Application of Hybrid Transform Domain Digital Watermarking in Power System Information Security by Shaomin Zhu, Zhiqiang Zhang

“…According to energy distribution and visual masking in low frequency subband, the singular values of the selected low frequency subband blocks were adaptively applied quantization index modulation for embedding watermark information. …”
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A hybrid recommendation system for Chinese character components using a dual-tower neural network and a deterministic algorithm by Shaoqing Yang

“…The framework synergizes deterministic rule validation (98.2% radical compatibility accuracy) and a dual-tower neural network (768d BERT embeddings with dynamic negative sampling), supported by a meticulously curated 141-radical/803-character database encoding 12,345 valid combinations.Controlled experiments (N = 127 learners) demonstrate three key advancements: (1) 80.4% recommendation F1 score (95%CI:78.9–81.7%), outperforming rule-based baselines by 29.5% (p < 0.001); (2) 30.7% sustained engagement increase measured through playtrace analysis (χ²=25.33); (3) 78ms mobile inference latency achieved via ONNX quantization (model size 202KB). …”
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MuRelSGG: Multimodal Relationship Prediction for Neurosymbolic Scene Graph Generation by Muhammad Junaid Khan, Adil Masood Siddiqui, Hamid Saeed Khan, Faisal Akram, M. Jaleed Khan

“…Neurosymbolic Scene Graph Generation (SGG) is a promising approach that jointly leverages the perception capabilities of deep neural networks and the reasoning capabilities of symbolic techniques for scene understanding and visual reasoning. …”
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Traditional guidance mechanism based deep robust watermarking by Xuejing GUO, Yixiang FANG, Yi ZHAO, Tianzhu ZHANG, Wenchao ZENG, Junxiang WANG

“…With the development of network and multimedia technology, multimedia data has gradually become a key source of information for people, making digital media the primary battlefield for copyright protection and anti-counterfeit traceability.Digital watermarking techniques have been widely studied and recognized as important tools for copyright protection.However, the robustness of conventional digital watermarking methods is limited as sensitive digital media can easily be affected by noise and external interference during transmission.Then the existing powerful digital watermarking technology’s comprehensive resistance to all forms of attacks must be enhanced.Moreover, the conventional robust digital watermarking algorithm’s generalizability across a variety of image types is limited due to its embedding method.Deep learning has been widely used in the development of robust digital watermarking systems due to its self-learning abilities.However, current initialization techniques based on deep neural networks rely on random parameters and features, resulting in low-quality model generation, lengthy training times, and potential convergence issues.To address these challenges, a deep robust digital watermarking algorithm based on a traditional bootstrapping mechanism was proposed.It combined the benefits of both traditional digital watermarking techniques and deep neural networks, taking into account their learning abilities and robust characteristics.The algorithm used the classic robust digital watermarking algorithm to make watermarked photos, and the constructed feature guaranteed the resilience of traditional watermarked images.The final dense image was produced by fusing the conventionally watermarked image with the deep network using the U-Net structure.The testing results demonstrate that the technique can increase the stego image’s resistance to various attacks and provide superior visual quality compared to the conventional algorithm.…”
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Detection and Severity Assessment of Parkinson’s Disease Through Analyzing Wearable Sensor Data Using Gramian Angular Fields and Deep Convolutional Neural Networks by Sayyed Mostafa Mostafavi, Shovito Barua Soumma, Daniel Peterson, Shyamal H. Mehta, Hassan Ghasemzadeh

“…In the present study, we developed a method for the diagnosis and severity assessment of PD using Gramian Angular Fields (GAFs) in combination with deep Convolutional Neural Networks (CNNs). Our model was applied to PD gait signals captured using pressure sensors embedded into insoles. …”
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Integrating Social Network and Space Syntax: A Multi-Scale Diagnostic–Optimization Framework for Public Space Optimization in Nomadic Heritage Villages of Xinjiang by Hao Liu, Rouziahong Paerhati, Nurimaimaiti Tuluxun, Saierjiang Halike, Cong Wang, Huandi Yan

“…Dispersed villages maintain moderate network density but face challenges in visual integration and centrality, demanding targeted activation of key intersections to improve regional cohesion. …”
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SEMSF-Net: Explainable Squeeze&#x2013;Excitation Multiscale Fusion Network for Aerial Scene and Coastal Area Recognition Using Remote Sensing Images by Muhammad John Abbas, Muhammad Attique Khan, Ameer Hamza, Shrooq Alsenan, Areej Alasiry, Mehrez Marzougui, Yang Li, Yunyoung Nam

