Posts

๐Ÿšข The Impact of Starlink on Maritime Cybersecurity: A Necessary Investment for the Future

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For decades, maritime vessels operated with limited and slow satellite communications , making them less attractive targets for cyberattacks . However, with the introduction of Starlink , ships now have access to high-speed, low-latency internet , transforming them into fully connected digital platforms . While this advancement brings enormous benefits in operational efficiency, it also exposes vessels to unprecedented cybersecurity risks .  SpaceX Debuts Maritime Offering for Starlink As the shipping industry embraces Starlink-powered connectivity , investing in cybersecurity has become a necessity, not an option . This article explores the growing cyber threats faced by ships due to Starlink and how businesses should strategically invest in security measures to mitigate these risks. ๐ŸŒŠ 1. How Starlink is Changing the Cybersecurity Landscape for Ships Traditionally, ships relied on expensive and slow VSAT (Very Small Aperture Terminal) or Inmarsat satellite connections , which...

"Recommender System" (1) Curriculum

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I would like to organize and document the learning curriculum and key research papers of interest for the Recommender System course that I am taking in the final semester of my Ph.D. program. Goals of this Course Collaborative Filtering (CF) A recommendation approach based on user behavior . Neighborhood-based Collaborative Filtering (CF) A method that recommends items based on similarities between users or items . User-based Collaborative Filtering (User-based CF) Recommends items based on similarities between users . Users with similar preferences or behaviors receive similar recommendations. Item-based Collaborative Filtering (Item-based CF) Recommends items based on similarities between items . Items that have been interacted with in a similar way are recommended together

The Importance of Having Personal Principles in Organizational Life

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 I have come to As the first step, I am recording my personal conclusions on the issues I have contemplated over the past month. [Relational Aspects] I do not strive to become someone else in order to be remembered as a good person in the organization. I am who I am. Work-related matters should be discussed in meetings where all relevant team members (or stakeholders) are present. Even if someone feels uncomfortable or is being held accountable, I will not avoid the situation. Instead, I will share the facts accurately and discuss solutions together to foster future growth and stronger relationships. When I recognize actions that go against basic common sense, I will focus on identifying the fundamental issue rather than getting caught up in others’ emotions. I do not indiscriminately offer consideration, comfort, or reprimands to others. I focus solely on facts and do not convey my emotions in judgment. The driving force of my 30s— “An eye for an eye, a tooth for a tooth” ...

"GNN (Graph Neural Network) ML Learning" (1) Curriculum - Approach

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Shifting Perceptions and Expectations of AI from Companies The way companies perceive and expect from AI is evolving. Until now, aside from cutting-edge research and product development , the role of AI engineers and data scientists in enterprises can generally be categorized as follows: Image Processing : Companies have widely utilized CNN-based models for object recognition and comparison (performance improvement). To overcome data scarcity, techniques like few-shot learning have been applied in areas such as product search, similar image/product recommendation, and design generation . Text Processing : Enterprises have leveraged various Transformer-based models trained on proprietary datasets for customer intent recognition and sentiment analysis . Data-Driven Decision Support : Companies often assume they possess sufficient data, but in many cases, they lack the necessary datasets. AI teams analyze available data, form hypotheses , and generate insightful reports to support an...

(ICML 2019) EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

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EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks EfficientNet is a highly influential paper that has gained significant attention in the field of image classification due to its outstanding performance . For projects requiring extensive training time or computational resources , EfficientNet serves as a valuable approach to enhancing ConvNet performance . It provides an efficient and scalable method for training convolutional neural networks while optimizing accuracy and computational cost, making it highly applicable for real-world AI deployment . ๐Ÿ”— Research Paper: EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks ๐Ÿ“Œ Key Resources & Reviews ๐Ÿ“– Paper Review Summaries: Bellzero’s Review Laonple Blog Review ๐Ÿ’ป Source Code (PyTorch Implementation): GitHub: EfficientNet-PyTorch  

(Environment) (Cairo) – (1) Installing Required Libraries to Convert SVG Files to PNG

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Installing Required Libraries to Convert SVG Files to PNG The goal was to apply NBP OCR to SVG images and record the output as JSON (text, coordinates) . To achieve this, the first step was to convert the ".svg" file into ".png" . Initially, I thought that simply installing cairo via pip would suffice, but I soon realized that additional steps were necessary . To avoid wasting time solving issues when I attempted it again later, I decided to document the process and share it . If you need code references or encounter any setup issues, please feel free to leave a message here: https://github.com/shipjobs/HAND2TEXT/issues . Environment Language: Python 3.8.3 64bit Operating System: Windows 10 Development Environment: Visual Studio Code To convert an ".svg" file to ".png" , if you import the libraries as shown below, you will naturally encounter a reference error : import  cairo  from  svglib.svglib  import  svg2rlg  import  cairosvg For those...

