영상 처리 및 컴퓨터 비전
R2026bDeep Learning Toolbox™를 사용하여 영상 처리, 컴퓨터 비전, 외관 검사, 의료 영상, 포인트 클라우드 처리, 자율주행 응용 분야에 딥러닝을 적용합니다.
카테고리
추천 예제
딥러닝을 사용하여 영상 해상도 높이기
이 예제에서는 VDSR(Very-Deep Super-Resolution) 신경망을 사용하여 하나의 저해상도 영상에서 고해상도 영상을 만드는 방법을 보여줍니다.
Cardiac Left Ventricle Segmentation from Cine-MRI Images Using U-Net Network
Segment 2-D cardiac MRI images using U-Net, and explore predictions using Grad-CAM explainability maps.
Lidar Object Detection Using Complex-YOLO v4 Network
Detect objects in point clouds using you only look once version 4 (YOLO v4) deep learning network. In this example, you:
Train Deep Learning Semantic Segmentation Network Using 3-D Simulation Data
Use 3-D simulation data to train a semantic segmentation network and fine-tune it to real-world data using generative adversarial networks (GANs).
Multiclass Object Detection Using YOLO v2 Deep Learning
Train a YOLO v2 multiclass object detector and evaluate object detector performance across selected classes and overlap thresholds.
Spacecraft Pose Estimation Using HRNet Keypoint Detector and PnP Solver
Estimate keypoints and pose of spacecraft.
Reidentify People Throughout a Video Sequence Using ReID Network
Track people throughout a video sequence using re-identification with a residual network.
Perform Instance Segmentation Using SOLOv2
Segment object instances of randomly rotated machine parts in a bin using a deep learning SOLOv2 network.
