A machine vision approach for classification and dimensional design of furniture panels using GMM-SVM by Yuan Tian, Li Zhao, Haoxin Li

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Sitting and Standing Intention Detection Based on Dynamical Region Connectivity and Entropy of EEG by Wenwen Chang, Wenchao Nie, Yueting Yuan, Yuchan Zhang, Renjie Lv, Lei Zheng, Guanghui Yan

“…Based on the brain signals, decoding and analyzing the gait features to make a reliable prediction of action intention are the core issues in the brain computer interface (BCI)-based hybrid rehabilitation and intelligent walking aid robot system. …”
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YOLOv8-POS: a lightweight model for coal-rock image recognition by Yanqin Zhao, Wenyu Wang

“…This reduces unnecessary computational overhead while preserving the integrity of critical feature information, thus significantly cutting down on the model’s parameters and computational demands. …”
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Spherical harmonics texture extraction for versatile analysis of biological objects. by Oane Gros, Josiah B Passmore, Noa O Borst, Dominik Kutra, Wilco Nijenhuis, Timothy Fuqua, Lukas C Kapitein, Justin M Crocker, Anna Kreshuk, Simone Köhler

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Student Performance Prediction Using Machine Learning Algorithms by Esmael Ahmed

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Photovoltaic panel defect detection algorithm based on infrared imaging and improved YOLOv8 by Jingdong Wang, Zhu Cheng

“…To address the challenges of high missed detection rates, complex backgrounds, unclear defect features, and uneven difficulty levels in target detection during the industrial process of photovoltaic panel defect detection, this article proposes an infrared detection method based on computer vision, with enhancements built upon the YOLOv8 model. …”
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Feedback control architecture and the bacterial chemotaxis network. by Abdullah Hamadeh, Mark A J Roberts, Elias August, Patrick E McSharry, Philip K Maini, Judith P Armitage, Antonis Papachristodoulou

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iPro-CSAF: identification of promoters based on convolutional spiking neural networks and spiking attention mechanism by Qian Zhou, Jie Meng, Hao Luo

“…Therefore, it is an urgent challenge to develop computational methods for identifying promoters. Most current methods were designed for promoter recognition on few species and required complex feature extraction methods in order to attain high recognition accuracy. …”
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A study on an efficient citrus Huanglong disease detection algorithm based on three-channel aggregated attention by Yizong Wang, Zhengrong Xiao, Hong Wang, Fei Li, Jiya Tian

“…Methods Firstly, a new character to float (C2f) Attention inverse residual moving block (IRMB) module is designed, which significantly enhances the model’s sensitivity to tiny disease features while reducing the number of parameters by fusing the lightweight IRMB with the adaptive attention gating mechanism, and solves the problem of losing key texture information due to downsampling in the traditional C2f module. …”
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Fault Line Selection Method Based on Transfer Learning Depthwise Separable Convolutional Neural Network by Haixia Zhang, Wenao Cheng

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Face to Face: Anthropometry-Based Interactive Face Shape Modeling Using Model Priors by Yu Zhang, Edmond C. Prakash

“…For each facial feature, we compute a set of anthropometric measurements to parameterize the example meshes into a measurement space. …”
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GRSNet: An Ultra-Lightweight Neural Network for 3D Point Cloud Classification and Segmentation by Zourong Long, Gen Tan, You Wu, Hong Yang, Chao Ding

“…Algorithms that directly extract features from raw point cloud data have simple architectures, but they are constrained by computational demands and limited efficiency. …”
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Plant Leaf Recognition using OSSGabor filter and Vision Transformer by Thuy Phuong Khuat, Trang Van, Hoang Thien Van

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Optical Neuroimage Studio (OptiNiSt): Intuitive, scalable, extendable framework for optical neuroimage data analysis. by Yukako Yamane, Yuzhe Li, Keita Matsumoto, Ryota Kanai, Miles Desforges, Carlos Enrique Gutierrez, Kenji Doya

“…OptiNiSt includes the following features. 1) Researchers can easily create analysis pipelines by selecting multiple processing modules, tuning their parameters, and visualizing the results at each step through a graphic user interface in a web browser. 2) In addition to pre-installed tools, new analysis algorithms can be easily added. 3) Once a processing pipeline is designed, the entire workflow with its modules and parameters are stored in a YAML file, which makes the pipeline reproducible and deployable on high-performance computing clusters. 4) OptiNiSt can read image data in a variety of file formats and store the analysis results in NWB (Neurodata Without Borders), a standard data format for data sharing. …”
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RSero: A user-friendly R package to reconstruct pathogen circulation history from seroprevalence studies. by Nathanaël Hozé, Margarita Pons-Salort, C Jessica E Metcalf, Michael White, Henrik Salje, Simon Cauchemez

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CNN based plant disease identification using PYNQ FPGA by Vivek Karthick Perumal, Supriyaa T, Santhosh P R, Dhanasekaran S

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Identification of hateful amharic language memes on facebook using deep learning algorithms by Mequanent Degu Belete, Girma Kassa Alitasb

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The mechanical influence of densification on epithelial architecture. by Christian Cammarota, Nicole S Dawney, Philip M Bellomio, Maren Jüng, Alexander G Fletcher, Tara M Finegan, Dan T Bergstralh

“…This prompted us to ask to what extent epithelial architecture emerges from two mechanical considerations: A) the constraints of densification and B) cell-cell adhesion, a hallmark feature of epithelial cells. To address these questions, we developed a novel polyline cell-based computational model and used it to make theoretical predictions about epithelial architecture upon changes to density and cell-cell adhesion. …”
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On the origins of suboptimality in human probabilistic inference. by Luigi Acerbi, Sethu Vijayakumar, Daniel M Wolpert

“…The degree of suboptimality was modulated by statistical features of the priors but was largely independent of the class of the prior and level of noise in the cue, suggesting that suboptimality in dealing with complex statistical features, such as bimodality, may be due to a problem of acquiring the priors rather than computing with them. …”
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Network archaeology: uncovering ancient networks from present-day interactions. by Saket Navlakha, Carl Kingsford

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