Reset
Showing 20 of 549 academic articles

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

Deep Learning-Based Prediction of Wind Power for Multi-turbines in a Wind Farm

Xiaojiao Chen, Xiuqing Zhang, Mi Dong, Liansheng Huang et al. • Frontiers in Energy Research (2021)

The prediction of wind power plays an indispensable role in maintaining the stability of the entire power grid. In this paper, a deep learning approach is proposed for the power prediction of multiple wind turbines. Starting from the time s...

DOAJ Open Access (DOAJ) DOI: 10.3389/fenrg.2021.723775

Deep Learning for Video Game Playing

Niels Justesen, Philip Bontrager, Julian Togelius, Sebastian Risi • IEEE Transactions on Games (2019)

In this paper, we review recent deep learning advances in the context of how they have been applied to play different types of video games such as first-person shooters, arcade games, and real-time strategy games. We analyze the unique requ...

OPENALEX Open Access DOI: https://doi.org/10.1109/tg.2019.2896986

A learning‐based energy management strategy for hybrid energy storage systems with compressed air and solid oxide fuel cells

Yundie Guan, Xiangyu Zhang, Zheming Liang, Tao Chen • IET Renewable Power Generation (2025)

Abstract The intermittency and volatility of renewable energy have been major challenges in modern power systems. This paper proposes a self‐adaptive energy management strategy based on deep reinforcement learning (DRL) to integrate renewab...

DOAJ Open Access (DOAJ) DOI: 10.1049/rpg2.13192

ACtriplet: An improved deep learning model for activity cliffs prediction by integrating triplet loss and pre-training

Xinxin Yu, Yimeng Wang, Long Chen, Weihua Li et al. • Journal of Pharmaceutical Analysis (2025)

Activity cliffs (ACs) are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target. ACs offer crucial insights that aid m...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jpha.2025.101317

Systemic Review and Meta-Analysis: The Application of AI-Powered Drone Technology with Computer Vision and Deep Learning Networks in Waste Management

Tyrone Bright, Sarp Adali, Cristina Trois • Drones (2025)

As the generation of Municipal Solid Waste (MSW) has exponentially increased, this poses a challenge for waste managers, such as municipalities, to effectively control waste streams. If waste streams are not managed correctly, they negative...

DOAJ Open Access (DOAJ) DOI: 10.3390/drones9080550

A longitudinal study on students’ self-regulated listening during transition to an English-medium transnational university in China

Sihan Zhou, Gene Thompson • Studies in Second Language Learning and Teaching (2023)

Listening to academic content in English medium instruction (EMI) classrooms at university can be a demanding task for students who transition from first language (L1) instructed secondary schools. This longitudinal mixed methods study anal...

DOAJ Open Access (DOAJ) DOI: 10.14746/ssllt.38281

Gene expression inference with deep learning

Yifei Chen, Yi Li, Rajiv Narayan, Aravind Subramanian et al. • Bioinformatics (2016)

MOTIVATION: Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dro...

OPENALEX Open Access DOI: https://doi.org/10.1093/bioinformatics/btw074 PMC: 4908320

Deployment optimization of laser chargers in self-organizing power transfer internet of things

Junzhe Hu, Chuanwen Luo, Yi Hong, Guopeng Wang et al. • Wireless Power Transfer (2025)

Recently, the Internet of Things (IoT) has played an important role in many fields. Nevertheless, the fast and uneven energy consumption of IoT Devices (IoTDs) significantly limits the lifetime of IoT networks. One of the effective solution...

DOAJ Open Access (DOAJ) DOI: 10.48130/wpt-0025-0004

SPAF-SegNeXt: Prior-Guided Attention and Frequency-Spatial Hybrid Fusion for Multimodal Sugarcane Segmentation in Remote Sensing

Wei Zhang, Chao Ren, Haoming Bai, Huada Huang et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2026)

Accurate monitoring of the spatial extent of sugarcane cultivation is critical for optimizing land-use efficiency and regulating the sugar industry. However, sugarcane cultivation areas are characterized by complex topography and fragmented...

DOAJ Open Access (DOAJ) DOI: 10.1109/JSTARS.2026.3716367

Integrating multi-source geoscience data with RF-weighted conditional variational autoencoders (CVAE) for porphyry copper prospectivity mapping: an application to the Ardestan district, Central Iran

Samane Esmaelzade Kalkhoran, Seyyed Saeed Ghannadpour • Scientific Reports (2026)

Abstract Porphyry Cu deposits in the Urmia–Dokhtar magmatic belt constitute important exploration targets, yet the heterogeneous and multi-scale nature of geological, geochemical, and remote sensing data introduces substantial uncertainty i...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-61085-6

Deep Learning for Generic Object Detection: A Survey

Li Liu, Wanli Ouyang, Xiaogang Wang, Paul Fieguth et al. • International Journal of Computer Vision (2019)

Abstract Object detection, one of the most fundamental and challenging problems in computer vision, seeks to locate object instances from a large number of predefined categories in natural images. Deep learning techniques have emerged as a ...

OPENALEX cc-by DOI: https://doi.org/10.1007/s11263-019-01247-4

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)

Deep Learning-Based Land Cover Extraction from Very-High-Resolution Satellite Imagery for Assisting Large-Scale Topographic Map Production

Yofri Furqani Hakim, Fuan Tsai • Remote Sensing (2025)

The demand for large-scale topographic maps in Indonesia has significantly increased due to the implementation of several government initiatives that necessitate the utilization of spatial data in development planning. Currently, the nation...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs17030473

TransImg: A Translation Algorithm of Visible-to-Infrared Image Based on Generative Adversarial Network

Shuo Han, Bo Mo, Junwei Xu, Shizun Sun et al. • International Journal of Computational Intelligence Systems (2024)

Abstract Infrared images of sensitive targets are difficult to obtain and cannot meet the design and training needs of target detection and tracking algorithms for mobile platforms such as aircraft. This paper proposes an image translation ...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44196-024-00674-7