Exploring the World of Computer Science: Research, Innovation, and Opportunity
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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.
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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.
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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.
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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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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
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
Javier Del Ser,
Javier Del Ser
TECNALIA, Basque Research and Technology Alliance (BRTA)
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
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
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
Rui Zhu,
Rui Zhu
a Faculty of Actuarial Science and Insurance, Bayes Business School, City
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
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
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
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
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
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