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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

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

A novel agricultural commodity price prediction model integrating deep learning and enhanced swarm intelligence algorithm.

Kaixuan Sun, Qi Yao, Yanhui Li • PLoS ONE (2025)

The volatility of agricultural commodity prices significantly affects market stability and financial market dynamics, especially during periods of economic uncertainty and global shocks. Accurate price prediction, however, remains challengi...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0337103

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

Deep Learning in Medical Ultrasound Analysis: A Review

Shengfeng Liu, Yi Wang, Xin Yang, Baiying Lei et al. • Engineering (2019)

Ultrasound (US) has become one of the most commonly performed imaging modalities in clinical practice. It is a rapidly evolving technology with certain advantages and with unique challenges that include low imaging quality and high variabil...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.eng.2018.11.020

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 Cardiac Image Segmentation: A Review

Chen Chen, Chen Qin, Huaqi Qiu, Giacomo Tarroni et al. • Frontiers in Cardiovascular Medicine (2020)

Deep learning has become the most widely used approach for cardiac image segmentation in recent years. In this paper, we provide a review of over 100 cardiac image segmentation papers using deep learning, which covers common imaging modalit...

OPENALEX cc-by DOI: https://doi.org/10.3389/fcvm.2020.00025 PMC: 7066212

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 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

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 deep learning-driven pipeline for differentiating hypertrophic cardiomyopathy from cardiac amyloidosis using 2D multi-view echocardiography

Xiaofeng Li, Bo Peng, Xinyu Li, Zhenghan Wang et al. • Scientific Reports (2026)

Abstract Hypertrophic Cardiomyopathy (HCM) and Cardiac Amyloidosis (CA) are two cardiac conditions that can advance to heart failure if left untreated, which present considerable diagnostic challenges due to their overlapping echocardiograp...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-15443-5

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

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 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