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This dataset card aims to be a base template for new datasets. It has been generated using this raw template.

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  Dataset Creation… See the full description on the dataset page: https://huggingface.co/datasets/samp3209/logo-dataset.

The Brand Logos and Icons Dataset consists of a collection of 1,991 logos and icons images collected in two formats: 1810 images in PNG format and 145 images in JPG format. These logos represent a diverse array of designs from various industries, including brand logos, corporate symbols, and graphic elements.

Comprehensive dataset containing 12 verified Logos locations in Mexico with complete contact information, ratings, reviews, and location data.

The dataset comprises a total of 510 logo images categorized into five classes, representing different brands: Gojek, Grab, Uniqlo, Miniso, and CircleCI. Specifically, the dataset is divided into 83 training images and 19 testing images. Each image is standardized to a resolution of 300x300 pixels in PNG format. Additionally, the dataset includes a CSV file that labels each image as either positive (original) or negative (forged), which is crucial for tasks involving image verification or detection of counterfeits.

This dataset is particularly suited for applications in machine learning models that employ similarity metrics or triplet loss functions, which are common in tasks such as image comparison and identity verification. The data structure and labeling facilitate training models to discern subtle differences between genuine and forged logos, which is vital in the field of trademark protection.

Researchers interested in utilizing this dataset for academic purposes, particularly in studies involving data augmentation techniques or deep learning for logo recognition and verification, should cite the following source:

Suyahman, S., Sunardi, S., Murinto, M., & Khusna, A. N. (2024). Data Augmentation Using Test-Time Augmentation on Convolutional Neural Network-Based Brand Logo Trademark Detection. Indonesian Journal of Artificial Intelligence and Data Mining, 7(2).

Khusna, A. N. (2024). Siamese Neural Networks with Chi-square Distance for Trademark Image Similarity Detection. Scientific Journal of Informatics, 11(2), 429-438.

This citation provides acknowledgment to the original creators and their contribution to the development of methodologies in image processing and artificial intelligence.

Comprehensive dataset containing 119 verified Logos locations in Russia with complete contact information, ratings, reviews, and location data.

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.

Comprehensive dataset containing 3 verified Logos locations in State of São Paulo, Brazil with complete contact information, ratings, reviews, and location data.

The "Logo-2K+" dataset, published in the paper "Logo-2K+: Discriminative Region Navigation and Augmentation Network for Scalable Logo Classification", is a collection of 167,140 images of logos belonging to 2,341 sub-classes across 10 root-categories. The images were crawled from the Google and Baidu search engines.

Before making the dataset available for public use, I have carefully cleaned the dataset to ensure that it can be loaded and used without any errors. I have removed all folders with special characters and spaces in their names, and only kept alphanumeric characters and underscores. This makes the dataset more accessible and easier to use for researchers and developers working on logo classification.

The cleaned dataset is provided in three parts:

"Logo-2K+.rar" contains the original 167,140 logo images, grouped into 10 root-categories and 2,341 sub-classes.

a. "Logo-2K+classes.txt" provides labels for all sub-classes.

b. "train_images_root.txt" lists the paths of training images starting with the root-category.

c. "test_images_root.txt" lists the paths of testing images starting with the root-category.

d. "train_images.txt" lists the relative paths of training images starting with the sub-class.

e. "test_images.txt" lists the relative paths of testing images starting with the sub-class.

The "Logo-2K+" dataset is a valuable resource for researchers and developers working on logo classification, as it contains a large and diverse set of logo images with well-defined sub-class labels. The provided training and testing images, along with the label files, can be used to train and evaluate logo classification models.

The statistic comparison of 10 root categories from Logo-2K+ is shown as follows.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1885485%2F9473b590a6a770cf5b3cd42e9b66a13b%2FScreenshot%202023-03-23%20at%208.50.41%20PM.png?generation=1679575860470498&alt=media" alt="">

huggingface/brand-assets dataset hosted on Hugging Face and contributed by the HF Datasets community

Comprehensive dataset containing 11 verified Logos locations in Brazil with complete contact information, ratings, reviews, and location data.

Logos Co Limited Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Context

Data set has been harvested from search engines. It contains the 8 brands' logos and the stuffs which have logo on it.

Content

Data set contains 8 logo brands including; toyota, hyundai, lexus, skoda, volkswagen, mazda, mercedes, opel. Each brand has 300~350 training photos and 50 test photos.

Inspiration

How much can you augment the data and increase the accuracy & recall from the base notebook of mine?

The Database Market is Segmented by Database Type (Relational (RDBMS), Nosql, and More), Deployment (Cloud, On-Premsies), Service Model (Database-As-A-Service (DBaaS), License and Maintenance Software), Enterprise (SMEs, Large Enterprises), Workload Type (Transactional (OLTP), Analytical (OLAP), and More), End-User Vertical (BFSI, Retail, and More), and by Geography. The Market Forecasts are Provided in Terms of Value (USD).

This dataset provides information about the number of properties, residents, and average property values for Logos Drive cross streets in Grand Junction, CO.

Human decision-making is driven by subjective values assigned to alternative choice options. These valuations are based on reward cues. It is unknown, however, whether complex reward cues, such as brand logos, may bias the neural encoding of subjective value in unrelated decisions. In this functional magnetic resonance imaging (fMRI) study, we subliminally presented brand logos preceding intertemporal choices. We demonstrated that priming biased participants' preferences towards more immediate rewards in the subsequent temporal discounting task. This was associated with modulations of the neural encoding of subjective values of choice options in a network of brain regions, including but not restricted to medial prefrontal cortex. Our findings demonstrate the general susceptibility of the human decision making system to apparently incidental contextual information. We conclude that the brain incorporates seemingly unrelated value information that modifies decision making outside the decision-maker's awareness.

Logos Tech Co Limited Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Logos Chemical Technologies Industry And Trade Limited Company Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

PredictLeads Key Customers Data provides real-time visibility into business relationships, partnerships, and vendor affiliations across industries. Using advanced web scraping and logo recognition technology, this dataset offers a competitive edge for B2B sales, lead scoring, and company data enrichment.

Use Cases: ✅ Lead Scoring – Prioritize leads based on their key customer network and market influence. ✅ Cold Outreach – Personalize outreach by referencing shared customers or partners. ✅ B2B Data Enrichment – Enhance CRM data with business relationship insights. ✅ B2B Sales – Understand company partnerships to craft tailored sales strategies. ✅ Competitive Analysis – Identify companies working with competitors to refine positioning.

Key API Attributes:

• id (string, UUID) – Unique identifier for the key customer relationship.
• category (string) – Type of relationship (e.g., vendor, partner, customer).
• source_url (string, URL) – Web page where the key customer was identified.
• context (string) – Extracted text describing the business relationship.
• first_seen_at (ISO 8601 date-time) – When the key customer was first detected.
• last_seen_at (ISO 8601 date-time) – Most recent detection of the key customer.
• company1 (object) – Primary company in the relationship, including domain and company name.
• company2 (object) – Associated key customer, vendor, or partner details.

PredictLeads Docs: https://docs.predictleads.com/v3/guide/connections_dataset

Business location data for Maptitude mapping software are from Caliper Corporation and contain point locations for businesses.

View Logos group inc import data USA including customs records, shipments, HS codes, suppliers, buyer details & company profile at Seair Exim.