In this video, we will understand the complete CNN Architecture. A CNN architecture represents the design of the CNN. CNN architecture consists of Convolutional Layers, Pooling Layers, and fully ...

I’m trying to use ZigZag to evaluate different mapping strategies for different types of convolution layers (e.g., standard convolution vs. depthwise convolution).

Background: Accurate segmentation and classification of carotid plaques are critical for assessing stroke risk. However, conventional methods are hindered by manual intervention, inter-observer ...

You can create a release to package software, along with release notes and links to binary files, for other people to use. Learn more about releases in our docs.

Abstract: Melanoma is the most lethal skin cancer nowadays, but an early diagnosis can considerably boost the survival rate and cure rate. Convolutional neural network (CNN) can be implied on medical ...

Epilepsy detection using artificial intelligence (AI) networks has gained significant attention. However, existing methods face challenges in accuracy, computational cost, and speed. CNN excel in ...

In response to the challenges of small object detection in UAV aerial photography, such as complex backgrounds, tiny targets, dense targets, and edge deployment, the YOLOv11n model was improved.

Skin conditions are a worldwide health issue that requires prompt and accurate diagnosis in order to be effectively treated. This study presents a Convolutional Neural Network (CNN)-based automated ...