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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
16,511 datasets
A Kaggle dataset likely containing images of fruits and vegetables annotated for object detection tasks. The dataset's title suggests it is formatted for use with the YOLO (You Only Look Once) deep learning model. Specific details about the number of images, annotation format, and source are unknown.
Fruit-Veg-Merged-YOLO-Dataset is a collection of images likely annotated for object detection tasks. Published on Kaggle, it appears designed for training YOLO models. The dataset's specific size, creator, and update date are unknown.
sleep-detection-yolo-dataset is a dataset hosted on Kaggle. The title suggests it contains images annotated for detecting sleep-related states or objects, likely intended for training YOLO-based computer vision models. The dataset's author, organization, size, and update history are unknown.
dhbk_hb_model cnn gei 060 v24.6 is a pre-trained convolutional neural network model hosted on Kaggle. The title suggests it is likely designed for image classification or feature extraction tasks. Its specific architecture, training data, and performance metrics require verification after download.
dhbk_hb_emb_cnn likely contains image embeddings generated by a convolutional neural network. The dataset is hosted on Kaggle, but its specific content, size, and creator are unknown. Its title suggests it is a feature set derived from visual data.
23520461_BaiTap_YOLO is a dataset published on Kaggle. The title suggests it contains exercises or training materials related to the YOLO object detection algorithm. The dataset likely contains image data intended for computer vision tasks.
prepared_model_vgg16_lstm_30k is a dataset hosted on Kaggle. The title suggests it contains a pre-trained model combining the VGG16 convolutional neural network architecture with a Long Short-Term Memory (LSTM) network. The '30k' in the title likely indicates a scale of 30,000 samples or parameters, but the exact content and structure require verification.
prepared_model_vgg16_gru_30k is a dataset published on Kaggle. The title suggests it contains configuration or weights for a hybrid deep learning model combining VGG16 and GRU architectures. The dataset's specific content, scale, and authorship are unknown.
A dataset titled 'prepared_model_vgg16_bilstm_30k' is hosted on Kaggle. The title suggests it likely contains data or model weights related to a VGG16 convolutional neural network combined with a Bidirectional Long Short-Term Memory (BiLSTM) layer. The scale of 30k samples indicates a substantial collection, but the author, organization, and specific content are unknown.
Kaggle hosts a pre-trained model combining ResNet50 and LSTM architectures. The title suggests it was prepared for a task involving 30,000 data points, likely images. Its specific application and performance metrics are unknown.
prepared_model_resnet50_gru_30k is a dataset of pre-trained model weights published on Kaggle. The title suggests it contains weights for a ResNet50 architecture combined with a GRU layer. The dataset's scale, author, and specific content are unknown.
Kaggle hosts a pre-trained model named prepared_model_resnet50_bilstm_30k. The title suggests it combines a ResNet50 architecture with a BiLSTM layer, likely for a sequence or classification task involving 30,000 data points. Specific details about the dataset's creator, content, and update date are unavailable.
Kaggle hosts a dataset titled prepared_model_resnet50_lstm_attention_30k. The title suggests it contains data prepared for training or evaluating a hybrid deep learning model combining ResNet50, LSTM, and attention mechanisms. The dataset likely contains 30,000 samples, though the specific content and format require verification.
YOLO26m-qr is a dataset hosted on Kaggle. The title suggests it is likely an image dataset for object detection tasks, potentially related to QR codes. The dataset's specific content, size, and creation details are unknown.
A Kaggle dataset likely containing images for object detection tasks focused on vegetables and fruits. The dataset's specific size, origin, and update date are unknown. It is hosted on Kaggle, a platform for sharing machine learning datasets.
A collection of images of fruits and vegetables intended for training YOLO (You Only Look Once) object detection models. The dataset is hosted on Kaggle, but its size, specific contents, and creation details are not provided in the metadata. The dataset likely contains annotated images suitable for computer vision tasks.
Fruit-Vegetable-YOLO-Dataset is a collection of images likely intended for training object detection models using the YOLO framework. The dataset is hosted on Kaggle, but its specific size, annotation details, and creation date are unknown. Its content appears to focus on fruits and vegetables.
Kaggle hosts an image dataset for garbage object detection. The dataset likely contains annotated images intended for training computer vision models. Its specific size, origin, and update date are unknown.
NWPU-VGG16 is a pre-trained model dataset published on Kaggle. The dataset likely contains model weights and architecture files for the VGG16 convolutional neural network. Its specific content, size, and origin require verification after download.
A pre-trained Convolutional Neural Network model named 'dhbk_hb_model' is available on Kaggle. The title suggests it is a version 24.7 model, potentially trained on a dataset of images. Its specific architecture, training data, and performance metrics require verification after download.