Academic Articles & Research Papers

Fraud detection with natural language processing

Abstract Automated fraud detection can assist organisations to safeguard user accounts, a task that is very challenging due to the great sparsity of known fraud transactions. Many approaches in the literature focus on credit card fraud and ...

Detection of Duplicate Defect Reports Using Natural Language Processing

Defect reports are generated from various testing and development activities in software engineering. Sometimes two reports are submitted that describe the same problem, leading to duplicate reports. These reports are mostly written in stru...

Integrating NLP to Enhance Algorithmic Identification of Metastatic and Castration‐Resistant Prostate Cancer in Large Claims‐Based Studies

ABSTRACT Purpose Accurate classification of prostate cancer (PC) disease states defined by the presence or absence of metastasis and castration resistance (CRPC) is critical but challenging in population‐based research. As chart review is n...

Natural Language Processing

This chapter uncovers some of the basic techniques to tackle text data using PySpark. Today's textual form of data is being generated at a lightning pace with multiple social media platforms offering users the options to share their opinion...

A Survey on Natural Language Processing for Fake News Detection

Fake news detection is a critical yet challenging problem in Natural Language Processing (NLP). The rapid rise of social networking platforms has not only yielded a vast increase in information accessibility but has also accelerated the spr...

GBsim: A Robust GCN-BERT Approach for Cross-Architecture Binary Code Similarity Analysis

Recent advances in graph neural networks have transformed structural pattern learning in domains ranging from social network analysis to biomolecular modeling. Nevertheless, practical deployments in mission-critical scenarios such as binary...

Detecting Fake News in Urdu Language Using Machine Learning, Deep Learning, and Large Language Model-Based Approaches

Fake news is false or misleading information that looks like real news and spreads through traditional and social media. It has a big impact on our social lives, especially in politics. In Pakistan, where Urdu is the main language, finding ...

Navigating the Ethical Terrain of AI-Generated Text Tools: A Review

This review examines the ethical, social, and technical challenges posed by AI-generated text tools, focusing on their rapid advancement and widespread adoption. An exhaustive literature search across many databases, strict inclusion/exclus...

A systematic literature review on spam content detection and classification

The presence of spam content in social media is tremendously increasing, and therefore the detection of spam has become vital. The spam contents increase as people extensively use social media, i.e., Facebook, Twitter, YouTube, and E-mail. ...

A Semantic Hybrid Temporal Approach for Detecting Driver Mental Fatigue

Driver mental fatigue is considered a major factor affecting driver behavior that may result in fatal accidents. Several approaches are addressed in the literature to detect fatigue behavior in a timely manner through either physiological o...

Mention Detection for Coreference Resolution in Polish. Development of the Formal Grammar

Mention Detection for Coreference Resolution in Polish. Development of the Formal Grammar This paper presents the results of an improvement and extension of the Shallow Grammar of Polish, designed for the needs of the Computer-based Method...

Natural Language Processing for Requirements Engineering

Natural Language Processing for Requirements Engineering (NLP4RE) is an area of research and development that seeks to apply natural language processing (NLP) techniques, tools, and resources to the requirements engineering (RE) process, to...

Collectively encoding protein properties enriches protein language models

Abstract Pre-trained natural language processing models on a large natural language corpus can naturally transfer learned knowledge to protein domains by fine-tuning specific in-domain tasks. However, few studies focused on enriching such p...

GDG-YOLO: A dual-branch lightweight network based on global context augmentation for laryngeal disease detection.

Artificial intelligence-based masked face detection: A survey

The COVID-19 virus is causing a global pandemic. The total number of new coronavirus cases worldwide by the end of November 2020 had already surpassed 60 million. The World Health Organization (WHO) has determined that wearing masks is a cr...

Culling Double Counting in Sequence Images for Fruit Yield Estimation

Exact yield estimation of fruits on plants guaranteed fine and timely decisions on harvesting and marketing practices. Automatic yield estimation based on unmanned agriculture offers a viable solution for large orchards. Recent years have w...

Multi-Camera Machine Vision for Detecting and Analyzing Vehicle–Pedestrian Conflicts at Signalized Intersections: Deep Neural-Based Pose Estimation Algorithms

Over the past decade, researchers have advanced traffic monitoring using surveillance cameras, unmanned aerial vehicles (UAVs), loop detectors, LiDAR, microwave sensors, and sensor fusion. These technologies effectively detect and track veh...

DETECTION AND RECOGNITION OF ROAD SIGNS USING YOLOv5

In the field of deep learning, a convolutional neural network is a class of artificial neural networks that became dominant in various computer vision tasks, which is widely used to solve complex problems in various areas, including driver ...

Very large‐scale integration architecture for video stabilisation and implementation on a field programmable gate array‐based autonomous vehicle

Autonomous vehicles engaged in terrain exploration are typically equipped with a camera. The camera is subjected to vibration as the vehicle moves so that the videos captured require stabilisation to facilitate accurate interpretation by re...

Mobile system for road sign detection and recognition with template matching

This paper explores the effective approach to road sign detection and recognition based on mobile devices. Detecting and recognising road signs is a challenging matter because of different shapes, complex background and irregular sign illum...