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Fruit freshness detection based on multi-task convolutional neural network

Yinsheng Zhang, Xudong Yang, Yongbo Cheng, Xiaojun Wu et al. • Current Research in Food Science (2024)

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...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.crfs.2024.100733

Performance Benchmarking: Pre-trained Models and Custom Convolutional Neural Networks in Deep Learning

Sheemona Joseph C., S. Ganesh, S. Kannadhasan, K. Selvipriya • Journal of Informatics and Web Engineering (2025)

Recent advances in computer vision and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly increased road safety. CNNs were used in this work to automatically detect and categorise traffic signs—a crucial ta...

DOAJ Open Access (DOAJ) DOI: 10.33093/jiwe.2025.4.2.14

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

Jin Wang, Zhenghua Yang, Dongming Zhou, Dongming Zhou et al. • Frontiers in Bioinformatics (2026)

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...

DOAJ Open Access (DOAJ) DOI: 10.3389/fbinf.2026.1849059

Deep Neural Networks and Kernel Density Estimation for Detecting Human Activity Patterns from Geo-Tagged Images: A Case Study of Birdwatching on Flickr

Caglar Koylu, Chang Zhao, Wei Shao • ISPRS International Journal of Geo-Information (2019)

Thanks to recent advances in high-performance computing and deep learning, computer vision algorithms coupled with spatial analysis methods provide a unique opportunity for extracting human activity patterns from geo-tagged social media ima...

DOAJ Open Access (DOAJ) DOI: 10.3390/ijgi8010045

Deep Learning for Computer Vision: A Brief Review

Ksheera R Shetty, Vaibhav S Soorinje, Prinson Dsouza, Swasthik • International Journal of Advanced Research in Science Communication and Technology (2022)

Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief ...

OPENALEX cc-by DOI: https://doi.org/10.48175/ijarsct-2898

Deep learning based computer vision approaches for smart agricultural applications

V. G. Dhanya, Anakkallan Subeesh, Nand Lal Kushwaha, Dinesh Kumar Vishwakarma et al. • Artificial Intelligence in Agriculture (2022)

The agriculture industry is undergoing a rapid digital transformation and is growing powerful by the pillars of cutting-edge approaches like artificial intelligence and allied technologies. At the core of artificial intelligence, deep learn...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.aiia.2022.09.007

MaskDis R‐CNN: An instance segmentation algorithm with adversarial network for herd pigs

Shuqin Tu, Qiantao Zeng, Haofeng Liu, Yun Liang et al. • IET Image Processing (2023)

Abstract The current instance segmentation method can achieve satisfactory results in common scenarios. However, under the overlap or partial occlusion between targets caused by the complex scenes, accurate segmentation of pigs remains a ch...

DOAJ Open Access (DOAJ) DOI: 10.1049/ipr2.12880

AutoWindLoc: Precise Localization of Wind Turbines in High-Resolution Orthophotos for Enhanced Registers

J. Middendorf, A. Kelm, S. Frintrop • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2025)

The paper proposes a novel framework for automatically detecting wind turbines in orthophotos, transferring this information to a database, and linking detected turbines to an existing registry to minimize location inaccuracy. This inaccura...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprs-archives-XLVIII-M-7-2025-35-2025

Towards automated metaphase cell detection using foundation models: A SAM and DINO-based approach

M. Cihad Arslanoglu, Abdulkadir Albayrak, Huseyin Acar • Engineering Science and Technology, an International Journal (2026)

Karyotyping is a widely used laboratory technique to detect abnormalities in chromosomes. Karyotyping consists of many steps, including collecting samples, cell culturing and metaphase cell detection. Cytogeneticists examine all the images ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jestch.2025.102262

Deep Learning and Bidirectional Optical Flow Based Viewport Predictions for 360° Video Coding

Jayasingam Adhuran, Gosala Kulupana, Anil Fernando • IEEE Access (2022)

The rapid development of virtual reality applications continues to urge better compression of 360° videos owing to the large volume of content. These videos are typically converted to 2-D formats using various projection techniques i...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2022.3219861

Artifact segmentation using the U-Net architecture for powder X-ray diffraction images

Albert Vong, Howard Yanxon, Eric Roberts, Hannah Parraga et al. • Journal of Synchrotron Radiation (2026)

Modern synchrotron X-ray facilities generate X-ray diffraction (XRD) image data at rates that far exceed the capacity of manual analysis, yet critical processing steps such as artifact removal rely on human intervention. Rule-based algorith...

DOAJ Open Access (DOAJ) DOI: 10.1107/S160057752600754X

Multistage Convolutional Neural Network With Deformable Attention for Word-Level Offline Text-Independent Writer Identification

Manabu Okawa • IEEE Access (2025)

Offline writer identification is an essential component of biometric and forensic security fields, focusing on identifying the authors of handwritten documents in physical form. Historically, this approach has focused on text-dependent iden...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3586994

A Fully Unsupervised Deep Learning Framework for Non-Rigid Fundus Image Registration

Giovana A. Benvenuto, Marilaine Colnago, Maurício A. Dias, Rogério G. Negri et al. • Bioengineering (2022)

In ophthalmology, the registration problem consists of finding a geometric transformation that aligns a pair of images, supporting eye-care specialists who need to record and compare images of the same patient. Considering the registration ...

DOAJ Open Access (DOAJ) DOI: 10.3390/bioengineering9080369

A Deep Learning-Driven Computer Vision and Web-Based Monitoring System for Automated Nutrient Management in Soilless Agriculture

Eda Nur Urtekin, Emre Dandıl • Journal of Agricultural Sciences (2026)

Sustainable food production increasingly relies on intelligent automation technologies that optimize resource usage while maintaining crop health. This study presents a deep learning-driven computer vision and web based monitoring system de...

DOAJ Open Access (DOAJ) DOI: 10.15832/ankutbd.1817471

Convolutional-de-convolutional neural networks for recognition of surgical workflow

Yu-wen Chen, Ju Zhang, Peng Wang, Zheng-yu Hu et al. • Frontiers in Computational Neuroscience (2022)

Computer-assisted surgery (CAS) has occupied an important position in modern surgery, further stimulating the progress of methodology and technology. In recent years, a large number of computer vision-based methods have been widely used in ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fncom.2022.998096