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Natural Language Processing in Oncology

Wen-wai Yim, Meliha Yetişgen, William Proctor Harris, Sharon W. Kwan • JAMA Oncology (2016)

IMPORTANCE: Natural language processing (NLP) has the potential to accelerate translation of cancer treatments from the laboratory to the clinic and will be a powerful tool in the era of personalized medicine. This technology can harvest im...

OPENALEX DOI: https://doi.org/10.1001/jamaoncol.2016.0213

Natural language processing

Gobinda G Chowdhury • Annual Review of Information Science and Technology (2003)

Previous ARIST chapters (Haas, 1996;Warner, 1987) described a number of theoretical developments that have influenced research in NLP.The most recent theoretical developments can be grouped into four classes: (i) statistical and corpus-base...

OPENALEX Open Access DOI: https://doi.org/10.1002/aris.1440370103

Natural language processing with Python

Steven Bird, Ewan Klein, Edward Loper • CERN Document Server (European Organization for Nuclear Research) (2009)

This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'...

OPENALEX

An image based application in Matlab for automated modelling and morphological analysis of insect wings

Shahab Eshghi, Fatemeh Nabati, Shaghayegh Shafaghi, Vahid Nooraeefar et al. • Scientific Reports (2022)

Abstract Despite extensive research on the biomechanics of insect wings over the past years, direct mechanical measurements on sensitive wing specimens remain very challenging. This is especially true for examining delicate museum specimens...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-022-17859-9

Autonomous Driving Roadway Feature Interpretation Using Integrated Semantic Analysis and Domain Adaptation

Suyang Xi, Zihan Liu, Ziming Wang, Qiang Zhang et al. • IEEE Access (2024)

Lane detection is fundamental to autonomous driving, yet remains challenging in complex environments with occlusions, ambiguous markings, and varied lighting. We introduce the Global Semantic Enhancement Network (GSENet), a groundbreaking f...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3429396

Computer Vision System for Automatic Counting of Planting Microsites Using UAV Imagery

Wassim Bouachir, Koffi Eddy Ihou, Houssem-Eddine Gueziri, Nizar Bouguila et al. • IEEE Access (2019)

Mechanical site preparation by mounding is often used by the forest industry to provide optimal growth conditions for tree seedlings. Prior to planting, an essential step consists in estimating the number of mounds at each planting block, w...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2019.2923765

A Methodological Review on Prediction of Multi-Stage Hypovigilance Detection Systems Using Multimodal Features

Qaisar Abbas, Abdullah Alsheddy • IEEE Access (2021)

Several hypovigilance detection systems (HDx) were developed to avoid road-side accidents due to driver fatigue. They have suffered from several limitations. Notably many of these are focused on center-head position to define an area of int...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2021.3068343

Geo-Temporal Selective Approach for Dynamic Depth Estimation in Outdoor Object Detection and Distance Measurement

Muhammad Faseeh, Misbah Bibi, Murad Ali Khan, Atif Rizwan et al. • IEEE Access (2024)

Accurate depth information is crucial for various computer vision applications such as augmented reality, 3D modeling, and autonomous vehicles. Recent advancements have significantly improved both supervised and self-supervised methods for ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3485089

Melanoma Lesion Detection and Segmentation Using YOLOv4-DarkNet and Active Contour

Saleh Albahli, Nudrat Nida, Aun Irtaza, Muhammad Haroon Yousaf et al. • IEEE Access (2020)

Melanoma is the skin cancer caused by the ultraviolet radiation from the Sun and has only 15-20% of survival rate. Late diagnosis of melanoma leads to the severe malignancy of disease, and metastasis expands to the other body organs i.e. li...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3035345

Federated Learning in Computer Vision

Donald Shenaj, Giulia Rizzoli, Pietro Zanuttigh • IEEE Access (2023)

Federated Learning (FL) has recently emerged as a novel machine learning paradigm allowing to preserve privacy and to account for the distributed nature of the learning process in many real-world settings. Computer vision tasks deal with hu...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1109/access.2023.3310400

Cross-Correlation-Based Structural System Identification Using Unmanned Aerial Vehicles

Hyungchul Yoon, Vedhus Hoskere, Jong-Woong Park, Billie F. Spencer • Sensors (2017)

Computer vision techniques have been employed to characterize dynamic properties of structures, as well as to capture structural motion for system identification purposes. All of these methods leverage image-processing techniques using a st...

DOAJ Open Access (DOAJ) DOI: 10.3390/s17092075

Reliable Parkinson’s Disease Detection by Analyzing Handwritten Drawings: Construction of an Unbiased Cascaded Learning System Based on Feature Selection and Adaptive Boosting Model

Liaqat Ali, Ce Zhu, Noorbakhsh Amiri Golilarz, Ashir Javeed et al. • IEEE Access (2019)

Parkinson's disease (PD) is the second most common neurodegenerative disease of central nervous system (CNS). Till now, there is no definitive clinical examination that can diagnose a PD patient. However, it has been reported that PD patien...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2019.2932037

VISION-LINK AI Smart Glass: An Edge-Cloud Wearable AI System for Workflow Automation and Digital Inclusion in Emerging Economies

Buhari Salisu • International Journal of AI and Advanced Computing (2026)

The rapid advancement of Artificial Intelligence (AI), wearable computing, and Internet of Things (IoT) technologies has significantly transformed digital interactions across various sectors. However, the adoption of smart wearable technolo...

DOAJ Open Access (DOAJ) DOI: 10.5281/zenodo.21981139