(Cloud) NCP > AI Service > OCR review

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CLOVA OCR (optical character reader) Service review ๋ฌธ์„œ๋ฅผ ์ธ์‹ํ•˜๊ณ , ์‚ฌ์šฉ์ž๊ฐ€ ์ง€์ •ํ•œ ์˜์—ญ์˜ ํ…์ŠคํŠธ์™€ ๋ฐ์ดํ„ฐ๋ฅผ ์ •ํ™•ํ•˜๊ฒŒ ์ถ”์ถœ CLOVA OCR (๊ด‘ํ•™๋ฌธ์ž์ธ์‹) ์„ ํ•œ๋ฒˆ ์‚ฌ์šฉํ•ด ๋ณธ๋‹ค๋ฉด, NCP๊ฐ€ ์ œ๊ณต ์ค‘์— ์žˆ๋Š” AI Service ๋“ค ์— ๋Œ€ํ•˜์—ฌ ๋ณด๋‹ค ์‰ฌ์šด ์ ‘๊ทผ์ด ๊ฐ€๋Šฅํ•ด์งˆ ๊ฑฐ๋ผ ์ƒ๊ฐ ํ•˜๊ฒŒ ๋˜์–ด review ๋ฅผ ํ•ด๋ณด๊ณ ์ž ํ•ฉ๋‹ˆ๋‹ค. [์ ‘๊ทผ] Products & service : https://console.ncloud.com/dashboard OCR Service ๊ฒฝ๋กœ : Classic / CLOVA OCR / Domain [์ด์šฉ ๋ฐฉ์‹] ์„œ๋น„์Šค ํƒ€์ž… General / Template / Document ์„ ํƒ์— ๋”ฐ๋ผ Text OCR / ํ…œํ”Œ๋ฆฟ ๋นŒ๋” / Document ๋ฒ„ํŠผ์ด ๋…ธ์ถœ๋˜๋Š” ํ˜•์‹์œผ๋กœ ์„œ๋น„์Šค๋ฅผ ์„ค์ •ํ•จ  Text OCR (ํ…์ŠคํŠธ๋งŒ ์ถ”์ถœ)  ๊ณผ Template ๋นŒ๋” ํ˜•ํƒœ (ํŒ๋… ์˜์—ญ ์ง์ ‘ ์ง€์ •์„ ํ†ตํ•ด ์ธ์‹ ๊ฐ’ ์ถ”์ถœ ํ›„ ํ…Œ์ŠคํŠธ ๋ฐ ๊ฒฐ๊ณผ ์ „์†ก์ด ๊ฐ€๋Šฅ) ๋Š” ์„œ๋น„์Šค ํƒ€์ž…์— ๋”ฐ๋ผ ์•„๋ž˜์˜ 2๊ฐ€์ง€ ๋ฐฉ์‹์ด ์žˆ์œผ๋ฉฐ 1. General OCR : ์šฐ๋ฆฌ๊ฐ€ ์ผ๋ฐ˜์ ์œผ๋กœ ์ƒ๊ฐํ•˜๋Š” png, jpg์ด๋ฏธ์ง€ ํ˜น์€ pdf ์— ์กด์žฌํ•˜๋Š” text ๋“ค์„ ๋ชจ๋‘ ์ฝ์–ด ์˜ค๊ณ ์ž ํ•˜๋Š” ๋ฐฉ์‹ 2. Template OCR : ์šด์ „ ๋ฉดํ—ˆ์ฆ, ์‹ ์šฉ ์นด๋“œ, ์ฃผ๋ฏผ ๋“ฑ๋ก ๋“ฑ๋ณธ ์ด๋ฏธ์ง€ ๋“ฑ ์ด๋ฏธ์ง€๋‚ด ์ •ํ•ด์ง„ ํŠน์ • ์˜์—ญ์„ ๊ธฐ์ค€์œผ๋กœ text ๋“ค์„ ์ฝ์–ด ์˜ค๋Š” ๋ฐฉ์‹ Document ๋ฐฉ์‹์€ ๋จธ์‹ ๋Ÿฌ๋‹ ๊ธฐ๋ฐ˜์œผ๋กœ ๋ฌธ์„œ์˜ ์˜๋ฏธ์  ๊ตฌ์กฐ๋ฅผ ์ดํ•ดํ•˜๋Š” ํŠนํ™” ๋ชจ๋ธ ์—”์ง„์„ ํƒ‘์žฌํ•˜์—ฌ ์ž…๋ ฅ ์ •๋ณด(key-value)๋ฅผ ์ž๋™ ์ถ”์ถœํ•˜๋Š” ๋ฐฉ์‹ ์ธ์‹ ๋ชจ๋ธ๋กœ๋Š” ๋ฏธ๋ฆฌ ์ •ํ•ด์ง„ ์‚ฌ์—…์ž ๋“ฑ๋ก์ฆ, ์‹ ์šฉ์นด๋“œ,์˜์ˆ˜์ฆ, ์‹ ๋ถ„์ฆ, ๋ช…ํ•จ์ด ์ œ๊ณต ๋˜๋ฉฐ ์ด๋ฅผ ์„ ํƒํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค. [์ด๋Ÿฌํ•œ Type ๋ณ„ ์„œ๋น„์Šค๋ฅผ ์ด์šฉํ•˜๋Š” ๋ฐฉ๋ฒ• ๋˜ํ•œ 2๊ฐ€์ง€๋กœ ๊ตฌ๋ถ„ ๋  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.] 1. NCP OCR ์‚ฌ์ดํŠธ์— ์ ‘์†ํ•ด์„œ ์ œ๊ณต๋˜๋Š” UI ํ™”๋ฉด์œผ๋กœ ์ ‘๊ทผ ํ•˜๋Š” ๋ฐฉ์‹์œผ๋กœ ์›ํ•˜๋Š” ์ด๋ฏธ์ง€ ํŒŒ์ผ์„ drag and drop์œผ๋กœ ๋“ฑ๋กํ•˜๊ณ  ํ…...

