# Object Detection

A YOLOv11-based object detection model for detecting swimming pools in satellite images.

A license plate detection model fine-tuned based on the YOLOv8 framework, suitable for autonomous driving and traffic monitoring scenarios

An object detection model fine-tuned from microsoft/conditional-detr-resnet-50, suitable for target detection tasks in specific scenarios

An object detection model fine-tuned for 20 epochs on a boat dataset, based on the facebook/detr-resnet-50 model

This model is an object detection model fine-tuned on a grasshopper detection dataset, based on Facebook's DETR-ResNet-50-DC5 architecture.

This model is a fine-tuned object detection model based on microsoft/conditional-detr-resnet-50, specifically designed for trash detection tasks, with data augmentation techniques applied during training.

Florence-2 is an advanced vision foundation model developed by Microsoft, employing a prompt-based paradigm to handle various vision and vision-language tasks.

Florence-2 is an advanced visual foundation model developed by Microsoft, employing a prompt-based approach to handle a wide range of vision and vision-language tasks.

Object detection model based on RT-DETR architecture, fine-tuned on CPPE-5 dataset with pre-training on COCO and Objects365 datasets

This is a Mask2Former model fine-tuned on the ADE20K-mini dataset, specifically designed for instance segmentation tasks, capable of identifying 'person' and 'car' categories in images.

A table transformer model trained on the PubTables1M dataset for table structure recognition in documents.

DETR object detection model fine-tuned on an image folder dataset, based on facebook/detr-resnet-50

An object detection model fine-tuned on a food image dataset based on facebook/detr-resnet-101

A model fine-tuned based on facebook/detr-resnet-50 for object detection tasks

A fine-tuned model based on facebook/detr-resnet-50 for object detection tasks

A weed detection model fine-tuned based on facebook/detr-resnet-50, suitable for computer vision tasks.

YOLOS is an object detection model based on the Transformer architecture, designed for efficient visual task processing.

YOLOS-small is a small object detection model based on the Transformer architecture, designed for efficient visual tasks.

An object detection model fine-tuned on the COCO dataset based on facebook/detr-resnet-50

A fine-tuned model based on facebook/detr-resnet-50, specific purpose not clearly stated

This model is based on the DeTr architecture, pre-trained on 5,000 table detection images, and then fine-tuned for specific table detection tasks

A model fine-tuned based on facebook/detr-resnet-50, specific purpose not clearly stated

End-to-end object detection model based on Transformer architecture with ResNet-101 feature extractor

An OCR model fine-tuned from facebook/detr-resnet-50 for object detection tasks

A keyboard detection model fine-tuned based on facebook/detr-resnet-50 for keyboard recognition tasks in images.

A fine-tuned model based on facebook/detr-resnet-50 for object detection tasks

A vision object detection model fine-tuned on the beyond_words_23 dataset based on facebook/detr-resnet-50

DETR object detection model fine-tuned on the CPPE-5 dataset

A table detection model fine-tuned based on facebook/detr-resnet-50, trained on the table_detection_light dataset

Aircraft object detection model based on YOLOv8m, excelling on the plane-detection dataset.

An object detection model based on YOLOv8n, specifically designed for detecting forklifts and personnel.

Lightweight forklift object detection model based on YOLOv5n, optimized for forklift recognition

A small-sized YOLOS model fine-tuned on the COCO 2017 object detection dataset, utilizing Vision Transformer architecture for efficient object detection

A YOLOS model fine-tuned on the COCO 2017 object detection dataset, utilizing a Vision Transformer architecture, suitable for object detection tasks.

A vision Transformer (ViT)-based object detection model trained with DETR loss function, achieving excellent performance on the COCO dataset.

YOLOS model fine-tuned on the COCO 2017 object detection dataset, utilizing Vision Transformer architecture for efficient object detection.

A PyTorch-based object detection model specifically designed to identify hot dogs in images