The YOLOv4 Tiny algorithm can be applied to factory defect detection, medical image analysis, biological image analysis, industrial safety image analysis, mask image an

Use LSTM to train and predict the ticket sales.

Use YOLOv4 for real-time multi-object tracking, which can be applied to various fields such as monitoring systems and traffic flow analysis.

Use genetic algorithms to solve the multi-objective scheduling problem.

Use genetic algorithms to solve the problem of factory scheduling Job Shop.

This solution can be applied to factory defect detection, medical image analysis, biological image analysis, industrial safety image analysis, mask image analysis, etc.

This solution can be applied to factory defect detection, medical image analysis, biological image analysis, industrial safety image analysis, mask image analysis, etc.

Use genetic algorithm to solve the problem of factory scheduling Flow Shop.

Object detection using MobileNetV3 can be applied to factory defect detection, medical image analysis, biological image analysis, industrial safety image analysis, and

Use Autoencoder for credit card fraud detection.

This solution can be applied to factory defect detection, medical image analysis, biological image analysis, industrial safety image analysis, mask image analysis, etc.

Use FasterRCNN for object detection, which can be applied to factory defect detection, medical image analysis, biological image analysis, industrial safety image analys

The feature of CycleGAN is that it does not require training data to be paired, and can learn image conversion between different domains. The streets applied to semanti

Using DETR for object detection can be applied to factory defect detection, medical image analysis, biological image analysis, industrial safety image analysis, and mas

The application areas of BERT include Question Answer system, reading comprehension, semantic disassembly, and semantic analysis. 

Applied to human body posture detection, it can detect the position of people's eyes, nose, ears, neck, shoulders, elbows, wrists, hip joints, knee joints, and ank

Use DenseNet to train and inference stock data.

Jupyter-Image-GAN-Compression-PyTorch is to perform style conversion after compressing the GAN model. The compressed model not only reduces the amount of calculation, r

App4AI SDK, Use DenseNet to train and inference the Sin function.

FaceNet can be applied to face grouping and face classification, and judge the similarity of faces through Euclidean distance, and then achieve face recognition.

Use one-dimensional Convolutional neural network for data analysis.

GPT-2 is used to automatically generate an English article, and you can also enter any sentence to automatically generate an English article.

The easy-to-use tools for common image processing include image reading, image saving, grayscale conversion, binarization, and connection to find objects.

It can train custom speech datasets, infer and output categories, use CNN to recognize word classification, and implement simple speech recognition

The pix2pix architecture is similar to GAN, but the purpose is not to generate simulated images, but to use supervised learning to output the image style learned by the

Super Resolution is to increase the resolution of the video, a low-resolution image, using SRGAN to generate a high-resolution, thereby improving the resolution of the

The feature of CycleGAN is that it does not require training data to be paired, and can learn image conversion between different domains. The streets applied to semanti

AI human posture detection, such as human skeleton detection, fall detection, people counting, etc. It can detect the position of human eyes, ears, nose, neck, shoulder

Commonly used multi-function face recognition algorithm. It can be applied to crime detection and prevention, access control and attendance smart long-term care, public

ONNX (Open Neural Network Exchange) is a set of open neural network exchange formats. Why do we need interoperability between frameworks? Different frameworks have diff

Use UNet to segment the image. It can be applied to medical image analysis, defect image analysis, etc.

The mainstream time series data regression algorithm.

The mainstream deep learning time series data regression algorithm, but the results are relatively unstable.

Use CSPResNeXt50 for image classification. An example is to use steel plate defect classification. You can use this APP to train your images for image classification.

Data classification analysis by using XGBoost.

The labeling software supports various common labeling formats such as PASCAL VOC, labelme, VIA JSON, etc.

The mainstream data regression algorithm.

Inheriting the algorithm MaskRCNN of FasterRCNN, it improves the original architecture and adds the part of Semantic Segmentation, which can segment, detect and classif

Russian Alexey Bochkovskiy, the maintainer of YOLO Darknet, found that the CSPNet detector developed by Wang Jianyao, the post-doc of the Chinese Academy of Sciences an