FUSECAPS: Investigating Feature Fusion Based Framework for Capsule Endoscopy Image Classification
In order to improve model accuracy, generalization, and class imbalance issues, this work offers a strong methodology for classifying endoscopic images. We suggest a hybrid feature extraction method that combines convolutional neural networks (CNNs), multi-layer perceptrons (MLPs), and radiomics. Rich, multi-scale feature extraction is made possible by this combination, which captures both deep and handmade representations. These features are then used by a classification head to classify diseases, producing a model with higher generalization and accuracy. In this framework we have achieved a validation accuracy of 76.2% in the capsule endoscopy video frame classification task.
Code (0)
등록된 구현이 없습니다.
Tasks
image-classificationImage ClassificationSimilar Papers 제목 키워드 기반
Investigating Capsule Networks with Dynamic Routing for Text Classification
In this study, we explore capsule networks with dynamic routing for text classification. We propose three strategies to stabilize the dynamic routing process to alleviate the disturbance of some noise capsules which may …
ClassificationGeneral ClassificationMulti-Label Text ClassificationSentiment Analysis+2Action Capsules: Human Skeleton Action Recognition
Due to the compact and rich high-level representations offered, skeleton-based human action recognition has recently become a highly active research topic. Previous studies have demonstrated that investigating joint rela…
Action RecognitionSkeleton Based Action RecognitionTemporal Action LocalizationRetinal Vessel Segmentation with Deep Graph and Capsule Reasoning
Effective retinal vessel segmentation requires a sophisticated integration of global contextual awareness and local vessel continuity. To address this challenge, we propose the Graph Capsule Convolution Network (GCC-UNet…
Graph AttentionImage SegmentationMedical Image SegmentationRetinal Vessel Segmentation+2Investigating Capsule Network and Semantic Feature on Hyperplanes for Text Classification
As an essential component of natural language processing, text classification relies on deep learning in recent years. Various neural networks are designed for text classification on the basis of word embedding. However,…
ClassificationGeneral Classificationtext-classificationText ClassificationUnsupervised multi-branch Capsule for Hyperspectral and LiDAR classification
With the convenient availability of remote sensing data, how to make models to interpret complex remote sensing data attracts wide attention. In remote sensing data, hyperspectral images contain spectral information and …
Classification