Academic Articles & Research Papers

Handbook of Mathematical Models in Computer Vision

Rethinking the Inception Architecture for Computer Vision

Convolutional networks are at the core of most state-of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to become mainstream, yielding substantial gains in various benchmark...

TongueBench: performance of prompt-engineered large multimodal models in Traditional Chinese Medicine tongue diagnosis.

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 ...

Deep learning based identification and tracking of railway bogie parts

The Train Rolling-Stock Examination (TRSE) is a safety examination process that physically examines the bogie parts of a moving train, typically at speeds over 30 km/h. Currently, this inspection process is done manually by railway personne...

Applied research note: Predicting carcass portion weights for purebred turkey (Meleagris gallopavo) lines using a 2D imaging system

Summary: Improving carcass portion yields (e.g., breast meat) is a major goal of modern turkey breeding and traditionally requires manual collection of portion weights. This can be a labor-intensive process considering the large amount of d...

Tamarind health assessment dataset: Images of shelled, unshelled, and mixed tamarind podsMendeley Data

This data paper provides image dataset that includes 8432 high-quality images of Tamarindus indica [1] (tamarind), categorized into six types: Shelled Healthy Single, Shelled Healthy Multiple, Unshelled Healthy Single, Unshelled Healthy Mul...

A critical review on computer vision and artificial intelligence in food industry

Emerging technologies such as computer vision and Artificial Intelligence (AI) are estimated to leverage the accessibility of big data for active training and yielding operational real time smart machines and predictable models. This phenom...

Rethinking the Inception Architecture for Computer Vision

Convolutional networks are at the core of most state of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to become mainstream, yielding substantial gains in various benchmark...

An Exploratory Study: Can Vision-Enabled Large Language Models Interpret Selected Static Urologic Images?

A lightweight fully convolutional neural network for efficient and accurate tunnel crack detection

Introduction: Crack damage is a significant issue in tunnel environments, requiring efficient and reliable detection to ensure structural integrity. Many existing solutions are computationally expensive, making them unsuitable for the tight...

Backhand-Approach-Based American Sign Language Words Recognition Using Spatial-Temporal Body Parts and Hand Relationship Patterns

Most of the existing methods focus mainly on the extraction of shape-based, rotation-based, and motion-based features, usually neglecting the relationship between hands and body parts, which can provide significant information to address th...

Integrating Computer Vision: Advancements in Fire and Smoke Detection Using CNNs

Conventional fire detection systems, which depend on smoke and fire sensors, frequently have problems with calibration, susceptibility to environmental changes, and the requirement for ongoing maintenance. These flaws can result in unfavora...

Data Efficient Vision Transformer Based Model for Brain Tumor Classification in MRI

Accurate detection of brain tumors at early stages is crucial for clinical diagnosis and treatment planning. Magnetic Resonance Imaging (MRI) is the most popular method due to its soft-tissue contrast and spatial resolution. However, manual...

DualSight: multi-stage instance segmentation framework for improved precision

Abstract Powder properties, particularly their morphology (which includes size, shape, surface roughness, etc.), play a critical role in the quality of cold spray additively manufactured materials. A change in feedstock powder morphology ca...

Multimodal Phase-Space Dynamics Fusion for Robust Ischemia Screening: An Edge-AI Paradigm with SERF Magnetocardiography

Background: Myocardial ischemia (MI) is a major cause of morbidity and mortality worldwide and requires timely and reliable detection. Although Spin-Exchange Relaxation-Free (SERF) magnetocardiography (MCG) provides femtotesla-level sensiti...

DAPS3D: Domain Adaptive Projective Segmentation of 3D LiDAR Point Clouds

LiDARs are one of the key sources of reliable environmental ranging information for autonomous vehicles. However, segmentation of 3D scene elements (roads, buildings, people, cars, etc.) based on LiDAR point clouds has limitations. On the o...

HawkEye: AI-Driven Software for Objective Analysis and Characterization of Nodular Cast Iron Microstructures

Metallographic evaluation of nodular cast iron is crucial for quality control in the foundry industry. Traditionally, this process relies on experts who visually interpret microscopic images. This study introduces HawkEye, a comprehensive s...

Application of Graph Structures in Computer Vision Tasks

On the one hand, the solution of computer vision tasks is associated with the development of various kinds of images or random fields mathematical models, i.e., algorithms, that are called traditional image processing. On the other hand, no...

Attention is All Large Language Model Need

With the advent of the Transformer, the attention mechanism has been applied to Large Language Model (LLM), evolving from initial single- modal large models to today's multi-modal large models. This has greatly propelled the development of ...