3d CNN

3D convolutional neural networks (CNNs) process three-dimensional data, enabling analysis of volumetric information like medical images and point clouds. Current research emphasizes improving 3D CNN efficiency and accuracy through architectural innovations such as incorporating attention mechanisms, hybrid models combining 2D and 3D CNNs, and exploring alternative training strategies like contrastive learning. These advancements are significantly impacting fields like medical image analysis (e.g., Alzheimer's disease diagnosis, tumor detection), autonomous driving (3D object detection), and video analysis (deepfake detection), offering improved diagnostic tools and enhanced perception capabilities.