ML-Driven Energy Savings for Cellular Baseband Units via Traffic Prediction by Aneta Kolackova, Viet Anh Phan, Jan Jerabek, Sergey Andreev, Jiri Hosek

“…The design features a hybrid architecture of Hyper Convolutional Neural Network-Long Short-Term Memory (Hyper-CNN-LSTM) model for accurate forecasting with a reinforcement learning (RL) decision engine based on Dueling Double Deep Q-Networks (DDDQN), making it the first framework to apply DDDQN for BBU energy optimization in 5G and beyond networks. …”
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Diagnosis of Power Transformer On-Load Tap Changer Mechanical Faults Based on SABO-Optimized TVFEMD and TCN-GRU Hybrid Network by Shan Wang, Zhihu Hong, Qingyun Min, Dexu Zou, Yanlin Zhao, Runze Qi, Tong Zhao

“…This paper develops a hybrid framework combining metaheuristic-optimized decomposition with hierarchical temporal learning. …”
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BiDGCNLLM: A Graph–Language Model for Drone State Forecasting and Separation in Urban Air Mobility Using Digital Twin-Augmented Remote ID Data by Zhang Wen, Junjie Zhao, An Zhang, Wenhao Bi, Boyu Kuang, Yu Su, Ruixin Wang

“…Using Remote ID data, we propose BiDGCNLLM, a hybrid prediction framework that integrates a Bidirectional Graph Convolutional Network (BiGCN) with Dynamic Edge Weighting and a reprogrammed Large Language Model (LLM, Qwen2.5–0.5B) to capture spatial dependencies and temporal patterns in drone speed trajectories. …”
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Dual-hybrid intrusion detection system to detect False Data Injection in smart grids. by Saad Hammood Mohammed, Mandeep S Jit Singh, Abdulmajeed Al-Jumaily, Mohammad Tariqul Islam, Md Shabiul Islam, Abdulmajeed M Alenezi, Mohamed S Soliman

“…Experimental results demonstrate that the proposed IDS framework significantly outperforms traditional methods. …”
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Deep learning-based InSAR time-series deformation prediction in coal mine areas by Chuanzeng Shu, Zhiguo Meng, Ying Yang, Yongzhi Wang, Shanjun Liu, Xiaoping Zhang, Yuanzhi Zhang

“…This framework integrates a Transformer-encoder module, a Bi-LSTM-decoder module, and an innovative convolutional attention feature extraction module. …”
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RPFusionNet: An Efficient Semantic Segmentation Method for Large-Scale Remote Sensing Images via Parallel Region–Patch Fusion by Shiyan Pang, Weimin Zeng, Yepeng Shi, Zhiqi Zuo, Kejiang Xiao, Yujun Wu

“…RPFusionNet leverages two distinct feature representations: REGION (representing large areas) and PATCH (representing smaller regions). This framework comprises two parallel branches: the REGION branch initially downsamples the entire image, then extracts features via a convolutional neural network (CNN)-based encoder, and subsequently captures multi-level information using pooled kernels of varying sizes. …”
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CoastVisionNet: transformer with integrated spatial-channel attention for coastal land cover classification by Li Yang, Liu Yijun, Wenhao Deng

“…This work aligns strongly with emerging priorities in intelligent remote sensing, offering a scalable, interpretable, and physically grounded framework for next-generation coastal monitoring.…”
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MRDDA: a multi-relational graph neural network for drug–disease association prediction by Congzhou Chen, Yaozheng Zhou, Yinghong Li, Jin Xu, Demin Li, Lingfeng Wang

“…First, we design a hybrid graph convolutional framework to capture both local and global representations of drugs and diseases. …”
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Generation driven understanding of localized 3D scenes with 3D diffusion model by Hao Sun, Junping Qin, Zheng Liu, Xinglong Jia, Kai Yan, Lei Wang, Zhiqiang Liu, Shaofei Gong

“…In addition to accurately predicting the distribution of the noise tensor, the framework significantly enhances the understanding of localized scenes by effectively integrating spatial context information. …”
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AttenCRF-U: Joint Detection of Sleep-Disordered Breathing and Leg Movements in OSA Patients by Qiuyue Li, Kewei Li, Cong Fu, Yiyuan Zhang, Huan Yu, Chen Chen, Wei Chen

