Badge Detection

## Overview

Badge Detection is a dataset for object detection tasks - it contains Objects annotations for 1,192 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [BY-NC-SA 4.0 license](https://creativecommons.org/licenses/BY-NC-SA 4.0).

Car Badge Detection 2

## Overview

Car Badge Detection 2 is a dataset for object detection tasks - it contains Car Badges BmSC annotations for 585 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Open Set Logo Detection Dataset (OSLD Dataset) is a dataset of eCommerce product images with associated brand logo images. It is released under creative commons (CC BY-NC 4.0) license to promote research in open set logo detection. The dataset can be used only for research purposes. The dataset contains:

20K eCommerce product images, with logo bounding box annotations 12.1K logo classes with 20.8K canonical logo images Product image logo bounding box to canonical logo image match pair annotations

Car Badge Detection

## Overview

Car Badge Detection is a dataset for object detection tasks - it contains Car Badges annotations for 585 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Vehicle Logo Detection

## Overview

Vehicle Logo Detection is a dataset for object detection tasks - it contains Vehicle Logo annotations for 9,900 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

A logo detection dataset with full annotation, which has 3,000 logo categories, about 200,000 manually annotated logo objects and 158,652 images. LogoDet-3K creates a more challenging benchmark for logo detection, for its higher comprehensive coverage and wider variety in both logo categories and annotated objects compared with existing datasets.

Car Logo Detection

## Overview

Car Logo Detection is a dataset for object detection tasks - it contains Car Logos annotations for 5,697 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

The logos have been resized to a uniform shape of 70x70 to make it less demanding on computational resources and model complexity when training. Though the original files can be found on one of my github repos, the link can be found below. GitHub Repo. The code used to mine and process the data can also be found on the repo.

Original Data Source: Fake/Real Logo Detection Dataset

Object detection benchmark for logo detection.

Images are natural scenes. Each image contains multiple objects, and each image has a total of 1 logo. Logo detection & classification labels are provided.

Anesthesia Detection Badge Market Outlook

The global anesthesia detection badge market size was valued at USD 480 million in 2023 and is expected to grow to USD 890 million by 2032, with a compound annual growth rate (CAGR) of 7.1%. This growth can be attributed to a variety of factors such as advancements in wearable technology, increasing surgical procedures, and heightened awareness regarding patient safety during anesthesia.

The primary growth factor for the anesthesia detection badge market is the escalating prevalence of surgical procedures worldwide. With an aging population and a rise in chronic diseases, the demand for surgeries has seen a significant increase. This, in turn, has driven the need for accurate and reliable monitoring of anesthesia, leading to the adoption of anesthesia detection badges in healthcare settings. Moreover, the focus on improving patient safety and reducing anesthesia-related complications has also contributed significantly to market growth. Anesthesia detection badges provide real-time monitoring and alerts, ensuring timely interventions and enhancing overall patient care.

Technological advancements in the field of wearable medical devices have further propelled the market. The development of innovative and sophisticated anesthesia detection badges that are more accurate, user-friendly, and cost-effective has made them more accessible to healthcare providers. Additionally, integration with electronic health records and other medical systems has improved the efficiency of these devices, making them indispensable in modern healthcare facilities. The advent of miniaturized sensors and the Internet of Medical Things (IoMT) has also played a crucial role in expanding the market.

Another significant growth factor is the rising awareness and implementation of stringent regulatory standards in the healthcare sector. Governments and healthcare organizations worldwide are emphasizing the importance of monitoring anesthesia to ensure patient safety. Regulatory bodies have introduced guidelines and protocols that mandate the use of monitoring devices during surgical procedures. This regulatory push has incentivized healthcare providers to adopt anesthesia detection badges, thus driving market growth. Additionally, increasing healthcare expenditure and investments in healthcare infrastructure have further supported the market expansion.

From a regional perspective, North America currently holds the largest market share due to the presence of advanced healthcare infrastructure, high healthcare expenditure, and a large number of surgical procedures performed annually. Europe follows closely, driven by similar factors along with increasing government initiatives to improve patient safety. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, fueled by the rapid development of healthcare infrastructure, increasing medical tourism, and rising awareness about the importance of anesthesia monitoring. Latin America and the Middle East & Africa are also anticipated to show significant growth due to improving healthcare facilities and increasing adoption of advanced medical devices.

Product Type Analysis

The anesthesia detection badge market can be segmented by product type into wearable badges and non-wearable badges. Wearable badges are expected to dominate the market due to their convenience and ease of use. These badges can be comfortably worn by healthcare providers and patients, providing continuous monitoring without interfering with medical procedures. The advancement in wearable technology, including the development of compact, lightweight, and highly sensitive sensors, has significantly contributed to the growth of this segment. Additionally, wearable badges offer real-time data transmission, which is crucial for timely interventions and decision-making during surgical procedures.

