Search
Search Results
-
Adaptive cluster-based superpixel segmentation and BMWMMBO-based DCNN classification for glaucoma detection
Glaucoma is a chronic disease called the silent thief of sight because it has no symptoms. When glaucoma is not identified at an early stage, it...
-
Superpixel Attack
Deep learning models are used in safety-critical tasks such as automated driving and face recognition. However, small perturbations in the model...
-
A Weakly Supervised Semantic Segmentation Method Based on Local Superpixel Transformation
Weakly supervised semantic segmentation (WSSS) can obtain pseudo-semantic masks through a weaker level of supervised labels, reducing the need for...
-
Improving SLIC superpixel by color difference-based region merging
Superpixel-based segmentation has been widely used as a primary prepossessing step to simplify the subsequent image processing tasks. Since...
-
A survey on the utilization of Superpixel image for clustering based image segmentation
Superpixel become increasingly popular in image segmentation field as it greatly helps image segmentation techniques to segment the region of...
-
Integrating self-organizing feature map with graph convolutional network for enhanced superpixel segmentation and feature extraction in non-Euclidean data structure
Deep learning has been widely used on Euclidean data type, and the deep learning architecture has made a breakthrough by the development of...
-
Weakly supervised semantic segmentation for skin cancer via CNN superpixel region response
Precise segmentation for skin cancer lesions at different stages is conducive to early detection and further treatment. We propose a weakly...
-
Superpixelwise PCA based data augmentation for hyperspectral image classification
Data Augmentation (DA) is significant for Hyperspectral Image (HSI) classification especially in the case of limited labeled training data. Various...
-
Pairwise-Pixel Self-Supervised and Superpixel-Guided Prototype Contrastive Loss for Weakly Supervised Semantic Segmentation
Semantic segmentation plays an important role in many fields because of its powerful ability to classify each pixel efficiently and accurately, but...
-
Application of Superpixel Clustering Algorithm to Hip Joint Image Segmentation Registration
Hip fracture is the most common and serious type of fracture in the elderly. The traditional orthopedic disease diagnosis method lacks sufficient...
-
Hypergraph convolutional network for hyperspectral image classification
Recently, graph-based neural networks have been investigated in hyperspectral image (HSI) classification to address the limited global feature...
-
Analyzing Pulmonary Abnormality with Superpixel Based Graph Neural Network in Chest X-Ray
In recent years, the utilization of graph-based deep learning has gained prominence, yet its potential in the realm of medical diagnosis remains...
-
Interpretability-Mask: a label-preserving data augmentation scheme for better classification
Data augmentation effectively alleviates the over-fitting problem in convolutional neural network-based (CNN-based) models, especially in the limited...
-
SPCC: A superpixel and color clustering based camouflage assessment
In the military field, camouflage assessment has significant study implications. In this research, a region segmentation algorithm based on...
-
A Two-Branch Neural Network Based on Superpixel Segmentation and Auxiliary Samples
Existing hyperspectral image (HSI) classification methods generally use the information in the neighborhood of the samples but seldom utilize the...
-
Membership Adjusted Superpixel Based Fuzzy C-Means for White Blood Cell Segmentation
Fuzzy C-means (FCM) is a well-known clustering technique that is efficiently used for image segmentation. However, the performance of the FCM...
-
Automatic brain tumor segmentation from magnetic resonance images using superpixel-based approach
Cancer is the second leading cause of deaths worldwide, reported by World Health Organization (WHO). The abnormal growth of cells, which should die...
-
Adaptive Compatibility Matrix for Superpixel-CRF
Compatibility Matrix plays a very important role in Fully-connected pairwise Conditional Random Field (full-CRF). However, former studies often fix...
-
Fire detection in video surveillance using superpixel-based region proposal and ESE-ShuffleNet
This paper proposes a forest fire detection framework using superpixel-based suspicious fire region proposal and light-weight convolutional neural...
-
Chaotic fitness-dependent quasi-reflected Aquila optimizer for superpixel based white blood cell segmentation
The crisp partitional clustering techniques like K-Means (KM) are an efficient image segmentation algorithm. However, the foremost concern with crisp...
