Resilience Analysis of Urban Road Networks Based on Adaptive Signal Controls: Day-to-Day Traffic Dynamics with Deep Reinforcement Learning by Wen-Long Shang, Yanyan Chen, Xingang Li, Washington Y. Ochieng

“…The results show that the proposed adaptive signal control based on deep reinforcement learning can achieve better resilience in most of the cases, particularly in the scenarios of moderate and severe disruptions. …”
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I-NeRV: A Single-Network Implicit Neural Representation for Efficient Video Inpainting by Jie Ji, Shuxuan Fu, Jiaju Man

“…While implicit neural representations have shown promise for video inpainting, most of the existing research still revolves around image inpainting and does not fully account for the spatiotemporal continuity and relationships present in videos. …”
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Benchmark Study of Point Cloud Semantic Segmentation Architectures on Strawberry Organs by Rundong Xu, Hiroki Naito, Fumiki Hosoi

“…With the increasing consumer demand for healthy and natural foods, strawberries have emerged as one of the most popular small berries globally. Consequently, careful investigation of the relationship between leaf photosynthetic activity (source strength) and fruit development (sink strength) during strawberry growth provides important insights for maximizing the production potential of this crop. …”
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Vertically Recurrent Neural Networks for Sub‐Grid Parameterization by P. Ukkonen, M. Chantry

“…We achieve near‐perfect offline accuracy, and the forecast skill of a suite of global weather simulations using the emulator are for the most part statistically indistinguishable from reference runs. …”
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Towards Synthetic Augmentation of Training Datasets Generated by Mobility-on-Demand Service Using Deep Variational Autoencoders by Martin Gregurić, Filip Vrbanić, Edouard Ivanjko

“…The machine learning-based approaches for analysing the mobility needs of users are currently the most prevalent approach in the mobility-on-demand (MoD) analysis. …”
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Multi-View Collaborative Training and Self-Supervised Learning for Group Recommendation by Feng Wei, Shuyu Chen

“…By analyzing interaction histories, these systems automatically filter and recommend items that are most likely to resonate with users. Recently, with the swift advancement of social networking, group recommendation has emerged as a compelling research area, enabling personalized recommendations for groups of users. …”
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A novel multi-scale and fine-grained network for large choroidal vessels segmentation in OCT by Wei Huang, Qifeng Yan, Lei Mou, Yitian Zhao, Wei Chen, Wei Chen, Wei Chen

“…The experimental results show that the proposed method has the best performance compared to the most advanced segmentation networks currently available. …”
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Small Target Detection Algorithm for UAV Aerial Images Based on Improved YOLOv7-tiny by ZHANG Guanghua, LI Congfa, LI Gangying, LU Weidang

“…Results indicate that introducing the efficient decoupled head leads to the most significant accuracy improvement, increasing mAP by 1.1%. …”
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YOLO-WTB: Improved YOLOv12n Model for Detecting Small Damage of Wind Turbine Blades From Aerial Imagery by Phat T. Nguyen, Duy C. Huynh, Loc D. Ho, Matthew W. Dunnigan

“…In addition, in the backbone part, we also propose to remove a Convolution module and an Area Attention Concatenate-Convolution-Fusion module and add an improved SoftPool Feature Spatial Pyramid Pooling - Fast module to increase the feature extraction ability while maintaining the complexity of the model. …”
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Oxide Phototransistor Array With Multiply-and-Accumulation Functions for In-Sensor Image Processing by Saisai Wang, Xiaotao Jing, Wanlin Zhang, Rui Wang, Hong Wang, Qi Huang

“…Advanced in-sensor computing paradigm has gradually become a research hotspot in this IOT era of sensor data proliferation. However, most existing in-sensor computing devices are plagued by a complex structure, and the uniformity of the sensor array is difficult to ensure. …”
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Partial feature reparameterization and shallow-level interaction for remote sensing object detection by Minh Tai Pham Nguyen, Quoc Duy Nam Nguyen, Hoang Viet Anh Le, Minh Khue Phan Tran, Tadashi Nakano, Thi Hong Tran

