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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
16,479 datasets
ImageNet-repa-latents-train is a dataset of pre-extracted latent representations, likely derived from the ImageNet visual database. The dataset's specific size, column structure, and extraction method are not detailed in the provided metadata. It is hosted on Kaggle, but the original author, organization, and last update date are unknown.
A computer vision dataset titled 'no boots 3500' published on Kaggle. The dataset's specific content, scale, and creation details are not provided in the available metadata. Further verification is required to confirm the exact nature and scope of the images.
A pre-trained Convolutional Neural Network model, likely for image analysis tasks, published on Kaggle. The title suggests it may be version 24.8 of a model architecture. Specific details regarding the training data, performance, and intended application are not provided in the available metadata.
Kaggle hosts this dataset, which is likely a collection of image embeddings generated by a Convolutional Neural Network (CNN). The title suggests the embeddings may be related to a specific model or processing version (v24.8). The dataset's specific content, scale, and origin require verification after download.
A dataset formatted for YOLO OBB (Oriented Bounding Box) object detection models, hosted on Kaggle. The dataset likely contains images with annotations for detecting objects at various angles. Specific details on size, source, and creation date are not provided in the available metadata.
A dataset likely containing the best-performing weights for the YOLOv8n (You Only Look Once version 8 nano) object detection model, sourced from Kaggle. The specific training data, number of parameters, and performance metrics are not detailed in the available metadata. The dataset's author, organization, and last update date are unknown.
A dataset from Kaggle containing outputs from an ensemble of models including BART-CNN and LED-Arxiv. The specific content, size, and creation details are not provided in the metadata.
Prancvimgcnn is a dataset hosted on Kaggle. The title suggests it contains image data likely intended for training or benchmarking convolutional neural network (CNN) models. No further metadata on size, source, or specific content is available.
PRANCVCSVCNN is a dataset published on Kaggle. The title suggests a focus on computer vision and convolutional neural networks (CNNs). The dataset's specific content, size, and origin are not detailed in the provided metadata.
Encompassing image data for 3 popular fruit varieties categorized into two distinct states: Fresh and Rotten. It provides a targeted collection for binary and multi-class classification tasks focused on agricultural quality assessment.
Yolov8n_akari is a dataset hosted on Kaggle. The title suggests it is likely related to object detection, using the YOLOv8n model architecture. The dataset's specific content, size, and origin are not detailed in the available metadata.
A dataset for object detection tasks, likely containing images with bounding box annotations. It is hosted on Kaggle and categorized under Computer Vision. The specific content, size, and origin details require verification after download.
A pre-trained model named ResnetSE, hosted on Kaggle. The model's architecture, training data, and specific performance metrics are not detailed in the provided metadata. Its intended application likely involves image classification or feature extraction tasks.
Kaggle hosts the finallyocr12hours dataset, a resource for optical character recognition tasks. The dataset likely contains images and corresponding text for training or evaluating OCR models. Its specific content, size, and creation details require verification after download.
A collection of model checkpoints for the YOLO (You Only Look Once) object detection framework, likely used for benchmarking performance. The dataset is hosted on Kaggle and is associated with the platform's 'Benchmark' and 'Computer Vision' tags. Specific details on the number of checkpoints, their versions, and the training data used are not provided in the available metadata.
A pre-trained computer vision model for semantic segmentation tasks, likely based on the UNet architecture with a VGG backbone. The model appears to be associated with the PASCAL VOC dataset, a common benchmark for object recognition and segmentation. It was published on Kaggle, a platform for data science and machine learning resources.
Tabular data on paying attendance and revenue for Brazilian football league matches. The dataset is tagged for sports attendance analysis. Specific details on row count, columns, and temporal coverage are not provided in the input.
A pre-trained SegResNet model, likely designed for semantic segmentation tasks, is hosted on Kaggle. The model's architecture suggests it is intended for processing image data, potentially in domains like medical imaging. Specific details regarding its training data, performance, and intended use are not provided in the available metadata.
A collection of combined model weights for the YOLO11l object detection architecture. The dataset is hosted on Kaggle and likely relates to the SVAMITVA project, which suggests an application in analyzing satellite or aerial imagery. Specific details on the number of weights, their training data, or the author are not provided in the available metadata.
A dataset likely containing image data for use with the ResNet50 deep learning model. The dataset is hosted on Kaggle, but its specific contents, size, and origin are not detailed in the provided metadata. Further details such as the number of images, classes, and collection methodology require verification after download.