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The dataset comprises 16.7k images and 2 annotation files, each in a distinct format. The first file labeled Label contains annotations with the original scale.
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Explore our Google reCAPTCHA V2 Image Dataset, designed specifically for advancing object detection technologies like YOLO.
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Discover our curated Animal Image Dataset featuring bears, crows, elephants, and rats. Ideal for training Convolutional Neural Networks (CNNs) with annotated.
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Train AI models with the Construction Site Safety Dataset to classify safe vs. unsafe scenarios based on PPE requirements.
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Discover comprehensive global salary comparisons across different regions with our interactive dashboard. Explore the top-paying countries.
Download the Traffic Signs Detection Dataset to train AI models for autonomous vehicles, driver assistance, and smart city applications. Improve road safety with machine learning.
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Human action detection in the context of artificial intelligence refers to the process of identifying and classifying human actions or activities from visual data, such as images or videos, using machine learning and computer vision techniques..
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Plant disease is a deviation from the normal state of a plant that disrupts or alters its vital functions. Plant diseases can lead to significant yield losses.
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Explore our Felidae Dataset, designed for precise cat species recognition. This unique collection features unnormalized images.
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CIFAR-10 is a well-known and widely used dataset in the field of computer vision. It contains 60,000 small, low-resolution images in 10 different classes, with each class containing 6,000 images..
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The Electric Wires Dataset offers precise semantic segmentation of cable-like objects, perfect for industrial and infrastructure applications. This high-quality, domain-independent dataset includes detailed annotations.
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Our project involved gathering a wide range of audio recordings in different acoustic environments and accents.
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Explore the Plate Numbers YOLO Dataset, featuring diverse global license plate images under various conditions and annotations.
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The Real_Test_Data_for_Unblur dataset offers a collection of real-world blurred, shaky, and noisy images designed to test and evaluate image restoration algorithms. Unlike artificial datasets, it provides a realistic testing ground to ensure robust and practical algorithm performance in real-world scenarios
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This is a dataset of images of 50 types of car parts. It includes a train set, a test set and a validation set. There are 50 classes of car parts...
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This dataset was created by myself. This dataset contains videos of people doing workouts. The name of the existing workout corresponds to the name of the folder listed.
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Unlock the potential of generative AI with the Prompt2Image dataset, featuring prompts paired with images generated by state-of-the-art model.
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Explore the F1 GrandPrix Dataset, a detailed collection offering insights into circuits, constructors, drivers, and race outcomes.
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Explore the CIFAKE dataset with 60,000 real and 60,000 AI-generated images for machine learning and computer vision research.
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The purpose behind the creation of this dataset is the development of a machine learning model to classify fruits and vegetables as fresh or stale..
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The dataset comprises 16.7k images and 2 annotation files, each in a distinct format. The first file labeled Label contains annotations with the original scale.