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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

Deep learning as a tool for ecology and evolution

Marek L. Borowiec, Rebecca B. Dikow, Paul B. Frandsen, Alexander J. McKeeken et al. • Methods in Ecology and Evolution (2022)

Abstract Deep learning is driving recent advances behind many everyday technologies, including speech and image recognition, natural language processing and autonomous driving. It is also gaining popularity in biology, where it has been use...

OPENALEX cc-by-nc DOI: https://doi.org/10.1111/2041-210x.13901

Deep learning wavefront sensing

Yohei Nishizaki, Matias Valdivia, Ryoichi Horisaki, Katsuhisa Kitaguchi et al. • Optics Express (2019)

We present a new class of wavefront sensors by extending their design space based on machine learning. This approach simplifies both the optical hardware and image processing in wavefront sensing. We experimentally demonstrated a variety of...

OPENALEX Open Access DOI: https://doi.org/10.1364/oe.27.000240

Deep Learning on Graphs: A Survey

Ziwei Zhang, Peng Cui, Wenwu Zhu • IEEE Transactions on Knowledge and Data Engineering (2020)

Deep learning has been shown to be successful in a number of domains, ranging from acoustics, images, to natural language processing. However, applying deep learning to the ubiquitous graph data is non-trivial because of the unique characte...

OPENALEX Open Access DOI: https://doi.org/10.1109/tkde.2020.2981333

A review on deep learning in medical image analysis

S. Suganyadevi, V. Seethalakshmi, K. Balasamy • International Journal of Multimedia Information Retrieval (2021)

Ongoing improvements in AI, particularly concerning deep learning techniques, are assisting to identify, classify, and quantify patterns in clinical images. Deep learning is the quickest developing field in artificial intelligence and is ef...

OPENALEX other-oa DOI: https://doi.org/10.1007/s13735-021-00218-1 PMC: 8417661

Combining the YOLOv4 Deep Learning Model with UAV Imagery Processing Technology in the Extraction and Quantization of Cracks in Bridges

Szu-Pyng Kao, Yung-Chen Chang, Feng-Liang Wang • Sensors (2023)

Bridges are often at risk due to the effects of natural disasters, such as earthquakes and typhoons. Bridge inspection assessments normally focus on cracks. However, numerous concrete structures with cracked surfaces are highly elevated or ...

DOAJ Open Access (DOAJ) DOI: 10.3390/s23052572

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

Automated Lung Sound Classification Using a Hybrid CNN-LSTM Network and Focal Loss Function

Georgios Petmezas, Grigorios-Aris Cheimariotis, Leandros Stefanopoulos, Bruno Rocha et al. • Sensors (2022)

Respiratory diseases constitute one of the leading causes of death worldwide and directly affect the patient’s quality of life. Early diagnosis and patient monitoring, which conventionally include lung auscultation, are essential for the ef...

DOAJ Open Access (DOAJ) DOI: 10.3390/s22031232

A Selective Overview of Deep Learning

Jianqing Fan, Cong Ma, Yiqiao Zhong • Statistical Science (2021)

Deep learning has achieved tremendous success in recent years. In simple words, deep learning uses the composition of many nonlinear functions to model the complex dependency between input features and labels. While neural networks have a l...

OPENALEX Open Access DOI: https://doi.org/10.1214/20-sts783 PMC: 8300482

Deep Learning with Microfluidics for Biotechnology

Jason Riordon, Dušan Sovilj, Scott Sanner, David A. Sinton et al. • Trends in biotechnology (2018)

Advances in high-throughput and multiplexed microfluidics have rewarded biotechnology researchers with vast amounts of data but not necessarily the ability to analyze complex data effectively. Over the past few years, deep artificial neural...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.tibtech.2018.08.005

Deep Learning for Image Super-Resolution: A Survey

Zhihao Wang, Jian Chen, Steven C. H. Hoi • IEEE Transactions on Pattern Analysis and Machine Intelligence (2020)

Image Super-Resolution (SR) is an important class of image processing techniqueso enhance the resolution of images and videos in computer vision. Recent years have witnessed remarkable progress of image super-resolution using deep learning ...

OPENALEX Open Access DOI: https://doi.org/10.1109/tpami.2020.2982166

Computational Linguistics and Deep Learning

Christopher D. Manning • Computational Linguistics (2015)

Deep Learning waves have lapped at the shores of computational linguistics for several years now, but 2015 seems like the year when the full force of the tsunami hit the major Natural Language Processing (NLP) conferences. However, some pun...

OPENALEX Open Access DOI: https://doi.org/10.1162/coli_a_00239

A Survey on Deep Learning for Named Entity Recognition

Jing Li, Aixin Sun, Jianglei Han, Chenliang Li • IEEE Transactions on Knowledge and Data Engineering (2020)

Named entity recognition (NER) is the task to identify mentions of rigid designators from text belonging to predefined semantic types such as person, location, organization etc. NER always serves as the foundation for many natural language ...

OPENALEX Open Access DOI: https://doi.org/10.1109/tkde.2020.2981314

A Review of Deep Learning Research

Ruihui Mu, Xiaoqin Zeng • KSII Transactions on Internet and Information Systems (2019)

With the advent of big data, deep learning technology has become an important research direction in the field of machine learning, which has been widely applied in the image processing, natural language processing, speech recognition and on...

OPENALEX Open Access DOI: https://doi.org/10.3837/tiis.2019.04.001

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

Deep Learning for the Earth Sciences

Gustau Camps‐Valls, Devis Tuia, Xiao Xiang Zhu, Markus Reichstein • Wiley eBooks (2021)

Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only re...

OPENALEX Open Access DOI: https://doi.org/10.1002/9781119646181