Uncertainty-aware diabetic retinopathy detection using deep learning enhanced by Bayesian approaches by Mohsin Akram, Muhammad Adnan, Syed Farooq Ali, Jameel Ahmad, Amr Yousef, Tagrid Abdullah N. Alshalali, Zaffar Ahmed Shaikh

“…Abstract Deep learning-based medical image analysis has shown strong potential in disease categorization, segmentation, detection, and even prediction. …”
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Autonomous Robotic Manipulation: Real-Time, Deep-Learning Approach for Grasping of Unknown Objects by Malak H. Sayour, Sharbel E. Kozhaya, Samer S. Saab

“…Recent advancement in vision-based robotics and deep-learning techniques has enabled the use of intelligent systems in a wider range of applications requiring object manipulation. …”
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Image recognition technology for bituminous concrete reservoir panel cracks based on deep learning. by Kai Hu, Yang Ling, Jie Liu

“…This study introduces a novel deep learning-based anomaly model for effective crack detection. …”
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Blast loading prediction in a typical urban environment based on Bayesian deep learning by Weiwen Peng, Meilin Pan, Chunjiang Leng, Shufei Wang, Wei Zhong

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Deep learning and hyperspectral features for seedling stage identification of barnyard grass in paddy field by Siqiao Tan, Qiang Xie, Wenshuai Zhu, Yangjun Deng, Lei Zhu, Xiaoqiao Yu, Zheming Yuan, Zheming Yuan, Yuan Chen, Yuan Chen

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Deep learning–assisted diagnosis of acute mesenteric ischemia based on CT angiography images by Lei Song, Xuesong Zhang, Jian Zhang, Jie Wu, Jinkai Wang, Feng Wang

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Motion Route Planning and Obstacle Avoidance Method for Mobile Robot Based on Deep Learning by Jichao Cui, Guanghua Nie

“…In order to improve the motion route planning effect and obstacle avoidance effect of mobile robots, this paper combines the deep learning theory to analyze the motion route planning and obstacle avoidance process of mobile robots. …”
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Deep Learning Integration in PAPR Reduction in 5G Filter Bank Multicarrier Systems by Mohamed Hussien Moharam, AYA W. wafik

“…It also combines them with active constellation extension (TRACE) and with deep learning (TR-Net). TR-net decreases the greatest PAPR reduction by around 8.6 dB compared to the original value. …”
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Deep-Learning Prediction Model with Serial Two-Level Decomposition Based on Bayesian Optimization by Xue-Bo Jin, Hong-Xing Wang, Xiao-Yi Wang, Yu-Ting Bai, Ting-Li Su, Jian-Lei Kong

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The Health Index Prediction Model and Application of PCP in CBM Wells Based on Deep Learning by Chaodong Tan, Song Wang, Hanwen Deng, Guoqing Han, Guanghao Du, Wenrong Song, Xiongying Zhang

“…Therein, a health index (HI) formulation was made based on deep learning, and a statistical method was used to define the health status of PCP wells as being healthy, subhealthy, or faulty. …”
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Global TEC Map Fusion Through a Hybrid Deep Learning Model: RFGAN by Zhou Chen, Kecheng Zhou, Haimeng Li, Jing‐song Wang, Zhihai Ouyang, Xiaohua Deng

“…For the integrity and continuity of the global observation data, deep learning can obtain a global Ionospheric total electron content (TEC) map by fusing multi‐source TEC maps. …”
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Advancements and Challenges in Character Recognition: A Comparative Analysis of CNN and Deep Learning Approaches by Yang Ximin

“…This paper provides a comprehensive review of character recognition technologies, focusing on the application of Convolutional Neural Networks (CNN) and deep learning methodologies. Through an analysis of three key studies, the research highlights the strengths and limitations of current approaches. …”
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From Backtracking To Deep Learning: A Survey On Methods For Solving Constraint Satisfaction Problems by Fatima AIT HATRIT, Kamal AMROUN

“…To address this, extensive research has been conducted, leading to the development of effective techniques and algorithms for different types of CSPs, ranging from exhaustive search methods, which explore the entire search space, to modern techniques that use deep learning to learn how to solve CSPs. This paper represents a descriptive and synthetic overview of various CSPs solving methods, organized by approach: systematic search methods, inference and filtering methods, structural decomposition methods, local search-based methods, and deep learning-based methods. …”
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A deep learning‐based attack on text CAPTCHAs by using object detection techniques by Jiawei Nian, Ping Wang, Haichang Gao, Xiaoyan Guo

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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

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UAV-Multispectral Based Maize Lodging Stress Assessment with Machine and Deep Learning Methods by Minghu Zhao, Dashuai Wang, Qing Yan, Zhuolin Li, Xiaoguang Liu

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Deep Learning algorithm for the assessment of the first damage initiation monitoring the energy release of materials by Dario Santonocito, Dario Milone

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Accurate LAI estimation of soybean plants in the field using deep learning and clustering algorithms by Bing Shi, Luqi Guo, Lejun Yu

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GMTBLC: a deep learning-based bi-modal network traffic classification method by WEI Debin, JIANG Qinlong, WEN Jinglong, WANG Xinrui

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Deep learning-driven defense strategies for mitigating DDoS attacks in cloud computing environments by Doaa Mohsin Abd Ali Afraji, Jaime Lloret, Lourdes Peñalver

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