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Computer science

Exploring the World of Computer Science: Research, Innovation, and Opportunity

Register to submit your paper, and Start Earning from your Research Articles

Computer science is more than just a high-demand career path — it's a rapidly evolving field shaping the future of everything from healthcare to entertainment. Whether you're new to the discipline or a seasoned computer scientist, the opportunities for exploration and contribution are endless. Our platform welcomes original, non-peer-reviewed articles in computer science and related areas — and now, we’re offering free publication with monetization opportunities for contributors.

A Platform for Sharing Ideas and Insights

We aim to create a space where researchers, students, and enthusiasts can share their insights into topics ranging from artificial intelligence and cyber security to theoretical computer science and scientific computing. Whether you're diving into a new comp sci course, exploring mathematics for computer science, or conducting cs research, your voice matters — and we’d love to amplify it.

While we don’t offer computer science degrees, online computer science programs, or a bachelor’s in computer science, we provide a valuable outlet for those engaged in the field to share their perspectives and discoveries.

Your Experience is Worth Sharing

Whether you're pursuing a bs in computer science, working toward an msc computer science, enrolled in an online cs degree, or even completing a phd in computer science, you still have something valuable to contribute. Regardless of your academic path — from an associate degree to a doctorate — your perspective, research, or experience can help shape the conversation and inspire others in the computer science community.

Diverse Topics, Real Impact

Some of our most engaging submissions come from authors who have explored specific educational journeys, such as attending a computer science university or navigating an online master’s in computer science. Others dive into trending topics like ai computer scientist ethics, forensic computer applications, or the role of computer science in human behavior.

Writers often review essential tools like the best laptops for cs students, share insights about computer science programming, or discuss the experiences of being a female computer scientist. Every article contributes to a wider understanding of what it means to study and work in the field today.

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By sharing your work, you’re not only building your own portfolio — you’re contributing to a global dialogue. Your article can live alongside discussions of cs games, comp sci major experiences, or insights drawn from communities like computer science reddit. Whether you're taking intro to cs or exploring advanced topics like computer science and cyber security, your voice has value.

Submit your article today, share your knowledge, and monetize your voice. Let’s advance the field of computer science — together.


Computer Science Articles

Physics Maths Engineering

Flood-Related Multimedia Benchmark Evaluation: Challenges, Results and a Novel GNN Approach

Ilias Gialampoukidis,

Ilias Gialampoukidis

Information Technologies Institute, Centre for Research and Technology Hellas

heliasgj@iti.gr

Thomas Papadimos,

Thomas Papadimos

Information Technologies Institute, Centre for Research and Technology Hellas

info@rnfinity.com

Stelios Andreadis,

Stelios Andreadis

Information Technologies Institute, Centre for Research and Technology Hellas

info@rnfinity.com

Stefanos Vrochidis,

Stefanos Vrochidis

Information Technologies Institute, Centre for Research and Technology Hellas

info@rnfinity.com

Ioannis Kompatsiaris

Ioannis Kompatsiaris

Information Technologies Institute, Centre for Research and Technology Hellas

info@rnfinity.com


This paper discusses the importance of detecting breaking events in real time to help emergency response workers, and how social media can be used to process large amounts of data quickly. Most event detection techniques have focused on either images or text, but combining the two can improve performance. The authors present lessons learned from the Flood-related multimedia task in MediaEval2020, ...
2 years ago

Physics Maths Engineering

Panchromatic and multispectral image fusion for remote sensing and earth observation: Concepts, taxonomy, literature review, evaluation methodologies and challenges ahead

Kai Zhang,

Kai Zhang

School of Information Science and Engineering

zhangkainuc@sdnu.edu.cn

Feng Zhang,

Feng Zhang

School of Information Science and Engineering

2019010100@stu.sdnu.edu.cn

Wenbo Wan,

Wenbo Wan

School of Information Science and Engineering

wanwenbo@sdnu.edu.cn

Hui Yu,

Hui Yu

School of Creative Technologies

hui.yu@port.ac.uk

Jiande Sun,

Jiande Sun

School of Information Science and Engineering

jiandesun@sdnu.edu.cn

Javier Del Ser,

Javier Del Ser

TECNALIA, Basque Research and Technology Alliance (BRTA)

info@rnfinity.com

Eyad Elyan

Eyad Elyan

School of Computing

info@rnfinity.com


Panchromatic and multispectral image fusion, termed pan-sharpening, is to merge the spatial and spectral information of the source images into a fused one, which has a higher spatial and spectral resolution and is more reliable for downstream tasks compared with any of the source images. It has been widely applied to image interpretation and pre-processing of various applications. A large number o...
2 years ago

Physics Maths Engineering

A multi-strategy contrastive learning framework for weakly supervised semantic segmentation

Hui Fang,

Hui Fang

Loughborough University, UK

H.Fang@lboro.ac.uk

Kunhao Yuan,

Kunhao Yuan

Loughborough University, UK

info@rnfinity.com

Gerald Schaefer,

Gerald Schaefer

Loughborough University, UK

info@rnfinity.com

Yu-Kun Lai,

Yu-Kun Lai

Cardiff University, UK

info@rnfinity.com

Yifan Wang,

Yifan Wang

Loughborough University, UK

info@rnfinity.com

Xiyao Liu

Xiyao Liu

Central South University, China

info@rnfinity.com


Weakly supervised semantic segmentation (WSSS) has gained significant popularity as it relies only on weak labels such as image level annotations rather than the pixel level annotations required by supervised semantic segmentation (SSS) methods. Despite drastically reduced annotation costs, typical feature representations learned from WSSS are only representative of some salient parts of objects a...
2 years ago

