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Reliable Parkinson’s Disease Detection by Analyzing Handwritten Drawings: Construction of an Unbiased Cascaded Learning System Based on Feature Selection and Adaptive Boosting Model

Liaqat Ali, Ce Zhu, Noorbakhsh Amiri Golilarz, Ashir Javeed et al. • IEEE Access (2019)

Parkinson's disease (PD) is the second most common neurodegenerative disease of central nervous system (CNS). Till now, there is no definitive clinical examination that can diagnose a PD patient. However, it has been reported that PD patien...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2019.2932037

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

Adversarial Attack on Object Detection via Object Feature-Wise Attention and Perturbation Extraction

Wei Xue, Xiaoyan Xia, Pengcheng Wan, Ping Zhong et al. • Tsinghua Science and Technology (2025)

Deep neural networks are commonly used in computer vision tasks, but they are vulnerable to adversarial samples, resulting in poor recognition accuracy. Although traditional algorithms that craft adversarial samples have been effective in a...

DOAJ Open Access (DOAJ) DOI: 10.26599/TST.2024.9010029

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

SnowMapPy: An automated GEE Python tool for snow cover mapping and monitoring in the Moroccan Atlas Mountains

Haytam Elyoussfi, Hatim Bechri, Mostafa Bousbaa, Salwa Belaqziz et al. • SoftwareX (2026)

SnowMapPy is an open-source Python-based package developed to streamline the collection, processing, and analysis of MODIS snow cover data from Terra and Aqua satellites. By automating essential steps, including data clipping, reprojection,...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.softx.2026.103006

Problems In Indoor Mapping and Modelling

S. Zlatanova, G. Sithole, M. Nakagawa, Q. Zhu • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2013)

Research in support of indoor mapping and modelling (IMM) has been active for over thirty years. This research has come in the form of As-Built surveys, Data structuring, Visualisation techniques, Navigation models and so forth. Much of thi...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprsarchives-XL-4-W4-63-2013

Florence: A New Foundation Model for Computer Vision

Lu Yuan, Dongdong Chen, Yi‐Ling Chen, Noel Codella et al. • arXiv (Cornell University) (2021)

Automated visual understanding of our diverse and open world demands computer vision models to generalize well with minimal customization for specific tasks, similar to human vision. Computer vision foundation models, which are trained on d...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.2111.11432

Evaluating Adversarial Robustness of No-Reference Image and Video Quality Assessment Models with Frequency-Masked Gradient Orthogonalization Adversarial Attack

Khaled Abud, Sergey Lavrushkin, Dmitry Vatolin • Big Data and Cognitive Computing (2025)

Neural-network-based models have made considerable progress in many computer vision areas over recent years. However, many works have exposed their vulnerability to malicious input data manipulation—that is, to adversarial attacks. Although...

DOAJ Open Access (DOAJ) DOI: 10.3390/bdcc9070166

Evaluation of Modified FGSM-Based Data Augmentation Method for Convolutional Neural Network-Based Image Classification

Paulo Monteiro de Carvalho Monson, Vinicius Augusto Dare de Almeida, Gabriel Augusto David, Pedro Oliveira Conceição Junior et al. • Engineering Proceedings (2024)

Computer vision applications demand a significant amount of data for effective training and inference in many computer vision tasks. However, data insufficiency situations usually happen due to multiple reasons, resulting in computational m...

DOAJ Open Access (DOAJ) DOI: 10.3390/ecsa-11-20476

Knowledge, attitude, and practice among kindergarten teachers regarding vision and eye screening of preschool children

Dora Hamad S. AlHarkan • Oman Journal of Ophthalmology (2024)

PURPOSE To estimate the level and determinants of knowledge, attitude, and practices (KAPs) of kindergarten teachers regarding vision and eye screening of preschool children of Qassim region of Saudi Arabia. METHODS As a part of a study to ...

DOAJ Open Access (DOAJ) DOI: 10.4103/ojo.ojo_260_23

Deep Learning for Understanding Satellite Imagery: An Experimental Survey

Sharada Prasanna Mohanty, Jakub Czakon, Kamil A. Kaczmarek, Kamil A. Kaczmarek et al. • Frontiers in Artificial Intelligence (2020)

Translating satellite imagery into maps requires intensive effort and time, especially leading to inaccurate maps of the affected regions during disaster and conflict. The combination of availability of recent datasets and advances in compu...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2020.534696

A COMPARATIVE STUDY ON REINFORCEMENT LEARNING BASED VISUAL DIALOG SYSTEMS

Mostafa Aref, Ghada Elshamy, Marco Alfonse, Islam Hegazy • International Journal of Intelligent Computing and Information Sciences (2024)

Recently the conjunction between vision and language has created many intersecting tasks as visual question-answering systems, image captioning, etc. Specifically, dialog systems that depend on a visual scene play an important role in impro...

DOAJ Open Access (DOAJ) DOI: 10.21608/ijicis.2024.295310.1339

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

AI and Chatbot-Supported Interventions for Physical Activity and Obesity-Related Lifestyle Behaviors: Scoping Review With Attention to Family Involvement

Qianxia Jiang, Xiayu Summer Chen, Dev Patel, Keith Brazendale et al. • JMIR Pediatrics and Parenting (2026)

Abstract BackgroundAI-enabled chatbots and related conversational systems can facilitate human–computer interaction through natural language, personalization, and automated support. In pediatric health promotion, these tools hav...

DOAJ Open Access (DOAJ) DOI: 10.2196/98889