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Methods/SegNet

SegNet

Computer VisionIntroduced 200081 papers

Description

SegNet is a semantic segmentation model. This core trainable segmentation architecture consists of an encoder network, a corresponding decoder network followed by a pixel-wise classification layer. The architecture of the encoder network is topologically identical to the 13 convolutional layers in the VGG16 network. The role of the decoder network is to map the low resolution encoder feature maps to full input resolution feature maps for pixel-wise classification. The novelty of SegNet lies is in the manner in which the decoder upsamples its lower resolution input feature maps. Specifically, the decoder uses pooling indices computed in the max-pooling step of the corresponding encoder to perform non-linear upsampling.

Papers Using This Method

Determination Of Structural Cracks Using Deep Learning Frameworks2025-07-03 U-NetMN and SegNetMN: Modified U-Net and SegNet models for bimodal SAR image segmentation2025-06-05 Med-2D SegNet: A Light Weight Deep Neural Network for Medical 2D Image Segmentation2025-04-20 Role of the Pretraining and the Adaptation data sizes for low-resource real-time MRI video segmentation2025-02-20 Optimized Unet with Attention Mechanism for Multi-Scale Semantic Segmentation2025-02-06 Synesthesia of Machines Based Multi-Modal Intelligent V2V Channel Model2025-01-13 Multimodality Helps Few-Shot 3D Point Cloud Semantic Segmentation2024-10-29 Deep Learning tools to support deforestation monitoring in the Ivory Coast using SAR and Optical satellite imagery2024-09-16 Post-Mortem Human Iris Segmentation Analysis with Deep Learning2024-08-06 An Enhanced Encoder-Decoder Network Architecture for Reducing Information Loss in Image Semantic Segmentation2024-05-26 Hybrid Multihead Attentive Unet-3D for Brain Tumor Segmentation2024-05-22 Hierarchical SegNet with Channel and Context Attention for Accurate Lung Segmentation in Chest X-ray Images2024-05-20 Medical Image Analysis for Detection, Treatment and Planning of Disease using Artificial Intelligence Approaches2024-05-18 Intra-operative tumour margin evaluation in breast-conserving surgery with deep learning2024-04-16 Fuzzy Rank-based Late Fusion Technique for Cytology image Segmentation2024-03-16 Moving Object Proposals with Deep Learned Optical Flow for Video Object Segmentation2024-02-14 A knowledge-based data-driven (KBDD) framework for all-day identification of cloud types using satellite remote sensing2023-12-01 IARS SegNet: Interpretable Attention Residual Skip connection SegNet for melanoma segmentation2023-10-31 Equirectangular image construction method for standard CNNs for Semantic Segmentation2023-10-13 Image Segmentation Keras : Implementation of Segnet, FCN, UNet, PSPNet and other models in Keras2023-07-25