Multiscale Feature Fusion Attention Lightweight Facial Expression Recognition by Jinyuan Ni, Xinyue Zhang, Jianxun Zhang

“…The use of a modified depthwise separable convolution in the feature extraction network reduces the computational effort associated with the network parameters and enhances the characterization of the extracted features through a channel shuffle operation. …”
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Adaptive temporal compression for reduction of computational complexity in human behavior recognition by Haixin Huang, Yuyao Wang, Mingqi Cai, Ruipeng Wang, Feng Wen, Xiaojie Hu

“…With the advancement of deep learning algorithms and computer hardware, the conventional two-dimensional convolution technique for training video models has been replaced by three-dimensional convolution, which enables the extraction of spatio-temporal features. …”
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Mathematical modelling with computational fractional order for the unfolding dynamics of the communicable diseases by Mati ur Rahman, Yeliz Karaca, Ravi P. Agarwal, Sergio Adriani David

“…Mathematical models based on computational fractional orders, employed for accurate modelling of complex dynamic systems, can ensure the implementation of various analytical, numerical and computing methods encompassing their applications to emerging and ever-varying real-world problems. …”
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High-Resolution Computed Tomography of Single Breast Cancer Microcalcifications in Vivo by Kazumasa Inoue, Fangbing Liu, Jack Hoppin, Elaine P. Lunsford, Christian Lackas, Jacob Hesterman, Robert E. Lenkinski, Hirofumi Fujii, John V. Frangioni

“…Microcalcification is a hallmark of breast cancer and a key diagnostic feature for mammography. We recently described the first robust animal model of breast cancer microcalcification. …”
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Testing of Technical Indicators of Accumulators by Means of Complex Computer Model of EV by Fedotovs Jurijs, Bunina Inna, Zhiravetska Anastasia, Andrianova Svetlava

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Modeling and Simulations of Retina-Like Three-Dimensional Computational Ghost Imaging by Kaiyu Zhang, Jie Cao, Qun Hao, Fanghua Zhang, Yongchao Feng, Yang Cheng

“…R-3DCGI models are developed, and corresponding simulations are conducted to verify and evaluate the accuracy and features of the R-3DCGI. Results show that the models obtain rotation and scaling invariances and compress redundant information, thereby improving imaging efficiency over the traditional computational ghost imaging. …”
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A Space-Time Plume Algorithm to Represent and Compute Dynamic Places by Brent Dell, May Yuan

“…Point clustering analysis commonly assumes events occur in an empty space and therefore ignores geospatial features where events take place. This research introduces relational density, a novel concept redefining density as relative to the spatial structure of geospatial features rather than an absolute measure. …”
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Bearing Fault Prediction Based on Mixed Domain Features and GWO-SVM by Xuan Zhou, Ruiyang Xia, Zhaodong Zhang, Sasa Duan, Mao Cheng, Chengjiang Zhou, Min Mao

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Radiomics Signature of Aging Myocardium in Cardiac Photon-Counting Computed Tomography by Alexander Hertel, Mustafa Kuru, Johann S. Rink, Florian Haag, Abhinay Vellala, Theano Papavassiliu, Matthias F. Froelich, Stefan O. Schoenberg, Isabelle Ayx

“…<b>Conclusions</b>: Radiomics texture features of the left ventricular myocardium outperformed conventional parameters like EAT density and thickness in differentiating age groups, offering a potential imaging biomarker for myocardial aging. …”
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Improvement of the Cross-Scale Multi-Feature Stereo Matching Algorithm by Nan Chen, Dongri Shan, Peng Zhang

“…To address weak-textured regions in large-scale component images and reduce mismatches in stereo matching, we propose a cross-scale multi-feature stereo matching algorithm. In the cost-computation stage, the sum of absolute differences (SAD), census, and modified census cost aggregation are employed as cost-calculation methods. …”
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Edge computing privacy protection method based on blockchain and federated learning by Chen FANG, Yuanbo GUO, Yifeng WANG, Yongjin HU, Jiali MA, Han ZHANG, Yangyang HU

