Exploring Gait Recognition in Wild Nighttime Scenes by Haotian Li, Wenjuan Gong, Yutong Li, Yikai Wu, Kechen Li, Jordi Gonzàlez

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SLM-DFS: A systematic literature map of deepfake spread on social media by El-Sayed Atlam, Malik Almaliki, Ghada Elmarhomy, Abdulqader M. Almars, Awatif M.A. Elsiddieg, Rasha ElAgamy

“…The findings of this literature map suggest that DF detection is a multidisciplinary field that requires collaboration between experts in computer vision, machine learning, cybersecurity, and media forensics to address its current and future challenges…”
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Multi-Objective Simulated Annealing for Efficient Task Allocation in UAV-Assisted Edge Computing for Smart City Traffic Management by Ahmed Shamil Mustafa, Salman Yussof, Nurul Asyikin Mohamed Radzi

“…While existing technologies provide solutions for data collection (UAVs), processing (computer vision), and control (reinforcement learning), the integration and resource optimization of these components remains a significant challenge. …”
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Image segmentation and CNN-based deep learning architectures for the modelling on particulate matter formation during solid fuels combustion by Yanchi Jiang, Lanting Zhuo, Xiaojiang Wu, Zhongxiao Zhang, Xinwei Guo, Wei Wang, Cunjiang Fan

“…Three typical solid fuels (coal, biomass, and refuse-derived fuel) were individually combusted in a lab-scale drop tube furnace. The computer Vision method was employed to extract the morphological characteristics of particulate matter (PM) and establish a dataset of 12,637 particle features. …”
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Advances in Light Field Spatial Super-Resolution: A Comprehensive Literature Survey by Wenqi Lyu, Hao Sheng, Wei Ke, Xiao Ma

“…Super-resolution reconstruction of light field images has recently become a central focus in the fields of computational photography and computer vision. We present a systematic review of 17 mainstream light field spatial super-resolution techniques, evaluating their performance across seven public datasets. …”
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SVFRH: A Growth Stage-Based Compartmental Model for Predicting the Disease Incident in Tomato (Solanum lycopersicum) by Athira P. Shaji, S. Hemalatha

“…Over decades, research has primarily focused on addressing these challenges through computer vision and deep learning techniques. In this work, we employ a comprehensive modelling approach that combines compartmental and logistic regression models to thoroughly address disease dynamics in tomato crops, with a particular focus on tomato early blight diseases. …”
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Research on Innovative Apple Grading Technology Driven by Intelligent Vision and Machine Learning by Bo Han, Jingjing Zhang, Rolla Almodfer, Yingchao Wang, Wei Sun, Tao Bai, Luan Dong, Wenjing Hou

“…This study marks the first integration of advanced computer vision, image processing, and machine learning technologies to design an innovative automated apple grading system. …”
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Characterization of Complex Image Spatial Structures Based on Symmetrical Weibull Distribution Model for Texture Pattern Classification by Jinping Liu, Jiezhou He, Zhaohui Tang, Pengfei Xu, Wuxia Zhang, Weihua Gui

“…Texture pattern classification has long been an essential issue in computer vision (CV). However, texture is a kind of perceptual concept of human beings in scene observation or content understanding, which cannot be defined or described clearly in CV. …”
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Monitoring Space Weather: Using Automated, Accurate Neural Network Based Whistler Segmentation for Whistler Inversion by Bálint Ármin Pataki, János Lichtenberger, Mark Clilverd, Gergely Máthé, Péter Steinbach, Szilárd Pásztor, Lilla Murár‐Juhász, Dávid Koronczay, Orsolya Ferencz, István Csabai

“…Here, we present a fully automated way to perform such an image segmentation by leveraging the power of convolutional neural networks, a state‐of‐the‐art method for computer vision tasks. Testing the proposed method against a manually, and semi‐manually segmented whistler data set achieved <10% relative electron density prediction error for 80% of the segmented whistler traces, while for the L shell, the relative error is <5% for 90% of the cases. …”
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ClassWise-SAM-Adapter: Parameter-Efficient Fine-Tuning Adapts Segment Anything to SAR Domain for Semantic Segmentation by Xinyang Pu, Hecheng Jia, Linghao Zheng, Feng Wang, Feng Xu

