The DRAGON benchmark for clinical NLP by Joeran S. Bosma, Koen Dercksen, Luc Builtjes, Romain André, Christian Roest, Stefan J. Fransen, Constant R. Noordman, Mar Navarro-Padilla, Judith Lefkes, Natália Alves, Max J. J. de Grauw, Leander van Eekelen, Joey M. A. Spronck, Megan Schuurmans, Bram de Wilde, Ward Hendrix, Witali Aswolinskiy, Anindo Saha, Jasper J. Twilt, Daan Geijs, Jeroen Veltman, Derya Yakar, Maarten de Rooij, Francesco Ciompi, Alessa Hering, Jeroen Geerdink, Henkjan Huisman, On behalf of the DRAGON consortium

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Estimation Vehicular Waiting Time at Traffic Build-Up Queues by Mohamed Maher Ata, Mohamed El-Darieby, Baher Abdulhai, Emad Felemban, Saleh Basalamah, Basim Zafar

“…An automated system for queue end monitoring has been proposed using image processing based transformed domain and empirical mode decomposition (EMD) feature extraction systems. …”
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An Efficient Design of DCT Approximation Based on Quantum Dot Cellular Automata (QCA) Technology by Ismail Gassoumi, Lamjed Touil, Bouraoui Ouni, Abdellatif Mtibaa

“…On the other hand, quantum-dot cellular automata (QCA) can present a novel opportunity for the design of highly parallel architectures and algorithms for improving the performance of image and video processing systems. …”
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Advanced Hybrid Brain Tumor Segmentation in MRI: Elephant Herding Optimization Combined with Entropy-Guided Fuzzy Clustering by Baiju Karun, Arunprasath Thiyagarajan, Pallikonda Rajasekaran Murugan, Natarajan Jeyaprakash, Kottaimalai Ramaraj, Rakhee Makreri

“…EHO is utilized to optimize the clustering process, enhancing the algorithm’s ability to delineate tumor boundaries, while entropy-based fuzzy clustering accounts for intensity inhomogeneity and diverse tumor characteristics, promoting more consistent and reliable segmentation results. …”
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Development of software interface for AI-driven weed control in robotic vehicles, with time-based evaluation in indoor and field settings by G C Sunil, Arjun Upadhyay, Xin Sun

“…Conversely, independent paired t-test revels that there is significant difference in image size between lab and field testing. The reduction of herbicide application based on grid map was obtained 79 to 80 %, which does not include YOLOv4 algorithm failure and system synchronization failure. …”
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Automated Surface Crack Identification of Reinforced Concrete Members Using an Improved YOLOv4-Tiny-Based Crack Detection Model by Sofía Rajesh, K. S. Jinesh Babu, M. Chengathir Selvi, M. Chellapandian

“…The digital images captured from the failure of RC beams were analyzed using the CDM of the YOLOv4-tiny algorithm. …”
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Automatic Identification of Weave Patterns of Checked and Colored Fabrics Using Optical Coherence Tomography by Metin Sabuncu, Hakan Ozdemir, Mete U. Akdogan

“…For example, image processing algorithms are known to make errors when dealing with checked and colored fabrics. …”
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Lightweight coal mine conveyor belt foreign object detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…-EIEM module is proposed and embedded into the Backbone section to enhance the feature learning capability for image recognition tasks. Thirdly, to enhance the algorithm’s focus on key features, a Large Separable Kernel Attention mechanism (LSKA) is utilized to improve the original SPPF, thereby boosting the overall performance of the algorithm. …”
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Sensor-free, Camera-only: Low-cost multi-angle CPR skill assessments method based on computer vision by Longxin Liu, Cen Wu, Jiafeng Liu, Jiayi Yu, Meng Bi, Hong Yu

“…We calculate standardized mean times for compressions and respirations, determine operation frequencies, and extract grayscale and jitter signals from compression regions using image processing and Fast Fourier Transform (FFT). …”
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Deep learning-based semantic segmentation with novel navigation line extraction for autonomous agricultural robots by Chijioke Leonard Nkwocha, Ning Wang

