Academic Articles & Research Papers

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...

Natural Language Processing

Understanding and processing human language has always been a complicated task in computational theory. Natural language processing, a combination of artificial intelligence and computational linguistics, employs computational techniques to...

A Model-Driven Approach Employing DSL and Generation Templates to Accelerate the Development of Conversational Agents for Smart Tourism

Conversational agents are intelligent, ubiquitous software applications widely used across various sectors, such as commerce, tourism, and more. Their key benefits include automating tasks, improving customer service, and ensuring service a...

A maximum entropy approach to natural language processing

The concept of maximum entropy can be traced back along multiple threads to Biblical times. Only recently, however, have computers become powerful enough to permit the widescale application of this concept to real world problems in statisti...

An Analysis of the Training Data Impact for Domain-Adapted Tokenizer Performances—The Case of Serbian Legal Domain Adaptation

Various areas of natural language processing (NLP) have greatly benefited from the development of large language models in recent years. This research addresses the challenge of developing efficient tokenizers for transformer-based domain-s...

A Refutation of Finite-State Language Models through Zipf’s Law for Factual Knowledge

We present a hypothetical argument against finite-state processes in statistical language modeling that is based on semantics rather than syntax. In this theoretical model, we suppose that the semantic properties of texts in a natural langu...

ILSA: an automated language complexity analysis tool for French

Estimating language complexity is an important aspect of educational measurement and assessment that can be used, for instance, to control for unwanted variance due to language, or to provide students with texts that are conducive to learni...

Natural Language Processing

Natural language processing (NLP) is the study of mathematical and computational modeling of various aspects of language and the development of a wide range of systems. These include spoken language systems that integrate speech and natural...

Assessing GPT's capabilities in consumer food survey analysis: A comparative approach for understanding food technophobia and novel protein perceptions

This study explores the application of GPT models for automating consumer food survey analysis, focusing on Chinese consumers' acceptance of plant-based foods, cultured meat, insect-based proteins, and microbial proteins. Traditional survey...

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...

Geometric modeling and computer vision

Geometric matching algorithms and geometric representations are examined for point sets, curves, surfaces, volumes, and their space-time trajectories. The author focuses mainly on general-purpose techniques. Geometric matching benefits grea...

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...

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

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...

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

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 ...

Estimating Black Oat Biomass Using Digital Surface Models and a Vegetation Index Derived from RGB-Based Aerial Images

Responsible for food production and industry inputs, agriculture needs to adapt to worldwide increasing demands and environmental requirements. In this scenario, black oat has gained environmental and economic importance since it can be use...

TransCat: a hybrid CNN-transformer network with KAN for medical image segmentation

Medical image segmentation is a fundamental task in computer vision and plays an important role in clinical diagnosis and treatment planning. Existing methods are mainly built on either convolutional neural networks (CNNs) or Transformer-ba...

Lightweight Road Image Segmentation Algorithm Based on Multi-Scale Feature Fusion for Blind Guiding Scenarios

Image segmentation is a crucial technology for environmental perception, and it is widely used in various scenarios such as autonomous driving and virtual reality. With the rapid development of technology, computer vision-based blind guidin...

Learning by Watching: A Review of Video-Based Learning Approaches for Robot Manipulation

Robot learning of manipulation skills is hindered by the scarcity of diverse, unbiased datasets. While curated datasets can help, challenges remain regarding generalizability and real-world transfer. Meanwhile, large-scale ‘in-the-wi...

Impact of Protein Conformational Diversity on Structure-Based Prediction of Druggability.

Computer Vision Techniques in Manufacturing

Computer vision techniques have played an important role in promoting the informatization, digitization and intelligence of industrial manufacturing systems. Considering the rapid development of computer vision techniques, we present a comp...