Deep Learning Perception refers a branch of artificial intelligence that mimics the human brain's ability to perceive and recognize patterns, enabling machines to make decisions based on visual inputs. It plays a crucial role in various domains such as autonomous driving, medical image analysis, and robotics etc.
Naming Prefix | Description |
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HKAI__ | Perception using Deep Learning |
This repository meticulously documents my extensive journey through various projects related to cognitive perception using State-of-the-Art (SOTA) Deep Learning Models. Each project intricately tackles unique perception problems, showcasing the comprehensive application and unparalleled effectiveness of deep learning techniques in interpreting and understanding complex visual data.
Classification | Single State | Double Stage | Segmentation | Optical Flow |
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AlexNet | SSD | R-FCN | U-Net | RAFT |
VGG | FCOS | R-CNN | SegNet | FlowNet 2.0 |
ResNet | YOLO | Fast R-CNN | DeepLab | FlowNet Simple |
GoogleNet | RetinaNet | Faster R-CNN | Mask R-CNN | FlowNet Correlation |