Determination of the area index of lettuce leaves with a monocular camera by Laimonas Kairiūkštis, Başak Yalçıner, Emre Özkul

“…This study showcases the potential of computer vision and machine learning algorithms in transforming traditional agricultural practices into more efficient and data-driven processes. …”
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Transforming traffic accident investigations: a virtual-real-fusion framework for intelligent 3D traffic accident reconstruction by Yanzhan Chen, Qian Zhang, Fan Yu

“…This study proposes a novel virtual-real-fusion simulation framework that integrates traffic accident generation, unmanned aerial vehicle (UAV)-based image collection, and a 3D traffic accident reconstruction pipeline with advanced computer vision techniques and unsupervised 3D point cloud clustering algorithms. …”
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Skin Cancer Segmentation and Classification Using Vision Transformer for Automatic Analysis in Dermatoscopy-Based Noninvasive Digital System by Galib Muhammad Shahriar Himel, Md. Masudul Islam, Kh. Abdullah Al-Aff, Shams Ibne Karim, Md. Kabir Uddin Sikder

“…In recent years, deep learning models have shown remarkable success in various computer vision tasks, including image classification. …”
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A Review on Person Re-Identification Techniques and Its Analysis by C. Selvan, H. Anwar Basha, K. Meenakshi, Soumyalatha Naveen

“…Person re-identification (Re-ID) emerges as a captivating realm within computer vision, dedicated to the task of recognizing the same individual across diverse camera angles or locations. …”
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Degrade or Super-Resolve to Recognize? Bridging the Domain Gap for Cross-Resolution Face Recognition by Klemen Grm, Berk Kemal Ozata, Alperen Kantarci, Vitomir Struc, Hazim Kemal Ekenel

“…Our results show that the combination of standard computer vision approaches such as degradation, super-resolution, feature fusion, and score fusion can be used to substantially improve performance on the task of low resolution face recognition using off-the-shelf face recognition models without re-training on the target domain.…”
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Face Detection Using Hybrid SNN-ANN to Process Neuromorphic Event Stream by Waseem Shariff, Paul Kielty, Joe Lemley, Peter Corcoran

“…This paper tackles the challenges of face detection, a vital computer vision task with wide-ranging applications, particularly in driver monitoring systems, where both accuracy and computational efficiency are crucial. …”
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Multi-Scale Channel Distillation Network for Image Compressive Sensing by Tianyu Zhang, Kuntao Ye, Yue Zhang, Rui Lu

“…Recently, convolutional neural networks (CNNs) have demonstrated striking success in computer vision tasks. Methods based on CNNs for image compressive sensing (CS) have also gained prominence. …”
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Fault Detection in Induction Machines Using Learning Models and Fourier Spectrum Image Analysis by Kevin Barrera-Llanga, Jordi Burriel-Valencia, Angel Sapena-Bano, Javier Martinez-Roman

“…This methodology offers a scalable solution for predictive maintenance in induction motors, effectively combining signal processing, computer vision, and explainability techniques.…”
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Aircraft Detection for Remote Sensing Images Based on Deep Convolutional Neural Networks by Liming Zhou, Haoxin Yan, Yingzi Shan, Chang Zheng, Yang Liu, Xianyu Zuo, Baojun Qiao

“…Aircraft detection for remote sensing images, as one of the fields of computer vision, is one of the significant tasks of image processing based on deep learning. …”
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Frozen Weights as Prior for Parameter-Efficient Fine-Tuning by Xiaolong Ma, Peishun Liu, Haojie Gao, Zikang Yan, Ningning Ma, Wenqiang Liu, Xuefang Wang, Ruichun Tang

“…In the fields of natural language processing and computer vision, the emergence of large pre-trained models has led to the adoption of fine-tuning them for downstream tasks as an important paradigm. …”
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FSDN-DETR: Enhancing Fuzzy Systems Adapter with DeNoising Anchor Boxes for Transfer Learning in Small Object Detection by Zhijie Li, Jiahui Zhang, Yingjie Zhang, Dawei Yan, Xing Zhang, Marcin Woźniak, Wei Dong

“…The advancement of Transformer models in computer vision has rapidly spurred numerous Transformer-based object detection approaches, such as DEtection TRansformer. …”
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Automatic detection and counting of wheat spike based on DMseg-Count by Hecang Zang, Yilong Peng, Meng Zhou, Guoqiang Li, Guoqing Zheng, Hualei Shen

