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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
16,124 datasets
This dataset codes cooperation agreements between overlapping regional international organizations (RIOs) based on written documentation such as treaties, agreements, and joint statements. It was developed for a research project funded by the German Research Council to analyze variation in inter-organizational cooperation designs.
A collection of face images likely processed for deepfake detection research. The dataset appears to be derived from the FaceForensics++ (FF++) benchmark, a standard source for forgery analysis. It is hosted on Kaggle, but specific details about its size, preprocessing steps, and creation date are unknown.
CNN-Dataset1 is a dataset hosted on Kaggle. Its title suggests a focus on computer vision, likely for tasks like image classification or object detection. The dataset's specific content, size, and origin are not detailed in the available metadata.
CNN Dataset 2 is a computer vision dataset hosted on Kaggle. The dataset's specific content, size, and origin are not detailed in the available metadata. Its title suggests it is likely intended for tasks involving convolutional neural networks.
Kaggle hosts a dataset of pretrained VGG model weights intended for network pruning experiments. The dataset likely contains the learned parameters from a VGG architecture, a common convolutional neural network for image classification. Specific details on the source, training data, and model variant are not provided in the minimal metadata.
EfficientNet models are a family of convolutional neural networks known for their parameter efficiency and scaling methodology. The dataset likely contains model weights and architecture definitions for various EfficientNet variants. It is published on Kaggle, a platform for sharing data and code.
EfficientNet-B3 is a convolutional neural network architecture designed for image classification tasks. The dataset likely contains the pre-trained model weights for the B3 variant of the EfficientNet family. Published on Kaggle, this resource is intended for practitioners seeking to utilize or fine-tune this specific model.
EfficientNet-B0 is a convolutional neural network architecture designed for image classification. The dataset likely contains the model's pre-trained weights or configuration files. It is hosted on Kaggle, a platform for sharing datasets and machine learning resources.
Kaggle hosts a collection of model weights for two prominent instance segmentation architectures, Mask R-CNN and Mask2Former. The weights likely contain trained parameters for these neural networks. The dataset's author, organization, and specific details are unknown.
An image dataset likely intended for training and evaluating YOLO (You Only Look Once) object detection models. The dataset appears to contain scaled versions of data associated with YOLO versions 2 through 5. It was published on Kaggle, but the original author, collection method, and specific time range are unknown.
Kaggle hosts a dataset titled 'Image Classification IN-1K'. The dataset likely contains images intended for classification tasks. Its specific size, origin, and update history are unknown.
Vanilla Plant Disease Image Dataset is a collection of images related to plant health issues. It is hosted on Kaggle. The dataset's size, specific contents, and creation details are unknown.
YOLO scaled models are a series of architectures designed for efficient object detection. This dataset likely contains training data or model weights associated with the YOLOv2, YOLOv3, YOLOv4, and YOLOv5 versions. Published on Kaggle, it serves as a resource for practitioners working with these popular detection frameworks.
A reference list of department codes from the City of San Francisco's financial system, representing a flattened organizational hierarchy. The data includes nested Department Groups, Divisions, Sections, Units, Sub Units, and Departments, each with a code and name. It is maintained as needed and was last updated in March 2026.
UKGEOS Glasgow collected core samples from ten boreholes for laboratory analysis of organic carbon. The dataset includes measurements of total organic carbon percentage, Rock Eval pyrolysis, isotope ratios, kerogen microscopy, and liquid chromatography-organic carbon detection. Analyses were performed by Heriot-Watt University Edinburgh on samples from wells GGA01, GGA03r, GGA04, GGA05, GGA06r, GGA07, GGA08, GGA09r, GGB04, and GGB05.
A benchmark dataset for evaluating long-term memory capabilities in conversational AI systems. It contains multi-turn group dialogues spanning approximately 250 days per topic, organized by date and chat group. The dataset was created by EverMind-AI and last updated on 2026-02-25.
Surface sediment geochemistry data from Nairobi, Mathare, and Ngong Rivers in Kenya, collected on January 16, 2020. The dataset includes trace metals, Pb isotope ratios, and organic pollutants like pharmaceuticals and hydrocarbons, supporting a 2022 research publication.
Aggregating anonymized data from a study analyzing health professionals' perceptions and practices regarding immunization, considering organizational, structural, and work process aspects in public and private services. Data was collected via a structured questionnaire from 109 participants. It includes sociodemographic variables and questions related to the organization of immunization actions, professional practices, and perceptions of the work process.
Microsoft COCO 2017 is a dataset for object detection, segmentation, and captioning tasks. The dataset was created by Microsoft and is hosted on Kaggle. The specific number of images, annotations, and the last update date are not provided in the available metadata.
Kaggle hosts a dataset titled 'yolox26'. The dataset's content is inferred to relate to object detection, likely for training or benchmarking computer vision models. Its specific contents, scale, and origin are not detailed in the available metadata.