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Understanding tourist engagement with traditional dwellings through multimodal deep learning: a case study of the Gao Family Compound, Xi’an

Liyue Wu, Qinchuan Zhan, Yanjun Li • Humanities & Social Sciences Communications (2026)

Abstract This study applies a multimodal deep learning approach to examine tourist engagement with traditional architectural heritage. The Gao Family Compound in Xi’an serves as a representative case. Social-media texts and images from Weib...

DOAJ Open Access (DOAJ) DOI: 10.1057/s41599-026-07879-5

High-fidelity single-frame computational super-resolution using signal-preserving denoising-enabled deconvolution

Fudong Xue, Lin Yuan, Wenting He, Zuo’ang Xiang et al. • Nature Communications (2026)

Abstract Computational super-resolution (SR) methods enable nanoscale imaging from single-frame wide-field or spinning-disk confocal images without hardware modifications, yet face limitations: statistical restoration suffers from noise and...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41467-026-70791-8

DeepPROTACs is a deep learning-based targeted degradation predictor for PROTACs

Fenglei Li, Qiaoyu Hu, Xianglei Zhang, Renhong Sun et al. • Nature Communications (2022)

The rational design of PROTACs is difficult due to their obscure structure-activity relationship. Here the authors present a deep neural network model - DeepPROTACs - for predicting the degradation capacity of a proposed PROTAC molecule....

DOAJ Open Access (DOAJ) DOI: 10.1038/s41467-022-34807-3

An Efficient Distributed Reinforcement Learning Architecture for Long-Haul Communication Between Actors and Learner

Shin Morishima, Hiroki Matsutani • IEEE Access (2024)

A computing cluster that interconnects multiple compute nodes is used to accelerate distributed reinforcement learning that uses DQN (Deep Q-Network). In distributed reinforcement learning, actor nodes acquire experiences by interacting wit...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3402835

Distributed biconnectivity-preserving flocking with fast obstacle avoidance for UAV swarms

Jiaxin Li, Tong Duan, Peng Yi, Zhen Zhang et al. • Complex & Intelligent Systems (2026)

Abstract Obstacles in low-altitude environments force unmanned aerial vehicle (UAV) swarms to frequently alter their flight paths and communication links, which can easily cause network interruptions. It remains a significant challenge for ...

DOAJ Open Access (DOAJ) DOI: 10.1007/s40747-026-02343-y

Rider Optimization With Deep Learning Based Image Encryption for Secure Drone Communication

N. Kannaiya Raja, E. Laxmi Lydia, Thumpala Archana Acharya, K. Radhika et al. • IEEE Access (2023)

In recent years, drones or Unmanned Aerial Vehicles (UAVs) got significant attention among researchers because of their extensive application in commercial applications, border surveillance, etc. As the conventional terrestrial communicatio...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3324068

Learning to decode linear codes using deep learning

Eliya Nachmani, Yair Be'ery, David Burshtein • Allerton Conference on Communication, Control, and Computing (2016)

A novel deep learning method for improving the belief propagation algorithm is proposed. The method generalizes the standard belief propagation algorithm by assigning weights to the edges of the Tanner graph. These edges are then trained us...

OPENALEX Open Access DOI: https://doi.org/10.1109/allerton.2016.7852251

Privacy-Preserving Deep Learning

Reza Shokri, Vitaly Shmatikov • ACM SIGSAC Conference on Computer and Communications Security (CCS) (2015)

Deep learning based on artificial neural networks is a very popular approach to modeling, classifying, and recognizing complex data such as images, speech, and text. The unprecedented accuracy of deep learning methods has turned them into t...

OPENALEX DOI: https://doi.org/10.1145/2810103.2813687

CAMELON: A System for Crime Metadata Extraction and Spatiotemporal Visualization From Online News Articles

Siripen Pongpaichet, Boonyapat Sukosit, Chitchaya Duangtanawat, Jiramed Jamjongdamrongkit et al. • IEEE Access (2024)

Crimes result in not only loss to individuals but also hinder national economic growth. While crime rates have been reported to decrease in developed countries, underdeveloped and developing nations still suffer from prevalent crimes, espec...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3363879

Controlled Signal Technique in VL‐NOMA Communication Under Interference‐Controlled Environment With Intelligent Reflecting Surfaces

C. E. Ngene, Prabhat Thakur, Ghanshyam Singh • Engineering Reports (2025)

ABSTRACT This paper proposes a controlled signal technique for visible light non‐orthogonal multiple access (VL‐NOMA) communication in an interference‐controlled environment with intelligent reflecting surfaces (IRS) for beyond 5G (B5G) and...

DOAJ Open Access (DOAJ) DOI: 10.1002/eng2.13087

Research on high-precision recognition model for multi-scene asphalt pavement distresses based on deep learning

Sheng Zhang, Zhenghao Bei, Tonghua Ling, Qianqian Chen et al. • Scientific Reports (2024)

Abstract Accurate detection of asphalt pavement distress is crucial for road maintenance and traffic safety. However, traditional convolutional neural networks usually struggle with this task due to the varied distress patterns and complex ...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-024-77173-4

Deep Learning-Based Channel Estimation

Mehran Soltani, Vahid Pourahmadi, Ali Mirzaei, Hamid Sheikhzadeh • IEEE Communications Letters (2019)

In this letter, we present a deep learning algorithm for channel estimation in communication systems. We consider the time-frequency response of a fast fading communication channel as a 2D image. The aim is to find the unknown values of the...

OPENALEX Open Access DOI: https://doi.org/10.1109/lcomm.2019.2898944

Research on Strategies and Technologies for Resource Management and Control of Heterogeneous Network of High and Low Orbit Satellites

Meirong ZHANG, Mengting HAO, Chuang WANG, Gengxin ZHANG • 天地一体化信息网络 (2021)

With the vigorous development of space communication technology and the continuous advancement of space-integrated-ground information network, satellite communication networks resource management and control is becoming more and more comple...

DOAJ Open Access (DOAJ)

<i>H<sup>2</sup>A<sup>2</sup></i>Net: A Hybrid Convolution and Hybrid Resolution Network with Double Attention for Hyperspectral Image Classification

Hao Shi, Guo Cao, Youqiang Zhang, Zixian Ge et al. • Remote Sensing (2022)

Deep learning (DL) has recently been a core ingredient in modern computer vision tasks, triggering a wave of revolutions in various fields. The hyperspectral image (HSI) classification task is no exception. A wide range of DL-based methods ...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs14174235

Multi-Head Transformer Architecture with Higher Dimensional Feature Representation for Massive MIMO CSI Feedback

Qing Chen, Aihuang Guo, Yaodong Cui • Applied Sciences (2024)

To achieve the anticipated performance of massive multiple input multiple output (MIMO) systems in wireless communication, it is imperative that the user equipment (UE) accurately feeds the channel state information (CSI) back to the base s...

DOAJ Open Access (DOAJ) DOI: 10.3390/app14041356

An Integrated Method for River Water Level Recognition from Surveillance Images Using Convolution Neural Networks

Chen Chen, Rufei Fu, Xiaojian Ai, Chengbin Huang et al. • Remote Sensing (2022)

Water conservancy personnel usually need to know the water level by water gauge images in real-time and with an expected accuracy. However, accurately recognizing the water level from water gauge images is still a complex problem. This arti...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs14236023