Search Results for author:
Found 21 papers, 4 papers with code
Multiview Transformer: Rethinking Spatial Information in Hyperspectral Image Classification
To aggregate the multiview information, a fully-convolutional SED with a U-shape in spectral dimension is introduced to extract a multiview feature map.
Quantum-Inspired Spectral-Spatial Pyramid Network for Hyperspectral Image Classification
Using QSSN as the building block, we propose an end-to-end quantum-inspired spectral-spatial pyramid network (QSSPN) for HSI feature extraction and classification.
SEVGGNet-LSTM: a fused deep learning model for ECG classification
This paper presents a fused deep learning algorithm for ECG classification.
Uformer-ICS: A Specialized U-Shaped Transformer for Image Compressive Sensing
We develop a projection-based transformer block by integrating the prior projection knowledge of CS into the original transformer blocks, and then build a symmetrical reconstruction model using the projection-based transformer blocks and residual convolutional blocks.
GCT: Graph Co-Training for Semi-Supervised Few-Shot Learning
First, we propose a novel label prediction method, Isolated Graph Learning (IGL).
Automatic Color Image Stitching Using Quaternion Rank-1 Alignment
To quantitatively evaluate image stitching performance, we propose a perceptual seam quality (PSQ) measure to calculate misalignments of local regions along the seamline.
CIM: Class-Irrelevant Mapping for Few-Shot Classification
(2) Use the FEM to extract the features of novel data (with few labeled samples and totally different categories from base data), then classify them with the to-be-designed classifier.
Detection of Deepfake Videos Using Long Distance Attention
And a spatial-temporal model is proposed which has two components for capturing spatial and temporal forgery traces in global perspective respectively.
LineCounter: Learning Handwritten Text Line Segmentation by Counting
In this paper, we propose a novel Line Counting formulation for HTLS -- that involves counting the number of text lines from the top at every pixel location.
SauvolaNet: Learning Adaptive Sauvola Network for Degraded Document Binarization
The AST module further consolidates the outputs from MWS and PWA and predicts the final adaptive threshold for each pixel location.
Bridging the Distribution Gap of Visible-Infrared Person Re-identification with Modality Batch Normalization
Visible-infrared cross-modality person re-identification (VI-ReID), whose aim is to match person images between visible and infrared modality, is a challenging cross-modality image retrieval task.
Unified Batch All Triplet Loss for Visible-Infrared Person Re-identification
Visible-Infrared cross-modality person re-identification (VI-ReID), whose aim is to match person images between visible and infrared modality, is a challenging cross-modality image retrieval task.
Learning Domain-invariant Graph for Adaptive Semi-supervised Domain Adaptation with Few Labeled Source Samples
Traditional domain adaptation algorithms assume that enough labeled data, which are treated as the prior knowledge are available in the source domain.
Geometry Constrained Weakly Supervised Object Localization
The detector predicts the object location defined by a set of coefficients describing a geometric shape (i. e. ellipse or rectangle), which is geometrically constrained by the mask produced by the generator.
Universal chosen-ciphertext attack for a family of image encryption schemes
During the past decades, there is a great popularity employing nonlinear dynamics and permutation-substitution architecture for image encryption.
Multimedia
Hypergraph p-Laplacian Regularization for Remote Sensing Image Recognition
Graph based SSL and manifold regularization based SSL including Laplacian regularization (LapR) and Hypergraph Laplacian regularization (HLapR) are representative SSL methods and have achieved prominent performance by exploiting the relationship of sample distribution.
Ensemble p-Laplacian Regularization for Remote Sensing Image Recognition
Therefore, we develop an ensemble p-Laplacian regularization (EpLapR) to fully approximate the intrinsic manifold of the data distribution.
Discriminant Projection Representation-based Classification for Vision Recognition
Representation-based classification methods such as sparse representation-based classification (SRC) and linear regression classification (LRC) have attracted a lot of attentions.
Vision Recognition using Discriminant Sparse Optimization Learning
Based on this model, we then propose a classifier called locality-based discriminant sparse representation (LDSR).
Color Face Recognition using High-Dimension Quaternion-based Adaptive Representation
To obtain the high dimension correlation information among different color channels, we further propose the high-dimension quaternion-based adaptive representation (HD-QAR).
Pairwise Linear Regression Classification for Image Set Retrieval
This paper proposes the pairwise linear regression classification (PLRC) for image set retrieval.
