Academic Articles & Research Papers

Natural Language Processing

Natural language processing is widely discussed and researched topic nowadays. As it is one of the oldest area of research in machine learning it is used in major fields such as machine translation speech recognition and text processing. Na...

Attention in Natural Language Processing

Attention is an increasingly popular mechanism used in a wide range of neural architectures. The mechanism itself has been realized in a variety of formats. However, because of the fast-paced advances in this domain, a systematic overview o...

Advances in natural language processing

Natural language processing employs computational techniques for the purpose of learning, understanding, and producing human language content. Early computational approaches to language research focused on automating the analysis of the lin...

Natural language processing: an introduction

OBJECTIVES: To provide an overview and tutorial of natural language processing (NLP) and modern NLP-system design. TARGET AUDIENCE: This tutorial targets the medical informatics generalist who has limited acquaintance with the principles be...

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...

Mobile learning for less-commonly taught languages: design and application

The increasing development of emerging technologies contributes to ubiquitous and personalized language learning. Hence this study reported a project of designing and applying mobile learning for a less-commonly taught language, Fijian lang...

A Scoping Review of Deep Learning Methods for Photoplethysmography Data.

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...

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 ...

A comprehensive survey on RGB-D-based human action recognition: algorithms, datasets, and popular applications

Abstract Due to the rapid advances in computer vision and deep learning, human action recognition has become one of the most important representative tasks for video understanding. Especially for human action recognition based on RGB-D data...

Artificial Intelligence in Routine IVF Practice

Background: Artificial Intelligence (AI) has emerged as a transformative tool in in vitro fertilization (IVF) as it has done in other sectors. In IVF, AI offers advancements in embryo selection, treatment personalization, and outcome predic...

Identification of camouflage military individuals with deep learning approaches DFAN and SINETV2

Abstract Camouflaged object detection particularly is considered as challenging and crucial because these objects are designed to either mimic their environment or be completely hidden within it. The goal of camouflage patterns utilization ...

Machine Learning in Computer Vision: A Review

INTRODUCTION: Due to the advancement in the field of Artificial Intelligence (AI), the ability to tackle entire problems of machine intelligence. Nowadays, Machine learning (ML) is becoming a hot topic due to the direct training of machines...

Hyperspectral imaging and machine learning in brain tumor surgery: Current evidence, clinical applications, and future directions.

Discovery of Rare Phenotypes in Cellular Images Using Weakly Supervised Deep Learning.

TranSDet: Toward Effective Transfer Learning for Small-Object Detection

Small-object detection is a challenging task in computer vision due to the limited training samples and low-quality images. Transfer learning, which transfers the knowledge learned from a large dataset to a small dataset, is a popular metho...

Research progress and trends of deep learning based wireless communication receiving method

With the continues expansion of the application boundary for wireless communications, the application environment of wireless communications is becoming increasingly complex and diverse, which faces negative impacts such as radio frequency ...

UPANets: Learning from the Universal Pixel Attention Neworks

With the successful development in computer vision, building a deep convolutional neural network (CNNs) has been mainstream, considering the character of shared parameters in a convolutional layer. Stacking convolutional layers into a deep ...

Studying the causes of humidity fluctuations in food products within industrial environments

The production of processed foods and animal nutrition requires precise control over product characteristics to ensure consistent quality. Unexpected fluctuations in key parameters, particularly humidity, can lead to significant financial l...

RGB-D Tracking and Optimal Perception of Deformable Objects

Addressing the perception problem of texture-less objects that undergo large deformations and movements, this article presents a novel RGB-D learning-free deformable object tracker in combination with a camera position optimisation system f...