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Showing 20 of 785 academic articles

DEEP LEARNING-BASED DOOR AND WINDOW DETECTION FROM BUILDING FAÇADE

G. Sezen, M. Cakir, M. E. Atik, Z. Duran • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2022)

Detecting building façade elements is a crucial problem in computer vision for image interpretation. In Building Information Modeling (BIM) studies, the detection of building façade elements has an important role. BIM is a tool that allows ...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprs-archives-XLIII-B4-2022-315-2022

Rethinking the Inception Architecture for Computer Vision

Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens et al. • arXiv (Cornell University) (2015)

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...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1512.00567

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

Maurizio Capra, Beatrice Bussolino, Alberto Marchisio, Guido Masera et al. • IEEE Access (2020)

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 ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3039858

Automated detection of bicycle helmets using deep learning

Felix Wilhelm Siebert, Christoffer Riis, Kira Hyldekær Janstrup, Hanhe Lin et al. • Journal of Cycling and Micromobility Research (2024)

Bicycle helmets are a main measure for injury prevention in case of a crash and are a central variable in transport safety studies. Despite this, helmet use data is only collected sporadically, as the observation of helmet use in traffic by...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jcmr.2024.100013

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

Amol Bhosle, Deepali Godse, Sandip Thite, Kailas Patil et al. • Data in Brief (2025)

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...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.dib.2025.111917

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

Vijay Kakani, Van Huan Nguyen, Basivi Praveen Kumar, Hakil Kim et al. • Journal of Agriculture and Food Research (2020)

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...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.jafr.2020.100033

Rethinking the Inception Architecture for Computer Vision

Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens et al. • IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (2016)

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...

OPENALEX DOI: https://doi.org/10.1109/cvpr.2016.308

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

Hao Huang, G.T.S. Ho, V. Tang, E.W.H. Chow et al. • Journal of Advanced Research (2026)

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...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jare.2025.11.052

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

Vinodkumar Patil, Manisha Patil, Smital Patil, Satish Desale • Advances in Engineering and Intelligence Systems (2026)

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...

DOAJ Open Access (DOAJ) DOI: 10.22034/aeis.2026.570662.1424

DualSight: multi-stage instance segmentation framework for improved precision

Stephen Price, Kiran Judd, Kyle Tsaknopoulos, Rodica Neamtu et al. • Scientific Reports (2025)

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...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-09642-3

Generative Adversarial Networks in Computer Vision

Zhengwei Wang, Qi She, Tomas Emmanuel Ward • ACM Computing Surveys (2021)

Generative adversarial networks (GANs) have been extensively studied in the past few years. Arguably their most significant impact has been in the area of computer vision where great advances have been made in challenges such as plausible i...

OPENALEX Open Access DOI: https://doi.org/10.1145/3439723

Attention is All Large Language Model Need

Liu Yuxin • ITM Web of Conferences (2025)

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 ...

DOAJ Open Access (DOAJ) DOI: 10.1051/itmconf/20257302025

A Self-Supervised One-Shot Learning Approach for Seismic Noise Reduction

Catarina de Nazaré Pereira Pinheiro, Roosevelt de Lima Sardinha, Pablo Machado Barros, André Bulcão et al. • Applied Sciences (2024)

Neural networks have been used in various computer vision applications, including noise removal. However, removing seismic noise via deep learning approaches faces a specific issue: the scarcity of labeled data. To address this difficulty, ...

DOAJ Open Access (DOAJ) DOI: 10.3390/app14219721

Machine eye for defects: Machine learning-based solution to identify and characterize topological defects in textured images of nematic materials

Haijie Ren, Weiqiang Wang, Wentao Tang, Rui Zhang • Physical Review Research (2024)

Topological defects play a key role in the structures and dynamics of liquid crystals and other ordered systems. There is a recent interest in studying defects in different biological systems with distinct textures. However, a robust method...

DOAJ Open Access (DOAJ) DOI: 10.1103/PhysRevResearch.6.013259

A Comparative Study of Physically Accurate Synthetic Shadow Datasets in Agricultural Settings with Human Activity

Mengchen Huang, Ruben Fernandez-Beltran, Ginés García-Mateos • Sensors (2024)

Shadow, a natural phenomenon resulting from the absence of light, plays a pivotal role in agriculture, particularly in processes such as photosynthesis in plants. Despite the availability of generic shadow datasets, many suffer from annotat...

DOAJ Open Access (DOAJ) DOI: 10.3390/s24092737