“…Such achievement of visual foundation model stimulates continuous researches on specific downstream tasks in computer vision. The classwise-SAM-adapter (CWSAM) is designed to adapt the high-performing SAM for landcover classification on space-borne synthetic aperture radar (SAR) images. …”
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Modern possibilities of tear film stability restoration by V.V. Brzheskiy, G.G. Кim, V.А. Bobryshev

“…</p> <p> The article presents a case study of a patient — a student suffering from computer vision syndrome who unsuccessfully used low viscosity tear substitutes while working at a computer. …”
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Anthropometric Landmark Detection Network via Geodesic Heatmap on 3D Human Scan by Min Hee Cha, Jae Hyeon Park, Ji Sun Byun, Sangyeon Ahn, Gyoomin Lee, Seung Hyun Yoon, Sung In Cho

“…With advancement in computer vision and machine learning, researchers have increasingly focused on developing automated anthropometric data extraction technique. …”
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Meat analogues: The relationship between mechanical anisotropy, macrostructure, and microstructure by Miek Schlangen, Iris van der Doef, Atze Jan van der Goot, Mathias P. Clausen, Thomas E. Kodger

“…Mechanical properties are assessed using tensile testing, microstructure is studied using X-ray tomography and confocal laser scanning microscopy, and macrostructure is quantified using a computer vision algorithm based on segmentation and shape features. …”
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Engaging Students in Audiovisual Coding Through Interactive MATLAB GUIs by Carlos Cuevas, Carlos Cortes, Narciso Garcia

“…The tools, developed using MATLAB, were integrated into a computer vision course and assessed through a combination of pre- and post-tests, the System Usability Scale, and the Evaluation Tool for Learning Quality. …”
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An empirical study of LLaMA3 quantization: from LLMs to MLLMs by Wei Huang, Xingyu Zheng, Xudong Ma, Haotong Qin, Chengtao Lv, Hong Chen, Jie Luo, Xiaojuan Qi, Xianglong Liu, Michele Magno

“…Abstract The LLaMA family, a collection of foundation language models ranging from 7B to 65B parameters, has become one of the most powerful open-source large language models (LLMs) and the popular LLM backbone of multi-modal large language models (MLLMs), widely used in computer vision and natural language understanding tasks. …”
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Attention-enhanced optimized deep ensemble network for effective facial emotion recognition by Taimoor Khan, Muhammad Yasir, Chang Choi

“…Facial emotion recognition (FER) is rapidly advancing, with significant applications in healthcare, human-computer interactions, and biometric security, driven by recent advances in artificial intelligence (AI), computer vision, and deep learning. In recent studies, various algorithms have encountered several challenges such as data scarcity, low-resolution images, and suboptimal performance, particularly in real-time applications. …”
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Detection of Adversarial Attacks Using Deep Learning and Features Extracted From Interpretability Methods in Industrial Scenarios by Angel Luis Perales Gomez, Lorenzo Fernandez Maimo, Alberto Huertas Celdran, Felix J. Garcia Clemente

“…The adversarial training technique has been shown to improve the robustness of Machine Learning and Deep Learning models to adversarial attacks in the Computer Vision field. However, the effectiveness of this approach needs to be proven in the field of Anomaly Detection on industrial environments, where adversarial training has critical limitations. …”
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Multitask Learning-Based Pipeline-Parallel Computation Offloading Architecture for Deep Face Analysis by Faris S. Alghareb, Balqees Talal Hasan

“…Therefore, the presented pipeline-parallel architecture can be a cost-effective framework for real-time computer vision applications implemented on resource-limited devices.…”
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Explainable artificial intelligence with fusion-based transfer learning on adverse weather conditions detection using complex data for autonomous vehicles by Khaled Tarmissi, Hanan Abdullah Mengash, Noha Negm, Yahia Said, Ali M. Al-Sharafi

“…Autonomous vehicles (AVs), particularly self-driving cars, have produced a large amount of interest in artificial intelligence (AI), intelligent transportation, and computer vision. Tracing and detecting numerous targets in real-time, mainly in city arrangements in adversarial environmental conditions, has become a significant challenge for AVs. …”
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CGDINet: A Deep Learning-Based Salient Object Detection Algorithm by Chengyu Hu, Jianxin Guo, Hanfei Xie, Qing Zhu, Baoxi Yuan, Yujie Gao, Xiangyang Ma, Jialu Chen, Juan Tian

“…Salient object detection (SOD) is a key preprocessing step in computer vision, widely used in object tracking, action recognition, and image retrieval, among other fields. …”
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