🎓 Decompose Korean Component By Using Opencv
-
Updated
Jun 12, 2024 - Python
🎓 Decompose Korean Component By Using Opencv
[Open Source]. The improved version of AnimeGAN. Landscape photos/videos to anime
Graph Inference on MoLEcular Topology
图卷积神经网络 Graph Convolutional Network with Keras
Pipeline Game Input to YOLOv3 Object Detection to detect opponents.
A U-Net for approximating the MEG inverse problem
Balanced Multiclass Image Classification with TensorFlow on Python.
Docker Compose in combination with a neural network
Object Detection and Tracking in Street View Imagery using YOLOv3 and DeepSORT.
[ICMLA'19] [Tensorflow] Classifying different Retinal Diseases using Deep Learning from Optical Coherence Tomography Images
Experiments in which Deep Reinforcement Learning agents try to choose the correct traffic light phase at an intersection to maximize the traffic efficiency. (Deep Q-Learning and Independent Deep Q-Networks)
👣 “恒锐杯”鞋印花纹图像类别判定挑战赛
Tensorflow 2 Object Detection API kurulumu, GPU desteği, custom model hazırlama, label map oluşturma
This is a demo project which uses tensorflow object detection api to detect undesired objects in sensitive places with existing CC TV/ ip camera.
The cross-platform image classifier program is compatible with any desktop & web app of Tensorflow 1.15.4 GPU.
An easy-to-use CLI tool for training and testing image classifiers
[ICIP'20] [Tensorflow] Improving robustness using Joint Supervised-Unsupervised Network for OCT images
Part Grouping Network (PGN) implementation in TensorFlow, for custom parsing dataset
The purpose of this tutorial is to learn how to install and prepare TensorFlow framework to train your own convolutional neural network object detection classifier for multiple objects, starting from scratch
Compressed CNNs for airplane classification in satellite images (APoZ-based parameter pruning, INT8 weight quantization)
Add a description, image, and links to the tensorflow-gpu topic page so that developers can more easily learn about it.
To associate your repository with the tensorflow-gpu topic, visit your repo's landing page and select "manage topics."