Reset
Showing 20 of 1,033 academic articles

Image Segmentation Using Deep Learning: A Survey

Shervin Minaee, Yuri Y. Boykov, Fatih Porikli, Antonio Plaza et al. • IEEE Transactions on Pattern Analysis and Machine Intelligence (2021)

Image segmentation is a key task in computer vision and image processing with important applications such as scene understanding, medical image analysis, robotic perception, video surveillance, augmented reality, and image compression, amon...

OPENALEX Open Access DOI: https://doi.org/10.1109/tpami.2021.3059968

Applications of Deep Learning and Reinforcement Learning to Biological Data

Mufti Mahmud, M. Shamim Kaiser, Amir Hussain, Stefano Vassanelli • IEEE Transactions on Neural Networks and Learning Systems (2018)

Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics, bioimaging, medical imaging, and (brain/body...

OPENALEX Open Access DOI: https://doi.org/10.1109/tnnls.2018.2790388

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 Survey on Deep Learning for Steering Angle Prediction in Autonomous Vehicles

Usman Manzo Gidado, Haruna Chiroma, Nahla Aljojo, Saidu Abubakar et al. • IEEE Access (2020)

Steering angle prediction is critical in the control of Autonomous Vehicles (AVs) and has attracted the attention of researchers, manufacturers, and insurance companies in the automotive industry. Different Deep Learning (DL) architectures ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3017883

A Survey on Deep Learning for Human Mobility

Massimiliano Luca, Gianni Barlacchi, Bruno Lepri, Luca Pappalardo • ACM Computing Surveys (2021)

The study of human mobility is crucial due to its impact on several aspects of our society, such as disease spreading, urban planning, well-being, pollution, and more. The proliferation of digital mobility data, such as phone records, GPS t...

OPENALEX Open Access DOI: https://doi.org/10.1145/3485125

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

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

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

Deep Learning for Sequential Recommendation

Hui Fang, Danning Zhang, Yiheng Shu, Guibing Guo • ACM Transactions on Information Systems (2020)

In the field of sequential recommendation, deep learning--(DL) based methods have received a lot of attention in the past few years and surpassed traditional models such as Markov chain-based and factorization-based ones. However, there is ...

OPENALEX Open Access DOI: https://doi.org/10.1145/3426723

Time-series forecasting with deep learning: a survey

Bryan Y. Lim, Stefan Zohren • Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences (2021)

Numerous deep learning architectures have been developed to accommodate the diversity of time-series datasets across different domains. In this article, we survey common encoder and decoder designs used in both one-step-ahead and multi-hori...

OPENALEX Open Access DOI: https://doi.org/10.1098/rsta.2020.0209

Deep Learning: A Review

Rocio Vargas, Amir Hosein Mosavi, Ramon Ruiz • Preprints.org (2018)

Deep learning is an emerging area of machine learning (ML) research. It comprises multiple hidden layers of artificial neural networks. The deep learn- ing methodology applies nonlinear transformations and model abstractions of high level i...

OPENALEX cc-by DOI: https://doi.org/10.20944/preprints201810.0218.v1

Deep Learning for Hyperspectral Image Classification: An Overview

Shutao Li A, Weiwei Song, Leyuan Fang, Yushi Chen et al. • IEEE Transactions on Geoscience and Remote Sensing (2019)

Hyperspectral image (HSI) classification has become a hot topic in the field of remote sensing. In general, the complex characteristics of hyperspectral data make the accurate classification of such data challenging for traditional machine ...

OPENALEX Open Access DOI: https://doi.org/10.1109/tgrs.2019.2907932

Deep Learning in Mobile and Wireless Networking: A Survey

Chaoyun Zhang, Paul Patras, Hamed Haddadi • IEEE Communications Surveys & Tutorials (2019)

The rapid uptake of mobile devices and the rising popularity of mobile applications and services pose unprecedented demands on mobile and wireless networking infrastructure. Upcoming 5G systems are evolving to support exploding mobile traff...

OPENALEX Open Access DOI: https://doi.org/10.1109/comst.2019.2904897

Deep Learning for Anomaly Detection: A Survey

Raghavendra Chalapathy, Sanjay Chawla • arXiv (Cornell University) (2019)

Anomaly detection is an important problem that has been well-studied within diverse research areas and application domains. The aim of this survey is two-fold, firstly we present a structured and comprehensive overview of research methods i...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1901.03407

Application of Deep Learning in Food: A Review

Lei Zhou, Chu Zhang, Fei Liu, Zhengjun Qiu et al. • Comprehensive Reviews in Food Science and Food Safety (2019)

Deep learning has been proved to be an advanced technology for big data analysis with a large number of successful cases in image processing, speech recognition, object detection, and so on. Recently, it has also been introduced in food sci...

OPENALEX DOI: https://doi.org/10.1111/1541-4337.12492