“…This article proposed a novel squeeze&#x2013;excitation multiscale fusion network (SEMSF-Net) to classify LULC and the coastal regions using RS images. …”
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Implementation of CNN Algorithm for Indonesian Hoax News Detection on Online News Portals by Clifansi Remi Siwi Hati, Heni Sulistiani

“…The purpose of this research is to apply deep learning with the Convolutional Neural Network (CNN) algorithm in detecting text-based hoax news in Indonesian. …”
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Text-Guided Refinement for Referring Image Segmentation by Shuang Qiu, Shiyin Zhang, Tao Ruan

“…(c) It facilitates effective multi-modal information integration through a language-embedded visual encoder. Extensive experiments on three benchmark datasets validate the effectiveness of the proposed approach, demonstrating its superior performance in referring segmentation.…”
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A deep learning model combining circulating tumor cells and radiological features in the multi-classification of mediastinal lesions in comparison with thoracic surgeons: a large-s... by Feng Wang, Minwei Bao, Bo Tao, Fugui Yang, Guangxue Wang, Lei Zhu

“…The diagnostic performances of DMFN and monomodal CNN models were based on the Paraffin-embedded pathologies from surgical tissues. The predictive abilities were compared with thoracic resident physicians, attending physicians, and chief physicians by the area under the receiver operating characteristic (ROC) curve, and diagnostic results were visualized in the heatmap. …”
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CAD-ViT: Coordinate Attention-Enhanced Vision Transformer With Dilated Feature Fusion for Diabetic Retinopathy Staging by Ye Wang, Xiaofang Gou, Wenman Li

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Hypergraph-Driven High-Order Knowledge Tracing with a Dual-Gated Dynamic Mechanism by Fanglan Ma, Changsheng Zhu, Peng Lei

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Illumination-adaptative granularity progressive multimodal image fusion method by Chuanyun WANG, Dongdong SUN, Mingqi ZHOU, Tian WANG, Qian GAO, Zhaokui LI

“…The processed scene vectors are then progressively embedded into the fusion image reconstruction network, providing the fusion model with the ability to perceive scene information. …”
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A thematic-cognitive perspective for exploring the writing skills of children: a textual analysis using ENA by Jianheng Zhang, Tiong-Thye Goh, Dexin Chen, Yuan Gong, Bing Yang, Liqin Pan, Ting Song, Shiqi Yu, Hanzhen Li

“…Cognitive network maps were constructed to examine developmental trends and differences across grades and genders from both subject-matter and cognitive perspectives.ResultsThe analysis demonstrates ENA’s effectiveness in visualizing the cognitive features embedded in written texts. …”
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Group-based siamese self-supervised learning by Zhongnian Li, Jiayu Wang, Qingcong Geng, Xinzheng Xu

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Exploiting facial side similarities to improve AI-driven sea turtle photo-identification systems by Lukáš Adam, Kostas Papafitsoros, Claire Jean, ALan F. Rees, Vojtěch Čermák

“…We do so by employing two state-of-the-art automated neural network-based photo-ID methods, one local feature-based and one deep embedding-based, designed to rank profiles based on their similarities. …”
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Benchmarking Accelerometer and CNN-Based Vision Systems for Sleep Posture Classification in Healthcare Applications by Minh Long Hoang, Guido Matrella, Dalila Giannetto, Paolo Craparo, Paolo Ciampolini

“…For the image-based method, the Visual Geometry Group 16 (VGG16) convolutional neural network was fine-tuned with data augmentation strategies including rotation, reflection, scaling, and translation to enhance model generalization. …”
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Efficient Implementation of DVI Protocol on FPGA by Sara Ershadi-Nasab, Danial Bayati, Saeed Yazdani

“…This paper presents a general-purpose hardware implementation of the digital visual interface (DVI) protocol on the Xilinx Virtex-6 ML605 FPGA platform for real-time display of digital processing results. …”
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Estimation of Fractal Dimensions and Classification of Plant Disease with Complex Backgrounds by Muhammad Hamza Tariq, Haseeb Sultan, Rehan Akram, Seung Gu Kim, Jung Soo Kim, Muhammad Usman, Hafiz Ali Hamza Gondal, Juwon Seo, Yong Ho Lee, Kang Ryoung Park

“…To address these issues, this study proposes a computationally effective residual convolutional attention network (RCA-Net) for the disease classification of plants in field images with complex backgrounds. …”
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FilletCam AI: A handheld tool for precise fillet color profiling of Atlantic salmon and rainbow trout by Rakesh Ranjan, Harsh Shroff, Kata Sharrer, Scott Tsukuda, Christopher Good

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