Detecting objects in synthetic aperture radar (SAR) imagery has received much attention in recent years since SAR can operate in all-weather and day-and-night conditions. Due to the prosperity and development of convolutional neural networks (CNNs),...
Image fusion is an effective and efficient way to express the feature information of an infrared image and abundant detailed information of a visible image in a single fused image. However, obtaining a fused result with good visual effect, while pres...
With the rise of general models, transformers have been adopted in visual object tracking algorithms as feature fusion networks. In these trackers, self-attention is used for global feature enhancement. Cross-attention is applied to fuse the features...
Image retrieval based on a convolutional neural network (CNN) has attracted great attention among researchers because of the high performance. The pooling method has become a research hotpot in the task of image retrieval in recent years. In this pap...
Environment perception is one of the major issues in autonomous driving systems. In particular, effective and robust drivable road region detection still remains a challenge to be addressed for autonomous vehicles in multi-lane roads, intersections a...
This paper focuses on vessel detection through the fusion of synthetic aperture radar (SAR) images acquired from spaceborne–airborne collaborative observations. The vessel target detection task becomes more challenging when it features inshore interf...
Image inpainting aims to fill in corrupted regions with visually realistic and semantically plausible contents. In this paper, we propose a progressive image inpainting method, which is based on a forked-then-fused decoder network. A unit called PC-R...
Remote sensing (RS) image change detection (CD) is the procedure of detecting the change regions that occur in the same area in different time periods. A lot of research has extracted deep features and fused multi-scale features by convolutional neur...
Infrared–visible image fusion is valuable across various applications due to the complementary information that it provides. However, the current fusion methods face challenges in achieving high-quality fused images. This paper identifies a lim...
Camouflage design necessitates region-consistent colour and texture synthesis. However, practical datasets are frequently constrained by scarce paired supervision and cross-source distribution shift, which impede reliable generalisation across hetero...
Aiming at the problem of poor robustness and the low effectiveness of target tracking in complex scenes by using single color features, an object-tracking algorithm based on dual color feature fusion via dimension reduction is proposed, according to...
Atomic force acoustic microscopy (AFAM) is a measurement method that uses the probe and acoustic wave to image the surface and internal structures of different materials. For cellular material, the morphology and phase images of AFAM reflect the oute...
Current reported spatiotemporal solutions for fusing multisensor aerosol optical depth (AOD) products used to recover gaps either suffer from unacceptable accuracy levels, i.e., fixed rank smooth (FRS), or high time costs, i.e., Bayesian maximum entr...
An efficient method for the infrared and visible image fusion is presented using truncated Huber penalty function smoothing and visual saliency based threshold optimization. The method merges complementary information from multimodality source images...
This paper proposes an infrared (IR) and visible image fusion method introducing region segmentation into the dual-tree complex wavelet transform (DTCWT) region. This method should effectively improve both the target indication and scene spectrum fea...
In order to achieve the effective computer recognition of the She ethnic clothing from different regions through the extraction of color features, this paper proposes a She ethnic clothing classification method based on the Flower Pollination Algorit...
To improve and enrich the wheat growth information, visible and thermal infrared (TIR) remote sensing images were simultaneously acquired by an unmanned aerial vehicle (UAV). A novel algorithm was proposed for fusing the visible and TIR images combin...
Multi-focus image fusion is a very essential method of obtaining an all focus image from multiple source images. The fused image eliminates the out of focus regions, and the resultant image contains sharp and focused regions. A novel multiscale image...
Multi-modal (i.e., visible, near-infrared, and thermal-infrared) vehicle re-identification has good potential to search vehicles of interest in low illumination. However, due to the fact that different modalities have varying imaging characteristics,...
This paper proposes a 3D vehicle-detection algorithm based on multimodal feature fusion to address the problem of low vehicle-detection accuracy in unmanned system environment awareness. The algorithm matches the coordinate relationships between the...
Scene classification of high-resolution remote sensing images (HRRSI) is one of the most important means of land-cover classification. Deep learning techniques, especially the convolutional neural network (CNN) have been widely applied to the scene c...
Object detection is an essential task for autonomous vehicles to ensure safety. Due to the complexity of mining environments, it is difficult to detect objects accurately and robustly. To address these issues, this paper proposes a novel 3D LiDAR-bas...
High-resolution hyperspectral images are in great demand but hard to acquire due to several existing fundamental and technical limitations. A practical way around this is to fuse multiple multiband images of the same scene with complementary spatial...
In this paper, we present a reliable and robust biometric verification method based on bimodal physiological characteristics of palms, including the palmprint and palm-dorsum vein patterns. The proposed method consists of five steps: (1) automaticall...
In many actual applications, fused image is essential to contain high-quality details for achieving a comprehensive representation of the real scene. However, existing image fusion methods suffer from loss of details because of the error accumulation...
