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Article
Open Set Recognition in Real World
Open set recognition (OSR) constitutes a critical endeavor within the domain of computer vision, frequently deployed in applications, such as autonomous driving and medical imaging recognition. Existing OSR me...
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Article
An integrated smartphone-based electrochemical detection system for highly sensitive and on-site detection of chemical oxygen demand by copper-cobalt bimetallic oxide-modified electrode
A portable and integrated electrochemical detection system has been constructed for on-site and real-time detection of chemical oxygen demand (COD). The system mainly consists of four parts: (i) sensing electr...
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Article
Long-tailed object detection of kitchen waste with class-instance balanced detector
Intelligent detection and classification of kitchen waste can promote ecological sustainability by replacing inefficient manual processes. However, the presence of non-degradable waste mixed in kitchen waste o...
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Article
A robust newton iterative algorithm for acoustic location based on solving linear matrix equations in the presence of various noises
Among many prevalent acoustic location techniques, the location problems can be modelled as solving a linear equation. Although many mature algorithms have been developed to solve the linear equation in acoust...
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Article
Multi-attribute object detection benchmark for smart city
Object detection is an algorithm that recognizes and locates the objects in the image and has a wide range of applications in the visual understanding of complex urban scenes. Existing object detection benchma...
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Article
Unpaired remote sensing image super-resolution with content-preserving weak supervision neural network
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Article
Self-supervised patient-specific features learning for OCT image classification
Deep learning’s great success in image classification is heavily reliant on large-scale annotated datasets. However, obtaining labels for optical coherence tomography (OCT) data requires the significant effort...
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Article
Hybrid first and second order attention Unet for building segmentation in remote sensing images
Recently, building segmentation (BS) has drawn significant attention in remote sensing applications. Convolutional neural networks (CNNs) have become the mainstream analysis approach in this field owing to the...
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Chapter and Conference Paper
Disentanglement Network for Unsupervised Speckle Reduction of Optical Coherence Tomography Images
Optical coherence tomography (OCT) has received increasing attention in the diagnosis of ophthalmic diseases due to its non-invasive character. However, the speckle noise associated with the low-coherence inte...
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Chapter
Reconstruction of Retinal OCT Images with Sparse Representation
In addition to the speckle noise introduced in the acquisition process, clinical-used OCT images often have high resolution and thus create a heavy burden for storage and transmission. To alleviate these probl...
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Article
Open AccessOpen source software for automatic detection of cone photoreceptors in adaptive optics ophthalmoscopy using convolutional neural networks
Imaging with an adaptive optics scanning light ophthalmoscope (AOSLO) enables direct visualization of the cone photoreceptor mosaic in the living human retina. Quantitative analysis of AOSLO images typically r...
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Article
SAR Image Despeckling Via Structural Sparse Representation
A novel synthetic aperture radar (SAR) image despeckling method based on structural sparse representation is introduced. The proposed method utilizes the fact that different regions in SAR images correspond to...
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Article
Spectral–Spatial Hyperspectral Image Classification Based on KNN
Fusion of spectral and spatial information is an effective way in improving the accuracy of hyperspectral image classification. In this paper, a novel spectral–spatial hyperspectral image classification method...
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Article
Pansharpening Based on Intrinsic Image Decomposition
A fused image of high spatial and spectral resolutions can be obtained by fusing a panchromatic (PAN) image with a multi-spectral (MS) image. In this paper, a new image fusion method is proposed, based on an i...
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Chapter and Conference Paper
Spectral-Spatial Hyperspectral Image Classification Using Superpixel and Extreme Learning Machines
We propose an efficient framework for hyperspectral image (HSI) classification based on superpixel and extreme learning machines (ELMs). One superpixel can be regarded as a small region consisting of a number ...
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Chapter and Conference Paper
Hyperspectral Image Classification by Exploiting the Spectral-Spatial Correlations in the Sparse Coefficients
This paper proposes a novel hyperspectral image (HSI) classification method based on sparse model, which incorporates the spectral and spatial information of the sparse coefficient. Firstly, a sparse dictionar...
