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Architectural Framework to Enhance Image-Based Vehicle Positioning for Advanced Functionalities

Iosif-Alin Beti, Paul-Corneliu Herghelegiu, Constantin-Florin Caruntu • Information (2024)

The growing number of vehicles on the roads has resulted in several challenges, including increased accident rates, fuel consumption, pollution, travel time, and driving stress. However, recent advancements in intelligent vehicle technologi...

DOAJ Open Access (DOAJ) DOI: 10.3390/info15060323

Building neural networks

David M. Skapura (1995)

Foundations. Motivation. Neural-Network Fundamentals. Single Neuron Computations. Network Computations. Network Simulation. Foundations Summary. Suggested Readings. Bibliography. Paradigms. The Backpropagation Network. The Counterpropagatio...

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Dynamic Sign Language Recognition in Bahasa using MediaPipe, Long Short-Term Memory, and Convolutional Neural Network

Ivana Valentina Lemmuela, Mewati Ayub, Oscar Karnalim • Journal of Information Systems Engineering and Business Intelligence (2025)

Background: Communication is important for everyone, including individuals with hearing and speech impairments. For this demographic, sign language is widely used as the primary medium of communication with others who share similar conditio...

DOAJ Open Access (DOAJ) DOI: 10.20473/jisebi.11.1.17-29

Face recognition with Bayesian convolutional networks for robust surveillance systems

Umara Zafar, Mubeen Ghafoor, Tehseen Zia, Ghufran Ahmed et al. • EURASIP Journal on Image and Video Processing (2019)

Abstract Recognition of facial images is one of the most challenging research issues in surveillance systems due to different problems including varying pose, expression, illumination, and resolution. The robustness of recognition method st...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13640-019-0406-y

A review on deep learning in UAV remote sensing

Lucas Prado Osco, José Marcato, Ana Paula Marques Ramos, Lúcio André de Castro Jorge et al. • International Journal of Applied Earth Observation and Geoinformation (2021)

Deep Neural Networks (DNNs) learn representation from data with an impressive capability, and brought important breakthroughs for processing images, time-series, natural language, audio, video, and many others. In the remote sensing field, ...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.jag.2021.102456

An optimized deep learning framework for temporally stable real-time face detection in unconstrained video streams

P. E. Janani Pappu, B. Devanthan • Discover Artificial Intelligence (2026)

Abstract Face detection in real-time video streams remains challenging because of dynamic variations in illumination, pose, motion blur, and partial occlusion. This paper proposes an optimized deep learning framework that integrates YOLOv12...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44163-026-02275-z

Face recognition in dense crowd using deep learning approaches with IP camera

Sobhana Mummaneni, Venkata Chaitanya Satya Ramaraju Mudunuri, Sri Veerabhadra Vikas Bommaganti, Bhavya Vani Kalle et al. • Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska (2025)

A facial recognition system is a biometric security and surveillance system that can identify and monitor individuals in a crowded area. Manually monitoring a crowded environment is a difficult and error-prone task. Therefore, in such conte...

DOAJ Open Access (DOAJ) DOI: 10.35784/iapgos.6818

Multimodal artificial intelligence for subepithelial lesion classification and characterization: a multicenter comparative study (with video)

Jiao Li, Xiaojuan Jing, Qin Zhang, Xiaoxiang Wang et al. • BMC Medical Informatics and Decision Making (2025)

Abstract Background Subepithelial lesions (SELs) present significant diagnostic challenges in gastrointestinal endoscopy, particularly in differentiating malignant types, such as gastrointestinal stromal tumors (GISTs) and neuroendocrine tu...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12911-025-03147-9

A System for the Detection of Polyphonic Sound on a University Campus Based on CapsNet-RNN

Liyan Luo, Liujun Zhang, Mei Wang, Zhenghong Liu et al. • IEEE Access (2021)

In recent decades, surveillance and home security systems based on video analysis have been proposed for the automatic detection of abnormal situations. Nevertheless, in several real applications, it may be easier to detect a given event fr...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2021.3123970

A Review on Conventional Machine Learning vs Deep Learning

Nitin Kumar Chauhan, Krishna Pal Singh • International Conference on Computing, Power and Communication Technologies (GUCON) (2018)

In now days, deep learning has become a prominent and emerging research area in computer vision applications. Deep learning permits the multiple layers models for computation to learn representations of data by processing in their original ...

OPENALEX DOI: https://doi.org/10.1109/gucon.2018.8675097

Deep learning-enabled medical computer vision

Andre Esteva, Katherine Chou, Serena Y. Yeung, Nikhil Naik et al. • npj Digital Medicine (2021)

A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the potential for many fields-including medicine-to benefit from the insights that AI techniques can extract from data. Here we survey recent progress in th...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41746-020-00376-2 PMC: 7794558

Multimodal Deep Learning

Jiquan Ngiam, Aditya Khosla, Mingyu Kim, Juhan Nam et al. (2011)

Deep networks have been successfully applied to unsupervised feature learning for single modalities (e.g., text, images or audio). In this work, we propose a novel application of deep networks to learn features over multiple modalities. We ...

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Deep Learning for Video Game Playing

Niels Justesen, Philip Bontrager, Julian Togelius, Sebastian Risi • IEEE Transactions on Games (2019)

In this paper, we review recent deep learning advances in the context of how they have been applied to play different types of video games such as first-person shooters, arcade games, and real-time strategy games. We analyze the unique requ...

OPENALEX Open Access DOI: https://doi.org/10.1109/tg.2019.2896986

Image Segmentation Using Deep Learning: A Survey

Shervin Minaee, Yuri Y. Boykov, Fatih Porikli, Antonio Plaza et al. • IEEE Transactions on Pattern Analysis and Machine Intelligence (2021)

Image segmentation is a key task in computer vision and image processing with important applications such as scene understanding, medical image analysis, robotic perception, video surveillance, augmented reality, and image compression, amon...

OPENALEX Open Access DOI: https://doi.org/10.1109/tpami.2021.3059968

Deep learning as a tool for ecology and evolution

Marek L. Borowiec, Rebecca B. Dikow, Paul B. Frandsen, Alexander J. McKeeken et al. • Methods in Ecology and Evolution (2022)

Abstract Deep learning is driving recent advances behind many everyday technologies, including speech and image recognition, natural language processing and autonomous driving. It is also gaining popularity in biology, where it has been use...

OPENALEX cc-by-nc DOI: https://doi.org/10.1111/2041-210x.13901

Downscaling atmospheric chemistry simulations with physically consistent deep learning

A. Geiss, S. J. Silva, S. J. Silva, J. C. Hardin et al. • Geoscientific Model Development (2022)

Recent advances in deep convolutional neural network (CNN)-based super resolution can be used to downscale atmospheric chemistry simulations with substantially higher accuracy than conventional downscaling methods. This work both demonstrat...

DOAJ Open Access (DOAJ) DOI: 10.5194/gmd-15-6677-2022

A Comparison of Two Neural Network Based Methods for Human Activity Recognition

saeedeh zebhi, Seyed Mohammad Taghi AlModaressi, Vahid Abootalebi • AUT Journal of Electrical Engineering (2021)

In this paper, two different methods of human activity recognition based on video signals are introduced. The first method explores the effectiveness of combining feature descriptors obtained by local descriptors and artificial neural network ...

DOAJ Open Access (DOAJ) DOI: 10.22060/eej.2020.18517.5357