Physics Maths Engineering

Feature weighting in DBSCAN using reverse nearest neighbours

Stiphen Chowdhury,

Stiphen Chowdhury

School of Computing and Information Science

stiphen.chowdhury@aru.ac.uk

Na Helian,

Na Helian

Department of Computer Science

n.helian@herts.ac.uk

Renato Cordeiro de Amorim

Renato Cordeiro de Amorim

School of Computer Science and Electronic Engineering

r.amorim@essex.ac.uk


DBSCAN is arguably the most popular density-based clustering algorithm, and it is capable of recovering non-spherical clusters. One of its main weaknesses is that it treats all features equally. In this paper, we propose a density-based clustering algorithm capable of calculating feature weights representing the degree of relevance of each feature, which takes the density structure of the data int...
2 years ago

Physics Maths Engineering

Statistical hypothesis testing as a novel perspective of pooling for image quality assessment

Rui Zhu,

Rui Zhu

a Faculty of Actuarial Science and Insurance, Bayes Business School, City

info@rnfinity.com

Fei Zhou,

Fei Zhou

College of Information Engineering

info@rnfinity.com

Wenming Yang

Wenming Yang

Department of Electronic Engineering, Graduate School at Shenzhen

info@rnfinity.com


Image quality assessment is usually achieved by pooling local quality scores. However, commonly used pooling strategies, based on simple sample statistics, are not always sensitive to distortions. In this short communication, we propose a novel perspective of pooling: reliable pooling through statistical hypothesis testing, which enables effective detection of subtle changes of population paramete...
2 years ago

Physics Maths Engineering

Arbitrary Order Total Variation for Deformable Image Registration

Jinming Duan,

Jinming Duan

School of Computer Science

j.duan@bham.ac.uk

Xi Jia,

Xi Jia

School of Computer Science

info@rnfinity.com

Joseph Bartlett,

Joseph Bartlett

School of Computer Science

info@rnfinity.com

Wenqi Lu

Wenqi Lu

Tissue Image Analytics Centre, Department of Computer Science

info@rnfinity.com


In this work, we investigate image registration in a variational framework and focus on regularization generality and solver efficiency. We first propose a variational model combining the state-of-the-art sum of absolute differences (SAD) and a new arbitrary order total variation regularization term. The main advantage is that this variational model preserves discontinuities in the resultant defor...
2 years ago

Physics Maths Engineering

Utilizing support vector and kernel ridge regression methods in spectral reconstruction

Seyed Hossein Amirshahi,

Seyed Hossein Amirshahi

Amirkabir University of Technology (Tehran Polytechnic), School of Material Engineering and Advanced Processes

hamirsha@aut.ac.ir

Ida Rezaei,

Ida Rezaei

Amirkabir University of Technology (Tehran Polytechnic), School of Material Engineering and Advanced Processes

info@rnfinity.com

Ali Akbar Mahbadi

Ali Akbar Mahbadi

Amirkabir University of Technology (Tehran Polytechnic), School of Material Engineering and Advanced Processes

info@rnfinity.com


Two regression methods, namely, Support Vector Regression (SVR) and Kernel Ridge Regression (KRR), are used to reconstruct the spectral reflectance curves of samples of Munsell dataset from the corresponding CIE XYZ tristimulus values. To this end, half of the samples (i.e., the odd ones) were used as training set while the even samples left out for the evaluation of reconstruction performances. R...
2 years ago

Physics Maths Engineering

Object tracking and detection techniques under GANN threats: A systemic review

Saeed Matar Al Jaber,

Saeed Matar Al Jaber

School of Digital Technologies and Arts

a030340i@student.staffs.ac.uk

Asma Patel

Asma Patel

School of Digital Technologies and Arts

asma.patel@staffs.ac.uk


Current developments in object tracking and detection techniques have directed remarkable improvements in distinguishing attacks and adversaries. Nevertheless, adversarial attacks, intrusions, and manipulation of images/ videos threaten video surveillance systems and other object-tracking applications. Generative adversarial neural networks (GANNs) are widely used image processing and object detec...
2 years ago

Physics Maths Engineering

Elucidating robust learning with uncertainty-aware corruption pattern estimation

Jeongeun Park,

Jeongeun Park

Department of Artificial Intelligence

baro0906@korea.ac.kr

Seungyoun Shin,

Seungyoun Shin

Department Computer Engineering

info@rnfinity.com

Sangheum Hwang

Sangheum Hwang

Department of Data Science, Seoul National University of Science and Technology

info@rnfinity.com


Robust learning methods aim to learn a clean target distribution from noisy and corrupted training data where a specific corruption pattern is often assumed a priori. Our proposed method can not only successfully learn the clean target distribution from a dirty dataset but also can estimate the underlying noise pattern. To this end, we leverage a mixture-of-experts model that can distinguish two d...
2 years ago

Physics Maths Engineering

Poisson PCA for matrix count data

Joni Virta

Joni Virta

Department of Mathematics and Statistics

joni.virta@utu.fi


We develop a dimension reduction framework for data consisting of matrices of counts. Our model is based on the assumption of existence of a small amount of independent normal latent variables that drive the dependency structure of the observed data, and can be seen as the exact discrete analogue of a contaminated low-rank matrix normal model. We derive estimators for the model parameters and esta...
2 years ago

Related Subjects

Physics Math Chemistry Engineering Earth science Biology

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