Cross-Modal Object Detection Based on Content-Guided Feature Fusion and Self-Calibration by Liyang Ning, Xuxun Liu, Luoyu Zhou, Xueyu Zou

“…Additionally, deep features are prone to degradation through multiple convolutional layers, leading to the loss of detailed information. To address these issues, we propose a dual-backbone cross-modal object detection model based on YOLOv8n. …”
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ESL-YOLO: Small Object Detection with Effective Feature Enhancement and Spatial-Context-Guided Fusion Network for Remote Sensing by Xiangyue Zheng, Yijuan Qiu, Gang Zhang, Tao Lei, Ping Jiang

“…This model includes: (1) an innovative plug-and-play feature enhancement module that incorporates multi-scale local contextual information to bolster detection performance for small objects; (2) a spatial-context-guided multi-scale feature fusion framework that enables effective integration of shallow features, thereby minimizing spatial information loss; and (3) a local attention pyramid module aimed at mitigating background noise while highlighting small object characteristics. …”
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TF-CMFA: Robust Multimodal 3D Object Detection for Dynamic Environments Using Temporal Fusion and Cross-Modal Alignment by Yujing Wang, Abdul Hadi Abd Rahman, Fadilla 'Atyka Nor Rashid

“…However, most existing research seldom addresses the issues of robustness and performance degradation in dynamic environments due to the difficulty of aligning modal features. …”
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DAM-Faster RCNN: few-shot defect detection method for wood based on dual attention mechanism by Xingyu Tong, Zhihong Liang, Mingming Qin, Fangrong Liu, Jiayu Yang, Hengjiang Xiao, Wei Dai

“…To address the above issues, this paper proposes an improved Faster RCNN model based on a dual attention mechanism (DAM). …”
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Dynamic Collaborative Optimization Method for Real-Time Multi-Object Tracking by Ziqi Li, Dongyao Jia, Zihao He, Nengkai Wu

“…Firstly, a multi-scale feature adaptive enhancement (MS-FAE) module is designed, integrating multi-level features and introducing a small object adaptive attention mechanism to enhance the representation ability for small objects. …”
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CHAM-CLAS: A Certificateless Aggregate Signature Scheme with Chameleon Hashing-Based Identity Authentication for VANETs by Ahmad Kabil, Heba Aslan, Marianne A. Azer, Mohamed Rasslan

“…Our proposed CLAS scheme remedies these issues by incorporating an identity authentication module that leverages chameleon hashing within elliptic curve cryptography (CHAM-CLAS). …”
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Deep learning-based text generation for plant phenotyping and precision agriculture by Li Zhu, Long Tang, Shan Ren, Shan Ren

“…An environment-aware module is included to address environmental variability.ResultsThe generative model uses advanced deep learning techniques to process high-dimensional imaging data, effectively capturing complex plant traits while overcoming issues like occlusion and variability. …”
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ED-Swin Transformer: A Cassava Disease Classification Model Integrated with UAV Images by Jing Zhang, Hao Zhou, Kunyu Liu, Yuguang Xu

“…Secondly, the DASPP (Deformable Atrous Spatial Pyramid Pooling) module was designed to use deformable atrous convolution to adaptively match the irregular boundaries of diseased areas, enhancing the model’s robustness to morphological variations caused by angles and occlusions in low-altitude drone photography. …”
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HiEndo: harnessing large-scale data for generating high-resolution laparoscopy videos under a two-stage framework by Zhao Wang, Yeqian Zhang, Jiayi Gu, Yueyao Chen, Yonghao Long, Xiang Xia, Puhua Zhang, Chunchao Zhu, Zerui Wang, Qi Dou, Zheng Wang, Zizhen Zhang

“…In the second stage, we further design a super resolution module to improve the resolution of initial video and refine the fine-grained details. …”
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PHRF-RTDETR: a lightweight weed detection method for upland rice based on RT-DETR by Xianjin Jin, Jinheng Zhang, Fei Wang, Mengyan Zhao, Yunshuang Wang, Jianping Yang, Jinfeng Wu, Bing Zhou

“…Second, we integrate HiLo, a mechanism excluding parameter growth, into the AIFI module to enhance the model’s capability of capturing multi-frequency features. …”
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Development of an Intelligent Method for Target Tracking in Radar Systems at the Initial Stage of Operation Under Intentional Jamming Conditions by Serhii Semenov, Olga Wasiuta, Alla Jammine, Justyna Golec, Magdalena Krupska-Klimczak, Yevhen Tarasenko, Vitalii Voronets, Vitalii Breslavets, Serhii Lvov, Artem Moskalenko