“…To address this, we propose Attention-enhanced CRF with U-Net (AttenCRF-U), a novel joint detection framework that integrates multi-head self-attention (MHSA) within an encoder–decoder architecture to model long-range dependencies between overlapping events and employs multi-scale convolutional encoding to extract discriminative features across different temporal scales. …”
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Intelligent Design Method for Thermal Conductivity Topology Based on a Deep Generative Network by Qiyin Lin, Feiyu Gu, Chen Wang, Hao Guan, Tao Wang, Kaiyi Zhou, Lian Liu, Desheng Yao

“…In this study, we propose an innovative intelligent design framework integrating Conditional Deep Convolutional Generative Adversarial Networks (CDCGAN) with SIMP, capable of creating topology structures that meet prescribed thermal conduction performance. …”
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Two-dimensional spatial orientation relation recognition between image objects by Gong Peiyong, Zheng Kai, Jiang Yi, Zhao Huixuan, Huai Honghao, Guan Ruijie

“…These results validate TSOVF’s capacity to advance fine-grained visual relationship detection while providing a reproducible framework for future research in spatial-semantic analysis.…”
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GDText-VM: an arbitrary-shaped scene text detector based on globally deformable VMamba by Yingnan Zhao, Zheng Hu, Fangqi Ding, Jielin Jiang, Xiaolong Xu

“…Contemporary text detectors based on Convolutional Neural Networks face challenges in effectively modeling long-range dependencies. …”
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Advanced Deep Learning Approaches for Forecasting High-Resolution Fire Weather Index (FWI) over CONUS: Integration of GNN-LSTM, GNN-TCNN, and GNN-DeepAR by Shihab Ahmad Shahriar, Yunsoo Choi, Rashik Islam

“…Based on this, our study developed a hybrid modeling framework to forecast FWI over a 14-day horizon, integrating Graph Neural Networks (GNNs) with Temporal Convolutional Neural Networks (TCNNs), Long Short-Term Memory (LSTM), and Deep Autoregressive Networks (DeepAR). …”
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A Hybrid CNN-LSTM Model With Attention Mechanism for Improved Intrusion Detection in Wireless IoT Sensor Networks by Pendukeni Phalaagae, Adamu Murtala Zungeru, Abid Yahya, Boyce Sigweni, Selvaraj Rajalakshmi

“…This work introduces an Intrusion Detection System (IDS) framework that integrates Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks in a hybrid architecture, enhanced by an attention mechanism to improve feature extraction and classification accuracy. …”
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Intelligent integration of AI and IoT for advancing ecological health, medical services, and community prosperity by Abdulrahman Alzahrani, Patty Kostkova, Hamoud Alshammari, Safa Habibullah, Ahmed Alzahrani

“…The features of the proposed framework not only provide solutions to the existing inefficiencies but also enhance scalability, cost-effectiveness, and global environmental standardization. …”
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Real-Time Polyp Detection From Endoscopic Images Using YOLOv8 With YOLO-Score Metrics for Enhanced Suitability Assessment by Zahid Farooq Khan, Muhammad Ramzan, Mudassar Raza, Muhammad Attique Khan, Areej Alasiry, Mehrez Marzougui, Jungpil Shin

“…The proposed detector uses multiple convolutional, C2f (Faster Cross Stage Partial Bottleneck with 2 convolutions), and SPPF (Spatial Pyramid Pooling-Fast) blocks. …”
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Depression detection based on dual path DCGAN data generation and classification-regression network by LU Jingxue, LI Hongyan, ZHENG Ruichao, QIN Ruizhen

“…It proves that the multi-scale convolutional idea can extract more abundant global information and broader context information. …”
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Intelligent Interior Design Systems: Optimizing Layouts and Aesthetics Using AI and User Data by Zhe Ji, Yan Yu

“…To address these challenges, we mathematically formulated the layout generation problem as a constrained multi-objective optimization task, balancing aesthetics, functionality, and user preferences. Our computational framework leverages convolutional neural networks (CNNs) for layout parsing, graph neural networks (GNNs) for modeling spatial relationships, and Transformer-based architectures for context-aware reasoning. …”
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LPBERT: A Protein–Protein Interaction Prediction Method Based on a Pre-Trained Language Model by An Hu, Linai Kuang, Dinghai Yang

“…Inspired by the protein language model ProteinBERT, this study designed the LPBERT deep learning framework, which is a novel end-to-end deep learning architecture. …”
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