“…Compared with other deep learning models, the proposed DMseg-Count model can detect wheat spike image in challenging situations, and has better computer vision processing capabilities and performance evaluation detection effect. …”
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Streamlined photoacoustic image processing with foundation models: A training-free solution by Handi Deng, Yucheng Zhou, Jiaxuan Xiang, Liujie Gu, Yan Luo, Hai Feng, Mingyuan Liu, Cheng Ma

“…Foundation models (FMs) have rapidly evolved and have achieved significant accomplishments in computer vision tasks. Specifically, the prompt mechanism conveniently allows users to integrate image prior information into the model, making it possible to apply models without any training. …”
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Artificial Visual System for Stereo-Orientation Recognition Based on Hubel-Wiesel Model by Bin Li, Yuki Todo, Zheng Tang

“…The local-to-global information aggregation thought within the Hubel-Wiesel model not only contributed to neurophysiology but also inspired the development of computer vision fields. In this paper, we provide a clear and efficient conceptual understanding of stereo-orientation selectivity and propose a quantitative explanation for its generation based on the thought of local-to-global information aggregation within the Hubel-Wiesel model and develop an artificial visual system (AVS) for stereo-orientation recognition. …”
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Accelerating Deep Learning-Based Morphological Biometric Recognition with Field-Programmable Gate Arrays by Nourhan Zayed, Nahed Tawfik, Mervat M. A. Mahmoud, Ahmed Fawzy, Young-Im Cho, Mohamed S. Abdallah

“…Convolutional neural networks (CNNs) are increasingly recognized as an important and potent artificial intelligence approach, widely employed in many computer vision applications, such as facial recognition. …”
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Real-time detection of road surface friction coefficient: A new framework integrating diffusion model and Transformer in Transformer algorithms by Zhangcun Yan, Lishengsa Yue, Wang Luo, Jian Sun

“…The primary contribution of this study is the integration of generative artificial intelligence and computer vision algorithms to enhance RSFC recognition accuracy. …”
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The Recent Technologies to Curb the Second-Wave of COVID-19 Pandemic by M. Poongodi, Mohit Malviya, Mounir Hamdi, Hafiz Tayyab Rauf, Seifedine Kadry, Orawit Thinnukool

“…Large data sets need to be advanced so that extensive models related to deep analysis can be used to combat Coronavirus infection, which can be done by applying Artificial intelligence techniques such as Natural Language Processing (NLP), Machine Learning (ML), and Computer vision to varying processing files. This article aims to furnish variation sets of innovations that can be utilized to eliminate COVID-19 and serve as a resource for the coming generations. …”
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“Play by play”: A dataset of handball and basketball game situations in a standardized spaceZenodo by Bruno Cabado, Bertha Guijarro-Berdiñas, Emilio J. Padrón

“…The dataset consists of synthetic data generated from real video frames, including 308,805 labeled handball frames and 56,578 labeled basketball frames extracted from 2105 handball and 383 basketball 5-s video clips.Experts manually labeled the video clips based on the respective sports, while the individual frames were automatically labeled using computer vision and machine learning techniques. The dataset encompasses seven classes of game situations: left attack, left counterattack, left penalty, right attack, right counterattack, right penalty, and timeout. …”
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Real-time detection and monitoring of public littering behavior using deep learning for a sustainable environment by Eaman Alharbi, Ghadah Alsulami, Sarah Aljohani, Waad Alharbi, Somayah Albaradei

“…Leveraging surveillance cameras and advanced computer vision technology, SAWN aims to identify and reduce instances of littering. …”
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Advancing skeleton-based human behavior recognition: multi-stream fusion spatiotemporal graph convolutional networks by Fenglin Liu, Chenyu Wang, Zhiqiang Tian, Shaoyi Du, Wei Zeng

“…Grasping the intricacies of human behaviors depicted within these multimedia contexts has evolved into a pivotal quandary within the domain of computer vision. The technology of behavior recognition finds its practical application across domains such as human-computer interaction, intelligent surveillance, and anomaly detection, exhibiting a robust blend of pragmatic utility and scholarly significance. …”
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