Crack-ConvT Net: A Convolutional Transformer Network for Crack Segmentation in Underwater Dams by Pengfei Shi, Hongzhu Chen, Zaiming Geng, Xinnan Fan, Yuanxue Xin

“…To address these issues, this paper proposes Crack-ConvT Net, a U-Shape architecture that integrates Convolutional Neural Networks (CNNs) and Transformers for underwater dam crack segmentation. …”
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Information systems validation using formal models by Azadeh Sarram, Ali Harounabadi

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Evaluating Mixing Methods: Anonymity, Long-Term Information Leakage, and Cost by Alperen Aksoy, Dogan Kesdogan

“…When deploying systems, two well-known mixing methods, batch (e.g., Timed Mix) and continuous mixing (e.g., Stop-and-Go Mix), are commonly used in real-world Mix-nets. However, no comprehensive study has evaluated the impact of these methods on anonymity, long-term information leakage, and the cost associated with dummy message overhead. …”
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Diagnosis of Open and Short Circuit Intermittent Connection Faults for DeviceNet Based on Multilayer Information Fusion and Circuit Network Analysis by Longkai Wang, Yong Lei

“…This paper proposes a novel mixed IC fault diagnosis method for DeviceNet based on multilayer information fusion and circuit network analysis to identify the types and locations of IOC and ISC faults. …”
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Canopy height mapping in French Guiana using multi-source satellite data and environmental information in a U-Net architecture by Kamel Lahssini, Nicolas Baghdadi, Guerric le Maire, Guerric le Maire, Ibrahim Fayad, Ibrahim Fayad, Ludovic Villard

“…In this study, we present a deep learning application to map canopy height in French Guiana using freely available multi-source satellite data (optical and radar) and complementary environmental information. The potential of a U-Net architecture trained on sparse and unevenly distributed GEDI data to generate a continuous canopy height map at a regional scale was assessed. …”
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LGM-Net: Wheat Pest and Disease Detection Network Based on Local Global Information Interaction and Multi-Level Feature Fusion by Yimin Qu, Shaobo Yu, Jing Yang

“…Firstly, this paper designs a lightweight feature interactive network (LFI-Net) to fully extract the local and global features of wheat leaf diseases and improve the detection of wheat pest and disease targets under noise interference. …”
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High-Accuracy Recognition Method for Diseased Chicken Feces Based on Image and Text Information Fusion by Duanli Yang, Zishang Tian, Jianzhong Xi, Hui Chen, Erdong Sun, Lianzeng Wang

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PermQRDroid: Android malware detection with novel attention layered mini-ResNet architecture over effective permission information image by Kazım Kılıç, İbrahim Alper Doğru, Sinan Toklu

“…Methods In this study, an attention-layered mini-ResNet model is proposed, which can detect QR code-like images created using the 100 most effective defined permission information of Android applications. …”
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Research on a Rapid Three-Dimensional Compressor Flow Field Prediction Method Integrating U-Net and Physics-Informed Neural Networks by Chen Wang, Hongbing Ma

“…This model is based on structured CFD training data and physics-informed loss functions and is proposed for direct 3D compressor flow prediction. …”
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U-SeqNet: learning spatiotemporal mapping relationships for multimodal multitemporal cloud removal by Qian Zhang, Xiangnan Liu, Tao Peng, Xiao Yang, Mengzhen Tang, Xinyu Zou, Meiling Liu, Ling Wu, Tingwei Zhang

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New Function for Safety Signal Monitoring in MID‐NET®: The Case of an Anti‐COVID‐19 Drug by Yusuke Okada, Takashi Ando, Fumitaka Takahashi, Kenichi Watanabe, Kazuhiro Kajiyama, Tomoaki Hasegawa, Satomi Inomata, Yuki Kinoshita, Shinya Watanabe, Yoshiaki Uyama

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High-resolution reanalysis biological ocean data from the Copernicus Marine Service Information for Philippine marine research by Brenna Mei M. Concolis

“…Copernicus Marine Service Information provides reanalysis data of global biomass content that can be freely access by public users. …”
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Discussion on the formation and development of agricultural information science by WANG Ren-chao, HUANG Jing-feng, SHI Zhou, WANG Ke

Subjects: “…agricultural information science…”
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USE OF NEURAL NETWORKS FOR DETECTION AND RECOGNITION OF THE ANOMALIES IN ENTERPRISE CORPORATIVE INFORMATION SYSTEM by U. A. Vishniakou, O. S. Koval, M. G. Mozdurani Shiraz

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Bird Species Detection Net: Bird Species Detection Based on the Extraction of Local Details and Global Information Using a Dual-Feature Mixer by Chaoyang Li, Zhipeng He, Kai Lu, Chaoyang Fang

“…To address this limitation, we propose BSD-Net, a bird species detection network. BSD-Net efficiently learns local and global information in pixels to accurately detect bird species. …”
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AlexNet Convolutional Neural Network Architecture with Cosine and Hamming Similarity/Distance Measures for Fingerprint Biometric Matching by Ahmed Sabah Ahmed AL-Jumaili, Huda Kadhim Tayyeh, Abeer Alsadoon

“… In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. …”
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SFEF-Net: Scattering Feature Extraction and Fusion Network for Aircraft Detection in SAR Images by Qiang Zhou, Zongxu Pan, Ben Niu

“…Compared to traditional convolution, sparse convolution offers more flexible sampling positions and a larger receptive field without increasing the number of parameters, which enables SFEF-Net to better extract discrete features. Secondly, we developed the global information fusion and distribution module (GIFD) to fuse feature maps of different levels and scales. …”
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HierLabelNet: A Two-Stage LLMs Framework with Data Augmentation and Label Selection for Geographic Text Classification by Zugang Chen, Le Zhao

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ConvNeXt embedded U-Net for semantic segmentation in urban scenes of multi-scale targets by Yanyan Wu, Qian Li

“…Our improved algorithm, ConvNeXt embedding in the U-Net algorithm architecture, is named Conv-UNet. …”
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MFGC-Net: Bridging and Fusing Multiscale Features and Global Contexts for Multitask Sea Ice Fine Segmentation by Tianen Ma, Xinwei Chen, Linlin Xu, Pengfei Ma, Peilin Yu

“…Our experiments on the AI4Arctic Sea Ice Challenge Dataset show that MFGC-Net achieves outstanding performance in multitask sea ice segmentation compared with current state-of-the-art methods, as demonstrated by both quantitative and qualitative results.…”
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