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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
16,510 datasets
A dataset of fruit and vegetable images formatted for training YOLO (You Only Look Once) object detection models. The dataset is hosted on Kaggle, but specific details on the number of images, annotations, and creation date are not provided in the metadata. The content and scale require verification after download.
An image dataset for training and evaluating object detection models, specifically for pistol identification. The dataset is hosted on Kaggle and likely contains annotated images suitable for the YOLO v8 architecture. Details on the number of images, annotation format, and collection source are not provided in the metadata.
A pre-trained computer vision model hosted on Kaggle. The title suggests it is likely based on the EfficientNet architecture and may be fine-tuned for a specific task, such as classifying images of bees. Its specific origin, training data, and performance metrics are not detailed in the provided metadata.
A dataset titled 'Fruit or Vegetable object detection' is hosted on Kaggle. The dataset likely contains images for training and evaluating object detection models focused on food items. Further details on the number of images, annotation format, and specific classes are unavailable from the provided metadata.
CAC_DA_Amh_OCR is a dataset for Optical Character Recognition tasks, likely containing images of Amharic script text. The dataset is hosted on Kaggle, but its specific size, creation date, and author are not provided in the metadata. Its content and structure must be verified after download.
A dataset published on Kaggle, likely containing images annotated for object detection using the YOLOv7 model. The specific number of images, source, and creation date are unknown from the provided metadata. The dataset's primary purpose appears to be for training or benchmarking object detection algorithms.
A Kaggle dataset likely containing pre-trained models or training data for optical character recognition tasks. The dataset's author, size, and specific contents are not detailed in the provided metadata. Its last update date and licensing information are also unknown.
CNN-NEWPX is a pre-trained model dataset hosted on Kaggle. The dataset's specific content, size, and origin are not detailed in the provided metadata. Its title and platform tags suggest it is related to convolutional neural networks, likely for image-based tasks.
Meus Pesos YOLO is a dataset published on Kaggle. The title suggests it contains images annotated for object detection, likely related to tracking weights or similar objects. Metadata is minimal; the actual content, scale, and specific application require verification after download.
A dataset titled 'yolo-percepcao' hosted on Kaggle. The title suggests a focus on computer vision and object detection, likely using the YOLO (You Only Look Once) framework. Metadata is minimal; the dataset's content, scale, and origin require verification after download.
YOLO (You Only Look Once) model weights for object detection tasks, published on Kaggle. The dataset's specific version, training data, and performance metrics are not detailed in the available metadata. Further verification of the weights' origin and compatibility is required after download.
YOLO weight files, likely containing pre-trained model parameters for the YOLO (You Only Look Once) object detection algorithm. The dataset is hosted on Kaggle, but the specific version, author, and training data details are not provided in the metadata. The exact number of weight files, their format, and the training corpus are unknown.
A pre-trained convolutional neural network model published on Kaggle. The title suggests it may be a version 24.4 release, likely intended for image processing tasks. Specific details about its architecture, training data, and performance are not provided in the available metadata.
CNN embeddings likely extracted from a collection of images. The dataset's title suggests it contains feature vectors generated by a convolutional neural network (CNN). Published on Kaggle, its specific source, size, and creation date are unknown.
Kaggle hosts a dataset titled 'fruit-vegetable-yolo-dataset'. The dataset likely contains images of fruits and vegetables annotated for use with the YOLO object detection framework. The dataset's author, organization, size, and specific content are unknown.
A dataset for training and evaluating YOLO-based object detection models on images of fruits and vegetables. The dataset is hosted on Kaggle, but details on the number of images, annotations, and specific classes are not provided in the metadata. The original author, collection method, and temporal coverage are unknown.
A Kaggle-hosted collection of images likely intended for training YOLO-based object detection models. The dataset's title suggests it contains images of fruits and vegetables, but the exact number of images, annotation format, and source are unspecified. Metadata is minimal; actual content requires verification after download.
dhbk_hb_model cnn gei 030 v24.5 is a pre-trained convolutional neural network model hosted on Kaggle. The model likely contains image-based features for computer vision tasks. Its specific architecture, training data, and performance metrics are not detailed in the available metadata.
A dataset titled 'dhbk_hb_emb cnn gei 030 v24.5' hosted on Kaggle. The title suggests it may be related to computer vision and convolutional neural networks (CNN). The dataset's specific content, size, and origin are unknown.
MURA-cnn-pipeline.zip is a dataset from Kaggle, likely containing medical images for a convolutional neural network workflow. The title suggests a focus on musculoskeletal radiographs (MURA). Specifics on volume, source, and update date are not provided in the metadata.