“…Aiming at the needs of edge computing for data privacy, the correctness of calculation results and the auditability of data processing, a privacy protection method for edge computing based on blockchain and federated learning was proposed, which can realize collaborative training with multiple devices at the edge of the network without a trusted environment and special hardware facilities.The blockchain was used to endow the edge computing with features such as tamper-proof and resistance to single-point-of-failure attacks, and the gradient verification and incentive mechanism were incorporated into the consensus protocol to encourage more local devices to honestly contribute computing power and data to the federated learning.For the potential privacy leakage problems caused by sharing model parameters, an adaptive differential privacy mechanism was designed to protect parameter privacy while reducing the impact of noise on the model accuracy, and moments accountant was used to accurately track the privacy loss during the training process.Experimental results show that the proposed method can resist 30% of poisoning attacks, and can achieve privacy protection with high model accuracy, and is suitable for edge computing scenarios that require high level of security and accuracy.…”
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Evaluation of the volume and function of the right atrial appendage using computed tomography by Yang Liu, Tong Pan, Xin Tian, Cai-Ying Li

“…Abstract Objective To assess the volume and function of the right atrial appendage (RAA) in patients with sinus rhythm using 256-slice spiral computed tomography (CT) angiography. Methods A total of 60 patients with normal cardiac CT imaging features were enrolled in this retrospective study. …”
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Speech Analysis as a Tool for Detection and Monitoring of Medical Conditions: A review by Magdalena IGRAS-CYBULSKA, Daria HEMMERLING, Mariusz ZIÓŁKO, Wojciech DATKA, Ewa STOGOWSKA, Michał KUCHARSKI, Rafał RZEPKA, Bartosz ZIÓŁKO

“…A selection of articles was performed to identify studies that assess voice features quantitatively in selected disorders by acoustic and linguistic voice analysis. …”
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Feature-Separated Lightweight Model for Road Extraction in Wild Environments by Che Shi, Yuefeng Cen, Gang Cen

“…This design enhances prediction performance without significantly increasing parameters, reducing computational demands and making the model more adaptable for large-scale remote sensing tasks. …”
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Development and application of distributed computing system in inverse problems of fracture mechanics by Arkady N. Soloviev, Pavel V. Vasiliev, Lyubov A. Podkolzina

“…This simplifies the process of the system deployment, and increases the productivity of the computing process. A finite element model with a large set of parameters is calculated. …”
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Dynamic activation and enhanced image contour features for object detection by Jun Wu, Jiahui Zhu, Xin Tong, Tianliang Zhu, Tianyi Li, Chunzhi Wang

“…This paper proposes a lightweight and efficient object detection model based on YOLOv4, first using the lightweight network GhostNet to extract image features and reduce the number of parameters and computation of the backbone structure; then combining AFmodule and Meta-ACON activation function to enhance the feature extraction capability of the backbone network, which strengthen the mode’s ability to capture image spatial feature information; this paper also designs the RL-PAFPN feature fusion structure is with the Reslayer module to further improve the model’s ability to extract and fuse image features. …”
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Feature fusion with attributed deepwalk for protein–protein interaction prediction by Mei-Yuan Cao, Suhaila Zainudin, Kauthar Mohd Daud

“…However, current computational methods often rely on single feature types or simple feature concatenation, potentially missing the complex nature of protein interactions. …”
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AFQSeg: An Adaptive Feature Quantization Network for Instance-Level Surface Crack Segmentation by Shaoliang Fang, Lu Lu, Zhu Lin, Zhanyu Yang, Shaosheng Wang

“…In addition, the model significantly reduces computational cost, achieving a 78.5–88.7% reduction in parameter size and up to 96.8% improvement in inference speed, making it more efficient and deployable for real-world crack detection applications.…”
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Computer Multimedia Art Pattern Creation Based on P-Filling Algorithm by Wenli Lian

“…Experimental results show that, through this production model, users can produce a large number of computer multimedia art patterns with hand-drawn style features through very little interaction and parameter control.…”
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Leveraging advanced feature extraction for improved kidney biopsy segmentation by Muhammad Wajeeh Us Sima, Chengliang Wang, Muhammad Arshad, Jamshed Ali Shaikh, Salem Alkhalaf, Fahad Alturise

“…While the Segment Anything Model (SAM) excels in natural image segmentation, its direct application to medical imaging underperforms due to (1) insufficient preservation of fine-grained anatomical details, (2) computational inefficiency on gigapixel whole-slide images (WSIs), and (3) poor adaptation to domain-specific features like staining variability and sparse annotations. …”
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