Non-wearable badges, although not as popular as their wearable counterparts, still hold a significant market share. These badges are typically used in situations where continuous monitoring is not necessary, or in settings where wearable badges may not be feasible. Non-wearable badges are often employed in outpatient clinics and smaller healthcare facilities where the volume of surgical procedures is lower. The cost-effectiveness and ease of implementation of non-wearable badges make them a viable option for many healthcare providers, particularly in emerging markets where healthcare budgets may be more constrained.

The choice between wearable and non-wearable badges often d

The global anesthesia detection badge market is anticipated to be valued at USD 12.3 million by 2033, expanding at a CAGR of 8.4% from 2025 to 2033. This growth is primarily driven by the rising demand for accurate and efficient anesthesia monitoring, increased awareness about patient safety during surgical procedures, and technological advancements in anesthesia detection devices. Furthermore, the growing prevalence of chronic diseases and surgeries, coupled with the implementation of stringent regulations regarding patient safety in healthcare facilities, are contributing to the market's expansion. The application segment is further classified into human anesthesia and veterinary anesthesia. The human anesthesia segment accounted for a larger market share in 2025 and is expected to maintain its dominance throughout the forecast period. This is attributed to the high prevalence of surgeries and the increasing awareness of accurate anesthesia monitoring among healthcare professionals. The veterinary anesthesia segment is also expected to witness significant growth due to the rising number of veterinary procedures and the growing demand for advanced anesthesia management practices in animal healthcare. The key players operating in this market include Vetland Medical, DRE Veterinary, Hallowell EMC, ICU Medical, Vetronic, and New Gen Medical, among others.

Fake Logo Detection Project which is used to detect the fake logos

The global market for digital badges in education is experiencing robust growth, driven by the increasing adoption of technology in learning and the need for effective recognition of skills and achievements beyond traditional transcripts. The market, estimated at $500 million in 2025, is projected to experience a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $1.8 billion by 2033. Key drivers include the rising demand for personalized learning experiences, the growing acceptance of digital credentials by employers, and the increasing use of learning management systems (LMS) that integrate digital badge platforms. The higher education sector currently dominates the market, but the K-12 segment is poised for significant expansion as schools and districts embrace digital tools for assessment and learner recognition. Virtual badges currently hold the largest market share due to their cost-effectiveness and ease of implementation, though real badges are gaining traction for their tangible representation of accomplishment. Geographic distribution shows strong growth across North America and Europe, fueled by early adoption and robust digital infrastructure, while the Asia-Pacific region exhibits high potential for future expansion. Challenges remain, such as concerns about standardization, interoperability of different badge systems, and the need for robust validation mechanisms to ensure the credibility of digital badges. The competitive landscape is dynamic, with established players like Pearson Education and Accredible alongside innovative startups. Key players are focusing on strategic partnerships, platform integrations, and expanding their product offerings to cater to specific educational needs. Companies are also investing in technologies like blockchain to enhance the security and verification of digital badges, thereby increasing their value and trustworthiness. Future growth will depend on overcoming standardization challenges, fostering wider adoption in developing economies, and continuous innovation in badge design, verification, and integration with other learning technologies. The development and integration of AI-powered badge recommendation and analytics systems will also play a crucial role in expanding the market and its impact on education.

Logo-2K+:A Large-Scale Logo Dataset for Scalable Logo Classification The Logo-2K+ dataset contains a diverse range of logo classes from real-world logo images. It contains 167,140 images with 10 root categories and 2,341 leaf categories. The 10 different root categories are: Food, Clothes, Institution, Accessories, Transportation, Electronic, Necessities, Cosmetic, Leisure and Medical.

Data for article in Ecology Letters by Chaine, Shizuka, Block, Zhang, and Lyon entitled "Manipulating badges of status only fools strangers"

🩺 BCCD: Blood Cell Count & Detection

Microscopic Blood Analysis Dataset

https://img.shields.io/badge/License-MIT-yellow.svg" alt="License: MIT">
License Details

Say hello to BCCD, a dataset with 364 blood smear images and 4,888 labeled objects across 3 classes—WBC, RBC, and Platelets. Perfect for object detection in medical imaging and biomedical research! 🩻✨

📜 What’s This About?

Released in 2018, BCCD offers microscopic blood cell images with bounding box annotations, split into train (205), val (87), and test (72) sets. It’s a lightweight yet powerful tool for automating blood cell analysis in healthcare. 🧬

📊 What’s Inside?

• Images: 364
• Objects: 4,888
• Classes:
  • WBC (372) – White Blood Cells
  • RBC (4,155) – Red Blood Cells
  • Platelets (361)
• Splits: Train (205), Val (87), Test (72)
• Annotations: Bounding boxes
• Size: 7 MB

💡 What Can You Do With It?