(CVPR 2019) A Style-Based Generator Architecture for Generative Adversarial Networks

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  StyleGAN — Official TensorFlow Implementation Material related to our paper is available via the following links: Paper:  https://arxiv.org/abs/1812.04948 Video:  https://youtu.be/kSLJriaOumA Code:  https://github.com/NVlabs/stylegan FFHQ:  https://github.com/NVlabs/ffhq-dataset Additional material can be found on Google Drive:

(NeurIPS 2020) Dynamic allocation of limited memory resources in reinforcement learning

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Dynamic allocation of limited memory resources in reinforcement learning

(CVPR 2020 (Best Paper Award).) Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild

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 Unsupervised Learning of Probably Symmetric Deformable 3D Objects  from Images in the Wild Shangzhe Wu Christian Rupprecht Andrea Vedaldi Visual Geometry Group, University of Oxford {szwu, chrisr, vedaldi}@robots.ox.ac.uk

(Research) AI Blink Detection and Reminder (1) – Project Introduction

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[Open Source + Research Paper + Jetson Nano] Blinker Project This project aims to implement a blink detection system using dlib and OpenCV , following an existing open-source implementation. It builds upon facial recognition techniques to develop a system capable of detecting eye blinks in real-time. According to the contributor's description , this system can be applied in various scenarios, such as: ๐Ÿš— Drowsy driving detection – Alerting drivers when signs of fatigue are detected. ๐Ÿ“š Student monitoring – Analyzing drowsiness and focus levels in study environments. By leveraging Jetson Nano , this project explores the integration of edge AI for real-time blink detection, opening possibilities for applications in safety, education, and human-computer interaction . ๐Ÿš€ asily Implementable with a Camera and Software Development Setup If you have a camera and a properly configured software development environment , this project is relatively easy to implement. In this project, we...

(Research) Face Recognition (1) – Project Introduction

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Let's explore the Face Recognition Project ! ๐Ÿ˜Š In this project, we will maximize the use of open-source resources with the following objectives: 1️⃣ Understand key libraries and source code 2️⃣ Set up the required development environment 3️⃣ Optimize performance for better accuracy and efficiency 4️⃣ Share results and discuss potential improvements The goal is to go beyond simple implementation , actively improving the system and exploring ways to enhance its capabilities. ๐Ÿš€

(ISSN 2249-3905) Natural Language Processing: A Review

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ABSTRACT  1. Introduction  2. Scope and objective  3. Previous Works On NLP (Brief History)  4. Natural Language Processing Overview  5. Applications of NLP  6. Challenges and failures  7. Current and Future progress of NLP  8. Conclusions  References 

