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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
16,345 datasets
A YOLO-compatible dataset for real-time naval vessel detection. It contains images annotated with oriented bounding boxes (OBB), which are suited for detecting rotated objects. The dataset's author, size, and specific source are not provided.
Annotated images of trash in Malaysia, using instance segmentation to fit real-world noise. The dataset is hosted on Kaggle, but the author, organization, and specific collection details are not provided. The temporal coverage, total number of images, and file formats are unknown.
A dataset likely related to preparing images for YOLO (You Only Look Once) object detection models. It is published on Kaggle, but its specific contents, size, and creation details are not described. The title suggests it contains data intended for preprocessing steps in a computer vision pipeline.
Honey bee colony images formatted for YOLO object detection models. The dataset is hosted on Kaggle, a major platform for data science competitions and projects. Its specific content and collection methodology require verification after download.
LUNG_CANCER_DATASET_YOLO is a dataset from Kaggle. It likely contains medical images annotated for object detection using the YOLO framework. The specific contents, size, and origin are not detailed in the available metadata.
lung_areas_yolo_box_dataset is a computer vision dataset hosted on Kaggle. The title suggests it contains medical images with bounding box annotations for lung areas, likely intended for training object detection models. The dataset's specific size, origin, and update date are not provided in the available metadata.
Kaggle hosts pre-trained weights for the EfficientNet-B0 model architecture. The dataset likely contains the parameter files necessary to load the model. The author, organization, and specific details of the training data are unknown.
A model checkpoint named 'ckpt samresnet34 without realworld' is hosted on Kaggle. The dataset's content and creation details are unspecified. Its intended application likely relates to computer vision tasks.
Inception-weights-imagenet is a dataset of pre-trained model weights for the Inception architecture, likely intended for image classification tasks. The dataset is hosted on Kaggle, but its specific contents, such as the exact model variant or training details, are not described. Users must download the dataset to verify its structure and intended application.
VGG-weights likely contains the learned parameters for a VGG convolutional neural network architecture. The dataset is hosted on Kaggle, but its specific version, size, and creation details are not provided in the metadata. The content appears to be intended for transfer learning or model initialization in computer vision tasks.
(14-45_epochs)yolo12n_segformer is a dataset hosted on Kaggle. The title suggests it contains outputs or training data related to the YOLO12n and Segformer models, which are used for object detection and semantic segmentation tasks. The dataset's specific contents, scale, and origin are not detailed in the provided metadata.
NASNet-imagenet-weights is a dataset of pre-trained neural network weights for the NASNet architecture. The weights were likely trained on the ImageNet dataset, a large-scale visual recognition benchmark. The dataset is hosted on Kaggle, but specific details about the author, organization, and creation date are unknown.
Kaggle hosts a dataset for pothole segmentation, likely containing images of road surfaces. The dataset appears to be augmented for training YOLO (You Only Look Once) object detection models. Details on the dataset's size, origin, and collection date are not provided in the available metadata.
A dataset titled 'small-objects-visdrone-yolo' is hosted on Kaggle. The dataset likely contains images from the VisDrone benchmark, formatted for training YOLO object detection models. Its specific size, annotation details, and creation date are not provided in the available metadata.
Exploratory Graph Analysis (EGA) implements a framework for dimensionality and psychometric assessment using network estimation and community detection. The method, developed by Hudson Golino, includes bootstrap stability assessment, configural and metric invariance testing, and analysis for hierarchical and time-series data. It provides network loadings and scores analogous to factor analysis within a network psychometrics paradigm.
PASCAL VOC 2012 is a seminal benchmark dataset for computer vision tasks. It was created for the PASCAL Visual Object Classes challenge and is hosted on Kaggle. The dataset likely contains images with annotations for object detection, classification, and segmentation.
EPM's dataset tracks electric vehicle charging consumption at public stations from January 2019 to June 2025. Data is aggregated by fortnight and presented with monthly totals to monitor service usage. The dataset is published by www.datos.gov.co.
Rat Blood Component Image Datasets is an image collection for blood component analysis. The dataset appears to contain microscopic images of rat blood samples. Details on the number of images, collection methodology, and specific components are not provided in the available metadata.
Kaggle hosts a dataset titled ResNet18-Pet-Classification-Pipeline3. The title suggests it likely contains images of pets intended for classification tasks. The dataset is published on Kaggle, but detailed metadata such as author, size, and license are unknown.
GAN Model is a dataset hosted on Kaggle, likely containing data for training or evaluating Generative Adversarial Networks. The dataset's specific content, size, and origin are not detailed in the provided metadata. Kaggle is a platform where users share datasets for machine learning tasks.