• Detect & count blood cells with bounding boxes. 📍
• Train models for medical diagnostics. 🤖
• Explore biomedical imaging applications. 📈

📜 Citation

Using BCCD? Cite it:

@dataset{BCCD,
author={shenggan and Nicolas Chen and cosmicad and akshaylamba},
title={BCCD: Blood Cell Count and Detection},
year={2018},
url={https://github.com/Shenggan/BCCD_Dataset}
}

For Dataset Ninja tools:

@misc{ visualization-tools-for-bccd-dataset,
title = { Visualization Tools for BCCD Dataset },
author = { Dataset Ninja },
url = { https://datasetninja.com/bccd },
year = { 2025 },
journal = { Dataset Ninja }
}

📜 License

MIT License.

✅ Use freely—just credit the creators!

🌟 Let’s Make an Impact!

BCCD is your ticket to advancing blood cell analysis—download, experiment, and upvote if it sparks your next breakthrough. Let’s revolutionize healthcare together! 🙌

Fake Logo Detection

## Overview

Fake Logo Detection is a dataset for object detection tasks - it contains Logos annotations for 932 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Discover the LEGO Minifigure Faces dataset, a curated collection of 800 annotated images for facial recognition tasks.

Digital Badges Market size was valued at USD 177.96 Million in 2024 and is projected to reach USD 706.55 Million by 2031, growing at a CAGR of 18.81% during the forecasted period 2024 to 2031.

The Digital Badges Market is driven by the increasing emphasis on skills-based education and lifelong learning, as organizations and educational institutions use digital badges to recognize and validate specific skills and achievements. The rise of e-learning platforms and the need for micro-credentials in a rapidly evolving job market further boost demand. Additionally, the growing adoption of blockchain technology for secure and verifiable digital credentials enhances trust and credibility, encouraging broader acceptance. The shift towards remote work and online education also contributes to the market, as digital badges offer a flexible and accessible way to showcase competencies and accomplishments.

The size of the Digital Badges Industry market was valued at USD XXX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of 17.38% during the forecast period.Digital badges would be the electronic representation of a person's skills, achievements, or competencies. They are like virtual trophies or certificates that may be won through various approaches, such as completing online courses, participating in workshops, or demonstrated proficiency in specific skills. These badges are usually placed on social media profiles, resumes, or even personal websites to illustrate the individual's accomplishments to various employers, clients, or peers.The flexibility and ease of use of digital badges have made them increasingly popular. They are considered versatile in recognition and use in celebrating any achievement, ranging from the need to complete an online course that lasts for a short period to achieving a professional certification. As such, they are user-friendly for any segment of learners-both the students, working professionals, and even lifelong learners.Digital badges are capable of showcasing a far more relevant and accurate view of an individual's expertise and capabilities. Compared to traditional paper certificates, which are often used in the industry, there is less context and detail that digital badges can provide. For instance, a badge digital would contain information about what skills are acquired, at what level of proficiency and according to what criteria one's performance was evaluated. This kind of detail can be quite valuable to employers when they are seeking to hire employees with specific skills and qualifications. Digital badges are also very portable and shareable; they do not take up physical space like paper certificates, and therefore can easily be shared across various platforms, making it easy for the recipient to show off his achievements to a higher audience. This will definitely be helpful for those job seekers who want to exhibit their skills and experiences to future employers.Besides their practical uses, digital badges can also be employed to motivate and involve the learners. Digital badges serve as physical embodiments of recognition for the attainment of learners. They help an individual continue the learning process, which is a trend in lifelong learning, where an individual needs to provide skills updated with each passing time to keep suitably positioned in the job market.Overall, this digital badge is a very powerful tool through which individuals can show their competency or skills in the digital era.They are easy to access, portable, and shareable in showing one's competencies. They would be used to drive and engage learners as the trend of using digital badges would continue and become part of the new workforce. Recent developments include: June 2023: Skilljar has announced a partnership with Accredible; Issuing organizations can seamlessly connect their Skilljar training content with their credentialing program through the new Accredible Integration with Skilljar. This API integration offers learners a more streamlined and engaging experience, enhancing your credentials' market value and relevance., January 2023: Digital Nasional Berhad and Ericsson declared the launch of a free online academic program on 5G and digital technology for all students at the tertiary level in Malaysia. The 'MY5G Ericsson Malaysia Pioneers Programme' serves DNB's objective of contributing to the overall development of tech talent throughout the country. The program consists of three modules expected to enable students to understand digital services' technological functionalities and applications in detail. After clearing all the assessments, students would take online assessments within each module and earn an Ericsson digital badge.. Key drivers for this market are: Increasing Focus on Online Learning. Potential restraints include: Lack of IT Infrastructure in Developing Regions. Notable trends are: Academic Segment to Occupy a Significant Market Share.