THE BEST ARTIFICIAL INTELLIGENCE JOURNALS

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THE BEST ARTIFICIAL INTELLIGENCE  JOURNALS ์•ˆ๋…•ํ•˜์„ธ์š”?  ์—ฐ๊ตฌ ํ™œ๋™ ๋ฐ ํ•™์œ„ ์ทจ๋“์˜ ๋ชฉ์ , ๊ทธ๋ฆฌ๊ณ  ๊ธฐ์—…์— ์†Œ์†๋˜์–ด ๋…ผ๋ฌธ ๋“ฑ์žฌ๋ฅผ ์‹œ์ž‘ํ•ด ๋ณด๋ ค๋Š” ์ด๋“ค์—๊ฒŒ ๋„์›€์ด ๋  ๋งŒํ•œ ๋‚ด์šฉ์„ ์ •๋ฆฌํ•ด ๋ณด๊ณ ์ž ํ•ฉ๋‹ˆ๋‹ค.. ์ธ๊ณต์ง€๋Šฅ ํ•™๋ฌธ์— ๋Œ€ํ•˜์—ฌ ์—ฐ๊ตฌ์ž ๋ฐ ์—”์ง€๋‹ˆ์–ด๋“ค์ด ๋ชจ์ด๋Š” ํ•™ํšŒ๋Š” ์–ด๋–ค๊ฒƒ๋“ค์ด ์žˆ์œผ๋ฉฐ ๊ฐ ํ•™ํšŒ์˜ ์—ญ์‚ฌ๋‚˜ ํŠน์ง•, ๋™ํ–ฅ์ด ๊ถ๊ธˆํ•ด ์กŒ๊ธฐ ๋•Œ๋ฌธ ์ž…๋‹ˆ๋‹ค. ์›ํ•˜๋Š” ๋…ผ๋ฌธ์˜ ํƒ์ƒ‰์€ ๊ตฌ๊ธ€๊ฒ€์ƒ‰์ด๋‚˜ "http://www.arxiv-sanity.com/" ์„ ํ†ตํ•˜๋ฉด ์‰ฝ๊ฒŒ ์–ป์„ ์ˆ˜์žˆ๊ฒ ์ง€๋งŒ, ๊ฐ ํ•™ํšŒ๋ณ„ ํŠน์ง•์ด๋‚˜ ๋™ํ–ฅ์„ ์•„๋Š” ๊ฒƒ์ด ์šฐ๋ฆฌ์˜ ๋…ผ๋ฌธ ๋“ฑ์žฌ๋ฅผ ํฌํ•จํ•œ ์—ฐ๊ตฌ ํ™œ๋™์— ๋„์›€์ด ๋ ๊ฒƒ์ด๋ผ ์ƒ๊ฐ ํ•˜๊ธฐ์— ๊ทธ ๋‚ด์šฉ์„ ์ •๋ฆฌํ•จ๊ณผ ๋™์‹œ์— ๊ณผ์ •์„ ์ง€์†์ ์œผ๋กœ ๊ณต์œ ํ•ด ๋‚˜๊ฐ€๊ณ ์ž ํ•ฉ๋‹ˆ๋‹ค. 1. NeurIPS   (NIPS)     : ์—ฐ๊ตฌ์ž ๋ฐ ์—”์ง€๋‹ˆ์–ด๊ฐ€ ๋ชจ์ด๋Š” ์ตœ๋Œ€ ๊ทœ๋ชจ์˜ ์—ฐ๋ก€ ํ•™ํšŒ๋กœ , ์ƒˆ๋กœ์šด ๋ฐœ๊ฒฌ์„ ๊ณต์œ ํ•˜๊ณ  ํ˜‘์—…ํ•˜๋ฉฐ ํ•จ๊ป˜ AI ์‚ฐ์—… ๋ฐœ์ „์„ ๋„๋ชจํ•˜๋Š” ์žฅ     : ์—ญ์‚ฌ : 1987 ๋…„ , ๋ถ„์•ผ : ์ธ์ง€ ๊ณผํ•™๊ณผ ๋จธ์‹ ๋Ÿฌ๋‹ ์‘์šฉ ๋ถ„์•ผ ๋“ฑ ํญ ๋„“์Œ     ; ๋ฐ”๋กœ๊ฐ€๊ธฐ:    https://papers.nips.cc/  2. ICML : (International Conference on Machine Learning)     : ๋จธ์‹  ๋Ÿฌ๋‹์— ์ง‘์ค‘,  NeurIPS  ๋ฐ  ICLR  ๊ณผ ํ•จ๊ป˜  ๊ธฐ๊ณ„ ํ•™์Šต  ๋ฐ  ์ธ๊ณต ์ง€๋Šฅ  ์—ฐ๊ตฌ  ์— ํฐ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์„ธ          ๊ฐ€์ง€ ์ฃผ์š” ์ปจํผ๋Ÿฐ์Šค ์ค‘ ํ•˜๋‚˜ , ์ •ํ™•ํ•œ ๋‚ ์งœ๋Š” ํ•ด๋งˆ๋‹ค ๋‹ค๋ฅด์ง€๋งŒ ์ผ๋ฐ˜์ ์œผ๋กœ ๋…ผ๋ฌธ ์ œ์ถœ ๋งˆ๊ฐ์ผ์€ 1 ์›” ๋ง          ์ด๋ฉฐ ํšŒ์˜๋Š” ์ผ๋ฐ˜...