“…Then, we proposed a novel navigation line extraction algorithm based on the Douglas–Peucker algorithm which uses the output mask from the semantic segmentation to extract the centre navigation line for robot guidance. …”
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Rice Leaf Disease Classification—A Comparative Approach Using Convolutional Neural Network (CNN), Cascading Autoencoder with Attention Residual U-Net (CAAR-U-Net), and MobileNet-V2... by Monoronjon Dutta, Md Rashedul Islam Sujan, Mayen Uddin Mojumdar, Narayan Ranjan Chakraborty, Ahmed Al Marouf, Jon G. Rokne, Reda Alhajj

“…The initial algorithmic phase involved image pre-processing of the crop images, using a bilateral filter to improve image quality. …”
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Efficient wildlife monitoring: Deep learning-based detection and counting of green turtles in coastal areas by Naoya Noguchi, Hideaki Nishizawa, Taro Shimizu, Junichi Okuyama, Shohei Kobayashi, Kazuyuki Tokuda, Hideyuki Tanaka, Satomi Kondo

“…The reduced performance might be attributable to accumulated errors in detecting green turtles while processing numerous images in the footage (approximately 60 fps). …”
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Simulation and projection of land use and land cover using remote sensing data and CA–Markov model case study by Akash Behera, Kishan Singh Rawat, Sanjeev Kumar, Ali Saeed Almuflih, Naif Almakayeel, Mohamed Rafik N. Qureshi

“…The Talcher region has experienced notable transformations in LULC over the recent decades. Markovian algorithm’s efficiency and validation utilized two images from 2000 and 2010, while validation of CA-Markov predictions relied on a ground-based land cover image from 2020. …”
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Improved lightweight health identification method for plug seedling based on FPGA by Yatao Li, Jiahang Jiang, Junlang Ou, Junhua Tong, Yufei Lin, Jintao Cao

“…The improved Sobel operator has better comprehensive performance on FPGA for images with different resolutions, especially when processing images with smaller resolutions. …”
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Classification of Brain Tumors by Using a Hybrid CNN-SVM Model by Talitha Safa Nabila, Abu Salam

“…An MRI scan is a useful tool for tumor detection. Researchers can process the obtained image data to conduct research capable of detecting brain tumor disease. …”
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3D segmentation of uterine fibroids based on deep supervision and an attention gate by ZhiWei Liu, ChengNv Sun, ChengWei Li, FaJin Lv, FaJin Lv

“…A total of 147 patients' T2-weighted magnetic resonance (T2WI) images were used for training, 49 for validation, and 49 patients' MR Images were used for algorithm testing.ResultsExperimental results show that the proposed method achieves satisfactory segmentation results. …”
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Automatic identification and characteristics analysis of crack tips in rocks with prefabricated defects based on deep learning methods. by Mingtao Gao, Minhui Li, Lu Chen, Zihao Guo, Chengyang Guo, Liping Li, Changsen Bu

“…Especially in the rock specimen analysis of prefabricated multi-angle cracks, image quality and algorithm adaptability have emerged as the critical bottlenecks restricting the identification accuracy. …”
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Joint Optimization of the 3D Model and 6D Pose for Monocular Pose Estimation by Liangchao Guo, Lin Chen, Qiufu Wang, Zhuo Zhang, Xiaoliang Sun

“…In addition, a sliding window combined with a keyframe extraction strategy is adopted to speed up the algorithm processing. Experimental results on synthetic and real image sequences show that the proposed method achieves real-time and online high-precision monocular pose estimation with the absence of an accurate 3D model via the joint optimization of the target’s 3D model and pose.…”
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Lightweight underwater object detection method based on multi-scale edge information selection by Shaobin Cai, Xin Zhou, Wanchen Cai, Liansuo Wei, Yuchang Mo

“…With limited computational power and storage space, underwater equipment often cannot meet the demands for efficient processing. As a result, the YOLO algorithm has been widely applied in underwater object detection. …”
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An Efficient Cryptosystem for Video Surveillance in the Internet of Things Environment by Rafik Hamza, Alzubair Hassan, Teng Huang, Lishan Ke, Hongyang Yan

“…Finally, the proposed framework performs an efficient image encryption algorithm by employing a discrete fractional random transform (DFRT). …”
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