptors, either globally for the whole image or on selected or predetermined parts of the ...per image are used resulting ... Voir le document complet
5
Towards real-time image understanding with convolutional networks
... experimented with two sampling methods when learning the multiscale features: respecting natural frequencies of classes, and balancing them so that an equal amount of each class is shown to the ...2.2. ... Voir le document complet
125
Attention for Image Registration (AiR): an unsupervised Transformer approach
... images features and using different similarity metrics to measure the matching quality between images pairs during the optimization ...[4]. With the rapid promotion of deep learning in the field of medical ... Voir le document complet
10
Graph laplacian for interactive image retrieval
... the image description (feature+similarity) fits (2) the semantic wanted by the ...the features to the user’s feedback. Adapting features might be explicitly achieved or implicitly as a part of the ... Voir le document complet
5
Technical report: supervised training of convolutional spiking neural networks with PyTorch
... networks for image ...a local rule based on relative spike timing between ...supervised training rule to extract features that can be used by an external ...classifier. For ... Voir le document complet
25
Image Retrieval with Reciprocal and shared Nearest Neighbors
... based image retrieval systems from re- search laboratory prototypes into large scale, efficient and effective commercial ...powerful local descriptors such as SIFT (Lowe, 2004) into a suitable vector ... Voir le document complet
12
Training deep convolutional architectures for vision
... BETTER IMAGE FEATURES ...by training single-layer neural networks to solve three image classification ...experimented with fully-connected hidden units, as well as locally-connected ... Voir le document complet
116
Linear and Deformable Image Registration with 3D Convolutional Neural Networks
... addressed with numerous deep neural net- work architectures ...of convolutional neural networks (CNNs) as robust methods for image registration [14, ...introduced with impressive ... Voir le document complet
11
Convolutional Patch Representations for Image Retrieval: an Unsupervised Approach
... grid with a patch ...results with preceding layers, that are cheaper to compute and require smaller input ...scales with good performance on Hol- idays and ...of convolutional feature ... Voir le document complet
22
LOCAL VISUAL FEATURES EXTRACTION FROM TEXTURE+DEPTH CONTENT BASED ON DEPTH IMAGE ANALYSIS
... 2D local fea- tures: the invariance to viewpoint ...sual features, including SIFT, are designed to be invariant to in-plane ...deal with for two reasons: i) the visual information contained in ... Voir le document complet
6
Fully Convolutional Neural Networks For Remote Sensing Image Classification
... Color image (b) Fuzzy map (c) Binary map ...Pleiades image, with an FCN. CNN against 8.47s with the FCN, showing a 10x ...FCNs for the classification of a Pleiades image covering ... Voir le document complet
5
General pairwise Markov chains for unsupervised image segmentation
... that unsupervised image segmentation via PMCs models [9, 2] has been done for a particular subclass of ...framework for image segmentation with ...tions with universal ... Voir le document complet
6
Unsupervised Classifier Selection Approach for Hyperspectral Image Classification
... using training accuracy measure- ment is not recommended, since the training samples do not provide a fair global representation of HSI, especially when a very limited number of training samples is ... Voir le document complet
5
Local Visual Patch for 3D Shape Retrieval
... curves with the same shape. For example, if we rotate a curve in R 3 , we get a different SRVF but its shape remains ...functions. For example, for a curve β : S 1 → R ... Voir le document complet
6
Visual object retrieval by graph features
... object retrieval system based on the bag-of-visual-words (BoVW) approach ...an image by a set of ...an image are partitioned into several graphs by minimizing an energy via ...built for each ... Voir le document complet
4
An exploration of diversified user strategies for image retrieval with relevance feedback
... Feedback with Support Vector Machines It is assumed that every image is represented by a signature describing its vi- sual ...The image signatures employed here are presented in Section ...images ... Voir le document complet
18
High-Dimensional Mixture Models For Unsupervised Image Denoising (HDMI)
... the image itself or from a basis of natural image patches and possibly adapted to each image [36, 41, ...value for K and use covariance matrices with pre- defined ranks, we explore in ... Voir le document complet
30
Predicting Future Instance Segmentation by Forecasting Convolutional Features
... account for in- dividual objects, but rather lumps them together by assigning them to the same category label, ...associating with each pixel an instance label, as show in ...crucial for down-stream ... Voir le document complet
22
Efficient colour texture image retrieval by combination of colour and texture features in wavelet domain
... Content-based image retrieval (CBIR) is an active research field in pattern recognition and computer ...important features that are used in CBIR. Using the combination of both features ... Voir le document complet
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