Academic Articles & Research Papers

Transfer Learning in Natural Language Processing

The classic supervised machine learning paradigm is based on learning in isolation, a single predictive model for a task using a single dataset. This approach requires a large number of training examples and performs best for well-defined a...

Natural Language Processing in Oncology

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...

Readings in natural language processing

Unpacking Public Perceptions of Qris with Twitter Data: A Vader And LDA Methodology

QRIS, a mobile payment transaction system standardized by Bank Indonesia, has become the subject of extensive public discourse on Twitter. Employing VADER for sentiment analysis and LDA for topic modeling, this study aims to capture the nua...

Computer Vision/Computer Graphics CollaborationTechniques

Cross-modal correlations in ensemble averaging across vision, audition, and touch.

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 ...

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...

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

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...

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...

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...

Membrane protein solubilization and structure determination using de novo-designed proteins.

A novel nondestructive detection approach for seed cotton lint percentage using deep learning

Abstract Background The lint percentage of seed cotton is one of the most important parameters for evaluating seed cotton quality and affects its price. The traditional measuring method of lint percentage is labor-intensive and time-consumi...

Hyperspectral Methane Plume Segmentation Through Foundation Computer Vision Models

Efficient large-scale monitoring of methane emissions is crucial for sustainable environmental management, necessitating advanced remote sensing techniques that process hyperspectral imagery to provide detailed insights into the Earth&#x201...

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

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...

Design of an Apple Harvesting Robot Based on Hybrid Pneumatic-Electric Drive System

This paper presents the design of a high-efficiency apple harvesting robot based on a hybrid pneumatic-electric drive system, capable of operating around the clock. The robotic system comprises a mobile platform with two degrees of freedom ...

Fruit freshness detection based on multi-task convolutional neural network

Background: Fruit freshness detection by computer vision is essential for many agricultural applications, e.g., automatic harvesting and supply chain monitoring. This paper proposes to use the multi-task learning (MTL) paradigm to build a d...