“…As a result, our proposed detector obtains a competitive performance that outperforms most of the other large-size models and SOTA works. …”
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Efficient Single-Exposure Holographic Imaging via a Lightweight Distilled Strategy by Jiaosheng Li, Haoran Liu, Zeyu Lai, Yifei Chen, Chun Shan, Shuting Zhang, Youyou Liu, Tude Huang, Qilin Ma, Qinnan Zhang

“…The integration of deep learning (DL) advancements with physics-informed methodologies has opened new avenues for tackling this challenge. However, most of the existing DL-based holographic reconstruction methods have high model complexity. …”
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Analysis of Time-Fractional Delay Partial Differential Equations Using a Local Radial Basis Function Method by Kamran, Kalsoom Athar, Zareen A. Khan, Salma Haque, Nabil Mlaiki

“…The Laplace transform, which is one of the most powerful techniques for solving integer- and non-integer-order problems, is used to represent the desired solution as a contour integral in the complex plane, known as the Bromwich integral. …”
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Kidney Stone Detection based on Improved YOLOv7 with Attention Module and Super Resolution Techniques Under Limited Training Samples by Minh Tai Pham Nguyen, Viet Tuan Le, Huu Thanh Duong, Vinh Truong Hoang

“…Moreover, X-ray imaging, which is the current most popular medical imaging technique, is struggling with false positives, which is caused by low quality, making the diagnosis more challenging. …”
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Multi-Feature Fusion for Enhanced Feature Representation in Automatic Modulation Recognition by Jiuxiao Cao, Rui Zhu, Lingfeng Wu, Jun Wang, Guohao Shi, Peng Chu, Kang Zhao

“…With the advancement of deep learning, automatic modulation recognition has emerged as a promising solution. Nonetheless, most existing deep learning-based modulation recognition studies consider only single-domain feature information of the signal, such as time-domain or frequency-domain features. …”
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Deep learning-enabled exploration of global spectral features for photosynthetic capacity estimation by Xianzhi Deng, Xiaolong Hu, Liangsheng Shi, Chenye Su, Jinmin Li, Shuai Du, Shenji Li

“…The photosynthesis-sensitive spectral bands identified by our model were predominantly in the visible range. The most sensitive vegetation indices form discovered by our model was Reflectancenear−infrared+Reflectancegreen/blueReflectancenear−infrared×Reflectancered. …”
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Influence of Apis mellifera in-hive conditions on germination capacity of rapeseed pollen (Brassica napus) by Luciano Alberto Marinozzi, Soledad Camila Villamil, Liliana María Gallez

“… • Fresh pollen had the thickest and most developed pollen tubes. After 24 h in the hive, pollen grains had thinner, shorter, and convoluted pollen tubes. …”
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An extended TOPSIS technique based on correlation coefficient for interval-valued q-rung orthopair fuzzy hypersoft set in multi-attribute group decision-making by Rana Muhammad Zulqarnain, Imran Siddique, Sameh Askar, Ahmad M. Alshamrani, Dragan Pamucar, Vladimir Simic

“…This study determines incineration as the most beneficial method for BMW disposal, demonstrating its more efficient use of alternative disposal techniques. …”
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MFFSNet: A Lightweight Multi-Scale Shuffle CNN Network for Wheat Disease Identification in Complex Contexts by Mingjin Xie, Jiening Wu, Jie Sun, Lei Xiao, Zhenqi Liu, Rui Yuan, Shukai Duan, Lidan Wang

“…Wheat is one of the most essential food crops globally, but diseases significantly threaten its yield and quality, resulting in considerable economic losses. …”
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Testing a New Star Formation History Model from Principal Component Analysis to Facilitate Spectral Synthesis Modeling by Yanzhe Zhang, H. J. Mo, Katherine E. Whitaker, Shuang Zhou

“…The spectrum of a galaxy is a complicated convolution of many properties of the galaxy, such as the star formation history (SFH), initial mass function, and metallicity. …”
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