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- research-articleJuly 2024
3WAUS: A novel three-way adaptive uncertainty-suppressing model for facial expression recognition
Information Sciences: an International Journal (ISCI), Volume 677, Issue CAug 2024https://doi.org/10.1016/j.ins.2024.120962AbstractFacial Expression Recognition (FER) remains a challenging task due to the uncertainty caused by the noisy labels, interrater disagreement, and the inter-class similarity of facial expressions. However, the majority of existing FER methods are ...
Highlights- First application of the three-way decision in facial expression recognition.
- Propose a dynamic adaptive re-labeling method for facial expression recognition.
- Extensive experimental analysis validates the superiority of the ...
- research-articleJuly 2024
Robust image segmentation and bias field correction model based on image structural prior constraint
Expert Systems with Applications: An International Journal (EXWA), Volume 251, Issue COct 2024https://doi.org/10.1016/j.eswa.2024.123961AbstractIn this paper, we propose an advanced variational model for image segmentation and bias correction. In contrast to the majority of existing level set segmentation models that only consider illumination bias fields, we additionally consider the ...
Highlights- A novel image segmentation model based on image structural prior is introduced.
- An adaptive regularization constraint for adaptive restoration of image intensity.
- The model is robust to images with noise and intensity ...
- research-articleJuly 2024
Disentangling Instructive Information from Ranked Multiple Candidates for Multi-Document Scientific Summarization
SIGIR '24: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information RetrievalJuly 2024, Pages 2028–2037https://doi.org/10.1145/3626772.3657705Automatically condensing multiple topic-related scientific papers into a succinct and concise summary is referred to as Multi-Document Scientific Summarization (MDSS). Currently, while commonly used abstractive MDSS methods can generate flexible and ...
- research-articleAugust 2024
A novel approach for estimating fractional cover of crops by correcting angular effect using radiative transfer models and UAV multi-angular spectral data
- Yuanyuan Pan,
- Wenxuan Wu,
- Jiaoyang He,
- Jie Zhu,
- Xi Su,
- Wanyu Li,
- Dong Li,
- Xia Yao,
- Tao Cheng,
- Yan Zhu,
- Weixing Cao,
- Yongchao Tian
Computers and Electronics in Agriculture (COEA), Volume 222, Issue CJul 2024https://doi.org/10.1016/j.compag.2024.109030Highlights- The Multi-FVC model was developed based on PROSAIL model and Beer-Lambert law to retrieve FVC.
- Multi-FVC model was more potential in estimating FVC and suppressing the influence of soil.
- Soil effect caused by the second axis in the ...
Fractional vegetation cover (FVC) plays an important role in spectral unmixing, crop growth monitoring, crop light interception calculation, and yield estimation. However, the spectral reflectance would change with view zenith angles (VZAs), and ...
- research-articleJuly 2024
Domain-incremental learning without forgetting based on random vector functional link networks
AbstractIncremental learning is a paradigm that extends knowledge by learning from new data, often used to add new classes to an existing model or to learn a new domain. It imposes strict limitations on the model’s access to data from previous tasks, ...
Highlights- We propose a strategy to train a simplified RVFL network for a more effective domain IL.
- Simplified RVFL can achieve performance comparable to joint training in domain-IL.
- Training RVFL using our algorithm completely resolves ...
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- research-articleAugust 2024
Transformer-based Generation of Confrontation Network in Digital Art Applications
MIDA '24: Proceedings of the 2024 International Conference on Machine Intelligence and Digital ApplicationsMay 2024, Pages 862–867https://doi.org/10.1145/3662739.3672317With the continuous progress and development of society, the application of generative adversarial network (GAN) in digital art is increasing day by day. As a deep learning model, Transformer can bring better help to the development of GAN. This article ...
- research-articleJuly 2024
A chlorophyll-constrained semi-empirical model for estimating leaf area index using a red-edge vegetation index
Computers and Electronics in Agriculture (COEA), Volume 220, Issue CMay 2024https://doi.org/10.1016/j.compag.2024.108891Highlights- The effect of leaf chlorophyll on estimating leaf area index (LAI) was evaluated.
- A chlorophyll-constrained semi-empirical (CSE) model was proposed to estimate LAI.
- The variation of leaf chlorophyl content (LCC) was incorporated ...
The parameter of leaf area index (LAI) provides valuable information about plant growth. Most remote sensing methods for estimating LAI are based on the vegetation indices (VIs) in the visible and near-infrared (VNIR) spectral regions. Recently, ...
- research-articleApril 2024
MTM: Rethinking Memory Profiling and Migration for Multi-Tiered Large Memory
EuroSys '24: Proceedings of the Nineteenth European Conference on Computer SystemsApril 2024, Pages 803–817https://doi.org/10.1145/3627703.3650075Multi-terabyte large memory systems are often characterized by more than two memory tiers with different latency and bandwidth. Multi-tiered large memory systems call for rethinking of memory profiling and migration because of the unique problems unseen ...
- research-articleJuly 2024
AW4C: A Commit-Aware C Dataset for Actionable Warning Identification
MSR '24: Proceedings of the 21st International Conference on Mining Software RepositoriesApril 2024, Pages 133–137https://doi.org/10.1145/3643991.3644885Excessive non-actionable warnings generated by static program analysis tools can hinder developers from utilizing these tools effectively. Leveraging learning-based approaches for actionable warning identification has demonstrated promise in boosting ...
- research-articleApril 2024
A novel cascade calibration method for robotic grinding system
Intelligent Service Robotics (SPISR), Volume 17, Issue 3May 2024, Pages 505–520https://doi.org/10.1007/s11370-024-00534-5AbstractThis paper presents an efficient cascade calibration method with an improved Levenberg–Marquardt and sine–cosine hybrid algorithm to enhance the absolute positioning accuracy of robotic grinding systems. To expedite convergence in the Levenberg–...
