Academic Articles & Research Papers

Deep learning-based personalized learning path recommendation system for higher education

Abstract The growing variety of student profiles in higher education has made it more important than ever to have smart systems that can change learning experiences on the job. Current recommendation algorithms fail to capture the complex r...

Multi-Task Learning in Natural Language Processing: An Overview

Deep learning approaches have achieved great success in the field of Natural Language Processing (NLP). However, directly training deep neural models often suffer from overfitting and data scarcity problems that are pervasive in NLP tasks. ...

Which factors influence public perceptions of urban attractions? — A comparative study

To better serve the public, urban attractions must understand the public's likes and dislikes and continually adapt and optimize their service in response. However, traditional methods for gauging public opinion, such as questionnaires and ...

Natural language processing

Summary form only given. Natural language processing (NLP) is a major area of artificial intelligence research, which in its turn serves as a field of application and interaction of a number of other traditional AI areas. Until recently, th...

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...

Optimization for Computer Vision

Bridging the performance–efficiency gap: a resource-efficient hybrid DL-ML framework for jackfruit disease detection

Complex environment variability and limited computational resources in agricultural settings create challenges in automated detection in tropical regions, where jackfruit diseases pose major threats to harvest productivity and food security...

Sequential Normalization: Embracing Smaller Sample Sizes for Normalization

Normalization as a layer within neural networks has over the years demonstrated its effectiveness in neural network optimization across a wide range of different tasks, with one of the most successful approaches being that of batch normaliz...

High Performance GPU Strategies for Real-Time In-Cabin Monitoring

With the expeditious advancement in multicarrier automotive in-vehicle monitoring for a bus conforming environment with computer vision, there is an exigency for a setup subsisting on inspection cameras and an onboard embedded computing dev...

A Self-Adaptive Traffic Signal System Integrating Real-Time Vehicle Detection and License Plate Recognition for Enhanced Traffic Management

Traffic management systems play a crucial role in smart cities, especially because increasing urban populations lead to higher traffic volumes on roads. This results in increased congestion at intersections, causing delays and traffic viola...

A comprehensive analytical assessment of dino-based architectures for sustainable automated potato inspection in the Al Kharj Region

Abstract Self-supervised learning (SSL) has emerged as a pivotal paradigm in computer vision, particularly for applications where labeled data are limited, costly, or labor-intensive to obtain. This paradigm is especially relevant to sustai...

Discriminative feature encoding for intrinsic image decomposition

Abstract Intrinsic image decomposition is an important and long-standing computer vision problem. Given an input image, recovering the physical scene properties is ill-posed. Several physically motivated priors have been used to restrict th...

A lightweight optimization framework for real-time pedestrian detection in dense and occluded scenes

Pedestrian detection is one of the most widely applied tasks in industrial computer vision. It encapsulates three core challenges of object detection: detecting small objects, handling heavy occlusion, and balancing speed and accuracy for d...

Development of a hybrid artificial intelligence framework for pharmacotherapy optimization.

FOCUS: a feature optimization and cascaded unified screening strategy for computer-aided pathology-based glioma molecular subtype classification.

A Novel Mixed-Precision Quantization Approach for CNNs

Model size and inference speed have brought about major challenges for the deployment of Convolutional Neural Networks (CNNs) in many applications. An effective approach to address this issue is model quantization, which achieves network co...

Toward Automated Structural Design for Controlled Vibration Characteristics Using Topology Optimization and Computer Vision in Space Missions

This study explores the integration of computer vision with topology optimization for additive manufacturing, with a focus on maximizing eigenfrequency in a design domain. Utilizing custom-developed photogrammetry software, high-resolution ...

Scale Accuracy Evaluation of Image-Based 3D Reconstruction Strategies Using Laser Photogrammetry

Rapid developments in the field of underwater photogrammetry have given scientists the ability to produce accurate 3-dimensional (3D) models which are now increasingly used in the representation and study of local areas of interest. This pa...

OmniVO: Toward Robust Omni Directional Visual Odometry With Multicamera Collaboration for Challenging Conditions

With the recent developments in computer vision, vision-based odometry plays an increasingly important role in the field of autonomous systems. However, using traditional visual odometry or simultaneous localization and mapping (vSLAM) only...

Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead

Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning (DL) is already present in many applications ranging from computer vision for medicine to autonomous driving of modern cars as well as other sectors in ...