Deep Learning Based Object
Deep learning-based object detection aims to automatically identify and locate objects within images or videos, leveraging the power of neural networks to achieve high accuracy and speed. Current research emphasizes improving robustness in challenging scenarios, such as open-world settings with unseen objects, and addressing limitations in detecting small or obscured objects, often employing architectures like YOLO variants and EfficientDet. This field is crucial for numerous applications, including autonomous driving, medical image analysis, and industrial automation, driving advancements in both computer vision and related domains.
Papers
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