Precipitation is one of the crucial variables in the hydrological and ecological cycles. High-quality precipitation data are of great importance for climate change, water resource management, and agricultural research over complex terrains. Recently,...
MLP-based weakly supervised crowd counting approaches have made significant advancements over the past few years. However, owing to the limited datasets, the current MLP-based methods do not consider the problem of region-to-region dependency in the...
Recently, with the widespread application of deep learning networks, appearance-based gaze estimation has made breakthrough progress. However, most methods focus on feature extraction from the facial region while neglecting the critical role of the e...
The growing need to monitor changes in the surface of the Earth requires a high-quality, accessible Digital Elevation Model (DEM) dataset, whose development has become a challenge in the field of Earth-related research. The purpose of this paper is t...
With the prosperity of e-commerce applications, the web data of products are presented by multiple modalities, e.g., vision and language. For mining the product characteristics, multimodal attribute values are crucial, which are extracted from textua...
Convolution neural network (CNN)-based detectors have shown great performance on ship detections of synthetic aperture radar (SAR) images. However, the performance of current models has not been satisfactory enough for detecting multiscale ships and...
Foreign objects such as kites, nests and balloons, etc., suspended on transmission lines may shorten the insulation distance and cause short-circuits between phases. A detection method for foreign objects on transmission lines is proposed, which comb...
Object detection in point cloud data is one of the key components in computer vision systems, especially for autonomous driving applications. In this work, we present Voxel-Feature Pyramid Network, a novel one-stage 3D object detector that utilizes r...
Fused silica glass is a critical material in many industries due to its superior physicochemical properties. The detection of subsurface damage (SSD) poses fundamental challenges that directly affect the performance of fused silica glass. The polariz...
In precision agriculture, effective monitoring of corn pest regions is crucial to developing early scientific prevention strategies and reducing yield losses. However, complex backgrounds and small objects in real farmland bring challenges to accurat...
To get more obvious target information and more texture features, a new fusion method for the infrared (IR) and visible (VIS) images combining regional energy (RE) and intuitionistic fuzzy sets (IFS) is proposed, and this method can be described by s...
To understand driving environments effectively, it is important to achieve accurate detection and classification of objects detected by sensor-based intelligent vehicle systems, which are significantly important tasks. Object detection is performed f...
Multimodal image fusion is a promising technology designed to fuse information from different medical sensors, which offer structured insights for disease diagnosis and treatment. However, existing 2D-centric fusion methods fail to capture 3D spatial...
In tasks of transmission line defect detection, traditional object detection algorithms are ineffective, with few training samples of defective components. Meta-learning uses multi-task learning as well as fine-tuning to learn common features in diff...
Because high-precision DEMs are costly to obtain, while low-precision DEMs often fail to meet accuracy requirements for watershed flood simulation, this study proposes a multi-source DEM fusion method based on the Random Forest algorithm. This method...
Infrared and visible image fusion combines the thermal cues captured by infrared sensors with the rich structural and texture information provided by visible images. This technique is particularly valuable for security surveillance, nighttime scene p...
In the field of remote sensing, cloud cover severely reduces the quality of satellite observations of the earth. Due to the complete absence of information in cloud-covered regions, cloud removal with a single optical image is an ill-posed problem. S...
Compared with discrete emotion space, image emotion analysis based on dimensional emotion space can more accurately represent fine-grained emotion. Meanwhile, this high-precision representation of emotion requires dimensional emotion prediction metho...
To address video jitter and key-structure positional drift in industrial surveillance scenarios, this paper proposes a video stabilization method based on key-structure semantic constraints and grid motion fusion. First, Segment Anything Model 3 (SAM...
Multi-focus image fusion is the process of combining focused regions of two or more images to obtain a single all-in-focus image. It is an important research area because a fused image is of high quality and contains more details than the source imag...
The geological structure in the Red River fault zone (RRF) and adjacent areas is complex. Due to the lack of high-precision gravity data in the study area, it is difficult to obtain the distribution of materials within the Earth’s crust. In thi...
In this paper, a diverse-region hyperspectral image classification (DRHy) method is proposed by considering both irregularly local pixels and globally contextual connections between pixels. Specifically, the proposed method is operated on non-Euclide...
In the recent years, visual navigation has been considered an effective mechanism for achieving an autonomous landing of Unmanned Aerial Vehicles (UAVs). Nevertheless, with the limitations of visual cameras, the effectiveness of visual algorithms is...
When objects are obscured by shadows or dim surroundings, image quality is improved by fusing near-infrared and visible-light images. At night, when visible and NIR lights are insufficient, long-wave infrared (LWIR) imaging can be utilized, necessita...
Fusing infrared and visible images can effectively compensate for the inherent limitations of each modality in different scenes, resulting in fused images that contain richer information. However, existing methods often struggle to balance global dep...
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