“…In conditions of signal loss, noise, and unstable measurement reliability, traditional methods do not provide stable and accurate tracking, especially at the initial stages of radar operation. To address this issue, an intelligent method is proposed that integrates a probabilistic graphical evaluation and review technique (GERT) model, a recursive Kalman filter, and a measurement reliability prediction module based on a long short-term memory (LSTM) neural network. …”
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Assessment of binary prediction of fraudulent advertisements in ATS candidate tracking cloud systems by V. V. Ligi-Goryaev, G. A. Mankaeva, T. B. Goldvarg, S. S. Muchkaeva, V. V. Dzhakhnaev

“…Various machine learning algorithms can be employed to address this issue. Traditional classification algorithms, including LSVC (Support Vector Machine), GBT (Gradient Boosting Tree), and RF (Random Forest), have been chosen for this study. …”
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MT-Former: Multi-Task Hybrid Transformer and Deep Support Vector Data Description to Detect Novel anomalies during Semiconductor Manufacturing by Hyunsu Jeong, Chiho Yoon, Hyunseok Lim, Jaesuk Chang, Sampa Misra, Chulhong Kim

“…Therefore, classifying existing defects and new defects provides crucial clues to fix the issue in the newly introduced manufacturing process. …”
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Features of the Development of an Engineer’s Thinking in the Course of Training at a University (Using the Example of Studying the Discipline “Engineering Graphics”) by V. I. Vaulin, S. A. Singeev, N. I. Filonchik, S. V. Vaulin

“…The research used theoretical methods of analysis, synthesis of module structure, synthesis and generalizations, knowledge control, practical methods of performing graphic tasks, methods of mathematical statistics for evaluating educational achievements, analysis of literary sources and educational literature, experiment. …”
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Probing marine macroalgal phlorotannins as an antibacterial candidate against Salmonella typhi: Molecular docking and dynamics simulation approach by Arun Kumar Malaisamy, Balamuralikrishnan Balasubramanian, Pon Yazhine Tamilselvan, Venkatesh Sakthivel, Santhi Venkatachalapathi, Haripriya Kuchi Bhotla

“…Additionally, pharmacokinetic studies using the QikProp module demonstrated that the top-ranked compounds showed favourable drug-like properties with good druggable efficiency, moderate gut-blood barrier transport, and high human oral absorption. …”
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POTA: A Pipelined Oblivious Transfer Acceleration Architecture for Secure Multi-Party Computation by Li Xiaolin, Yan Wei, Liu Hongwei, Zhang Yong, Hao Qinfen, Liu Yong, Sun Ninghui

“…Furthermore, we design a modular multiplication module over a finite field to generate the more complex correlations required by MPC protocols. …”
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Flow Regulation Characteristics of Active Flow-Regulating Vanes in U-Shaped Bends by LI Lin, ZHANG Jing-kai, ZHANG Lu-guo, CHI Miao-miao, XIAO Yu-lei

“…[Objective] To address the issue that conventional river regulation structures struggle to dynamically adapt to the highly variable characteristics of natural rivers, this study develops an innovative active flow-regulating vane system. …”
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CC-Former: Urban Flood Mapping from InSAR Coherence with Vision Transformer: Libya and Storm Daniel as Test Case by T. Saleh, T. Saleh, T. Saleh, S. Holail, M. Al-Saad, F. Xu, M. Zahran, G.-S. Xia, G.-S. Xia

“…Urban flooding is a recurring and distressing issue with severe consequences, including the destruction of densely populated infrastructure and loss of life. …”
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Investigating COVID‐19‐Induced Adjustment Disorder Among Iranian Patients With Multiple Sclerosis in Pandemic Time by Elahe Samami, Seyed Mohammad Baghbanian, Seyedeh Zeynab Hossein Nezhad, Zohreh Shahhosseini, Mahmood Moosazadeh, Forouzan Elyasi

“…Given the utmost importance of this issue for vulnerable groups, the present study was to investigate COVID‐19‐induced AD among Iranian patients living with multiple sclerosis (MS) in 2020. …”
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A SAM-adapted weakly-supervised semantic segmentation method constrained by uncertainty and transformation consistency by Yinxia Cao, Xin Huang, Qihao Weng

“…Existing weakly-supervised methods often leverage low-level visual or high-level semantic features from networks to generate supervision information for unlabeled pixels, which can easily lead to the issue of label noises. Furthermore, these methods rarely explore the general-purpose foundation model, segment anything model (SAM), with strong zero-shot generalization capacity in image segmentation. …”
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