AI-Powered
Object Detection
Deep learning based Real-time
Object Detection
Object Tracking
Deep learning based tracker
trough Multi-camera View
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A deep learning-based approach
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Based on the state-of-art detectors
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Robust (trained on the dataset with noise, masking, corruption)
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Acceptable Accurate
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Support different type of Objects
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Tested on different Object such as Pedestrians and Vehicles
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Our detector needs optimization for processing time
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Based on SimpleNet and Efficient Net
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Near Real-time
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Accurate enough (about 95%)
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Robust against camera changes, light conditions, weather conditions, etc
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Combining Tracking and Detection
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Multi-object Tracker
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Online learning (learning based)
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Real-time tracker
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CNN-based feature extractor and using Triplet-loss
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Using Kalman filter for Motion Estimation
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The solution is highly scalable and can be used in several applications
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It does not depend on the camera type, position or situation
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The same solution can be applied in the similar scenarios