LKD-YOLOv8: A Lightweight Knowledge Distillation-Based Method for Infrared Object Detection by Xiancheng Cao, Yueli Hu, Haikun Zhang

“…Nonetheless, the limited computational power of edge devices presents a considerable challenge in achieving an optimal balance between accuracy and computational efficiency in infrared object detection. …”
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Improved YOLOv8-Based Algorithm for Citrus Leaf Disease Detection by Zhengbing Zheng, Yibang Zhang, Luchao Sun

“…The proposed approach uses YOLOv8n as the base model and introduces adaptive convolution into the Backbone, allowing the model to dynamically prioritize different disease features. This modification increases the model’s parameter count without adding to the computational cost in terms of floating-point operations. …”
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Dual-Scale Complementary Spatial-Spectral Joint Model for Hyperspectral Image Classification by Huayue Chen, Yue Sun, Xiang Li, Bochuan Zheng, Tao Chen

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Leveraging machine learning to proactively identify phishing campaigns before they strike by Kun Zhang, Haifeng Wang, Meiyi Chen, Xianglin Chen, Long Liu, Qiang Geng, Yu Zhou

“…Feature selection was conducted using SHapley Additive Explanations (SHAP) and Recursive Feature Elimination (RFE) to enhance interpretability and computational efficiency. …”
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Wilsonian renormalization of neural network Gaussian processes by Jessica N Howard, Ro Jefferson, Anindita Maiti, Zohar Ringel

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Research on multi class pests identification and detection based on fusion attention mechanism with Mask-RCNN-CBAM by Xingwang Wang, Xingwang Wang, Xingwang Wang, Can Hu, Xufeng Wang, Hainie Zha, Xueyong Chen, Shanshan Yuan, Jing Zhang, Jianfeng Liao, Zhangying Ye

“…The framework combines three innovations: (1) a CBAM attention mechanism to amplify pest features while suppressing background noise; (2) a feature-enhanced pyramid network (FPN) for multi-scale feature fusion, enhancing small pest recognition; and (3) a dual-channel downsampling module to minimize detail loss during feature propagation. …”
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Express method for contactless measurement of parameters of thermoelectric materials by A. A. Ashcheulov, I. A. Buchkovskii, I. S. Romanyuk

“…Its distinctive feature is the ability to determine the symmetric and asymmetric components of the electric conductivity of the material values. …”
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Classifying seismic event parameters using artificial intelligence by Abbas Maazallahi, Kameron Bustos, Mohammad Amir Salari, Eli Snir, Payam Norouzzadeh, Bahareh Rahmani

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A Python toolbox for neural circuit parameter inference by Alejandro Orozco Valero, Víctor Rodríguez-González, Noemi Montobbio, Miguel A. Casal, Alejandro Tlaie, Francisco Pelayo, Christian Morillas, Jesús Poza, Carlos Gómez, Pablo Martínez-Cañada

“…Abstract Computational research tools have reached a level of maturity that enables efficient simulation of neural activity across diverse scales. …”
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COMPUTED TOMOGRAPHY IN STUDYING THE SURGICAL ANATOMY OF THE POSTERIOR CRANIAL FOSSA by S. V. Ishkov

“…Objective: to determine the individual roentgenometric parameters of the posterior cranial fossa and the specific features of the location of brain structures on computed tomography scans in terms of their possible use on planning surgical approaches.Material and methods. …”
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Investigation of a Markov Model for Computer System Security Threats by Alexey A. A. Magazev, Valeria F. Tsyrulnik

“…In this work, a model for computer system security threats formulated in terms of Markov processes is investigated. …”
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Mechanistic computational modeling of sFLT1 secretion dynamics. by Amy Gill, Karina Kinghorn, Victoria L Bautch, Feilim Mac Gabhann

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REDETR-RISTD: Real-Time Long-Range Infrared Small Target Detection Network Based on the Reparameterized Efficient Detection Transformer by Ning Li, Daozhi Wei

“…REDETR-RISTD maintains accuracy while significantly reducing computational complexity. First, we introduce a self-developed reparameterized multi-scale feature extraction module (RMSFE). …”
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Ten recommendations for scanning foraminifera by X-ray computed tomography by A. Searle-Barnes, A. Brombacher, A. Brombacher, O. Katsamenis, O. Katsamenis, K. Rankin, M. Mavrogordato, T. Ezard

“…</p> <p>In our case study, the highest beam power resulted in the widest contrast between the subject of interest and the background, allowing the easiest threshold-based segmentation of the object and aiding computers in automated feature extraction.</p> <p>The values of these parameters can exhibit significant variability across individuals, based on the specific needs of the study, the equipment used, and the unique attributes of the samples under consideration. …”
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A computational study of stimulus driven epileptic seizure abatement. by Peter Neal Taylor, Yujiang Wang, Marc Goodfellow, Justin Dauwels, Friederike Moeller, Ulrich Stephani, Gerold Baier

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YOLO-Dynamic: A Detection Algorithm for Spaceborne Dynamic Objects by Haiying Zhang, Zhengyang Li, Chunyan Wang

“…SC_Block_C2f, developed in this study, integrates StarNet and Convolutional Gated Linear Unit (CGLU) operations, improving small-object recognition and feature extraction. Meanwhile, LASF_Neck employs a lightweight multi-scale architecture for optimized feature fusion and faster detection. …”
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LH-YOLO: A Lightweight and High-Precision SAR Ship Detection Model Based on the Improved YOLOv8n by Qi Cao, Hang Chen, Shang Wang, Yongqiang Wang, Haisheng Fu, Zhenjiao Chen, Feng Liang

“…LH-YOLO features only 1.862 M parameters, representing a 38.1% reduction compared to YOLOv8n. …”
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Enhanced detection of malaria infected red blood cells through phase driven classification by Charlotte Kyeremah, Aditya S. Paul, Daniel Haehn, Manoj T. Duraisingh, Chandra S. Yelleswarapu

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Mitigating Selection Bias in Local Optima: A Meta-Analysis of Niching Methods in Continuous Optimization by Junchen Wang, Changhe Li, Yiya Diao

“…As mainstream solvers for black-box optimization problems, evolutionary computation (EC) methods struggle with finding desired optima of lower attractiveness. …”
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2D affine transform parameters by Gaussian elimination with pivoting by Tariq N. Ataiwe, Israa Hatem, Hisham M. Jawad Al Sharaa

“…Geometric transformation is a technique used to define the properties of common features between different images using the same coordinates basis, This method can be effectively used in image processing and computer vision to facilitate the computation process throughout eliminating the need for solving the inverse of the matrix.…”
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