- research-articleApril 2024
AFSRNet: learning local descriptors with adaptive multi-scale feature fusion and symmetric regularization
Applied Intelligence (KLU-APIN), Volume 54, Issue 7Apr 2024, Pages 5406–5416https://doi.org/10.1007/s10489-024-05418-wAbstractMulti-scale feature fusion has been widely used in handcrafted descriptors, but has not been fully explored in deep learning-based descriptor extraction. Simple concatenation of descriptors of different scales has not been successful in ...
- research-articleMarch 2024
Understanding Concurrent Radiative Wireless Power Transfer in the IoT: Out of Myth, into Reality
IEEE Wireless Communications (IEEEWIRCOM), Volume 31, Issue 3June 2024, Pages 398–405https://doi.org/10.1109/MWC.022.2200592Radiative wireless power transfer plays a vital role in addressing the challenges facing today's Internet of Things. Challenges include frequent battery replacement, excessive electronic waste, and autonomous operation in hard-to-reach places. ...
- research-articleMarch 2024
Spaceborne distributed aperture radar maneuvering target detection approach with space-time 2D hybrid integration technique
Highlights- The proposed NRFRP in time dimension can accurately eliminate DFM with a onestep process of matrix multiplication, which greatly reduces the computational burden.
- The introduced MSCFT in time dimension corrects RWM accurately without ...
Moving target detection in spaceborne distributed aperture radar (SBDAR) is a challenging task in civilian and military fields. The common issues are that the current methods suffer from the large range cell migration (RCM) and time-varying ...
- research-articleMarch 2024
XVDPU: A High-Performance CNN Accelerator on the Versal Platform Powered by the AI Engine
- Xijie Jia,
- Yu Zhang,
- Guangdong Liu,
- Xinlin Yang,
- Tianyu Zhang,
- Jia Zheng,
- Dongdong Xu,
- Zhuohuan Liu,
- Mengke Liu,
- Xiaoyang Yan,
- Hong Wang,
- Rongzhang Zheng,
- Li Wang,
- Dong Li,
- Satyaprakash Pareek,
- Jian Weng,
- Lu Tian,
- Dongliang Xie,
- Hong Luo,
- Yi Shan
ACM Transactions on Reconfigurable Technology and Systems (TRETS), Volume 17, Issue 2Article No.: 20, Pages 1–24https://doi.org/10.1145/3617836Today, convolutional neural networks (CNNs) are widely used in computer vision applications. However, the trends of higher accuracy and higher resolution generate larger networks. The requirements of computation or I/O are the key bottlenecks. In this ...
- research-articleMarch 2024
On Item-Sampling Evaluation for Recommender System
ACM Transactions on Recommender Systems (TORS), Volume 2, Issue 1Article No.: 7, Pages 1–36https://doi.org/10.1145/3629171Personalized recommender systems play a crucial role in modern society, especially in e-commerce, news, and ads areas. Correctly evaluating and comparing candidate recommendation models is as essential as constructing ones. The common offline evaluation ...
- research-articleJuly 2024
A negative selection algorithm with hypercube interface detectors for anomaly detection▪
Applied Soft Computing (APSC), Volume 154, Issue CMar 2024https://doi.org/10.1016/j.asoc.2024.111339AbstractNegative selection algorithms play an important role in anomaly detection. Interface detectors are a special negative selection algorithm that completely eliminates outer holes, but there are detection blind areas. This paper proposes a negative ...
Highlights- HI-detector breaks away from the hyperspherical detector used by traditional negative selection algorithms.
- HI-detector consists of a cluster of multiple hypercube self-samples.
- HI-detector completely eliminates duplicate coverage ...
- research-articleFebruary 2024
MaskDUF: Data uncertainty learning in masked face recognition with mask uncertainty fluctuation
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PCMar 2024https://doi.org/10.1016/j.eswa.2023.121995AbstractAs an essential component of experts and intelligent systems, Masked Face Recognition (MFR) has been applied to various applications, but it is still a challenging task due to the aggravated uncertainty caused by mask occlusion. Most existing MFR ...
Highlights- Introduce data uncertainty learning theory into Masked Face Recognition.
- An adaptive variance regularizer for masked face is proposed to learn uncertainty.
- The mask uncertainty fluctuation is proposed to learn tight intra-class ...
- research-articleApril 2024
Multi-branch-feature fusion super-resolution network
Digital Signal Processing (DISP), Volume 145, Issue CFeb 2024https://doi.org/10.1016/j.dsp.2023.104332AbstractDeep network attracts extensive attention in the single image super-resolution field. Most of the deep network-based super-resolution methods usually employ a feature extraction stream to generate the input for the next extraction module during ...
- research-articleJanuary 2024
Fusing structural information with knowledge enhanced text representation for knowledge graph completion
Data Mining and Knowledge Discovery (DMKD), Volume 38, Issue 3May 2024, Pages 1316–1333https://doi.org/10.1007/s10618-023-00998-6AbstractAlthough knowledge graphs store a large number of facts in the form of triplets, they are still limited by incompleteness. Hence, Knowledge Graph Completion (KGC), defined as inferring missing entities or relations based on observed facts, has ...
- research-articleJanuary 2024
Improved small foreign object debris detection network based on YOLOv5
Journal of Real-Time Image Processing (SPJRTIP), Volume 21, Issue 1Feb 2024https://doi.org/10.1007/s11554-023-01399-0AbstractIn response to the challenges of detecting foreign object debris (FOD) on airport runways, where the objects are small in size and have indistinct features leading to false detections and missed detections, significant improvements were made to ...