Compact Convolutional Transformer

Compact Convolutional Transformers (CCTs) are hybrid deep learning models combining the strengths of convolutional neural networks (CNNs) and vision transformers (ViTs) to achieve efficient and accurate image classification, particularly with limited data. Current research focuses on applying CCTs to various challenging tasks, including medical image analysis (e.g., Alzheimer's disease diagnosis, COVID-19 detection, blood cell classification) and industrial applications (e.g., wafer defect recognition), leveraging their ability to capture both local and global features. The success of CCTs in these domains highlights their potential to improve the accuracy and efficiency of image-based analysis in diverse fields where large datasets are scarce or unavailable.

Papers

May 8, 2024

Few-Shot Class Incremental Learning via Robust Transformer Approach
Naeem Paeedeh, Mahardhika Pratama, Sunu Wibirama, Wolfgang Mayer, Zehong Cao, Ryszard Kowalczyk
Convolutional Neural Network Incremental Learning Class Incremental Learning Robust Transformer Compact Convolutional Transformer

March 24, 2024

Enhancing MRI-Based Classification of Alzheimer's Disease with Explainable 3D Hybrid Compact Convolutional Transformers
Arindam Majee, Avisek Gupta, Sourav Raha, Swagatam Das
Convolutional Neural Network Deep Learning Model Classification Code Alzheimer'S Disease Common Disease 3d Mri Compact Convolutional Transformer

July 1, 2023

More for Less: Compact Convolutional Transformers Enable Robust Medical Image Classification with Limited Data
Andrew Kean Gao
Vision Transformer Medical Image Classification Convolutional Layer Limited Data Compact Convolutional Transformer

March 24, 2023

Efficient Mixed-Type Wafer Defect Pattern Recognition Using Compact Deformable Convolutional Transformers
Nitish Shukla
Defect Pattern Wafer Defect Compact Convolutional Transformer Semiconductor Wafer Wafer Map Defect Pattern

November 4, 2022

SPEAKER VGG CCT: Cross-corpus Speech Emotion Recognition with Speaker Embedding and Vision Transformers
A. Arezzo, S. Berretti
Convolutional Neural Network Vision Transformer Speech Emotion Recognition Speaker Embeddings Speech Signal Cross Corpus Speech Emotion Recognition Compact Convolutional Transformer

September 27, 2022

CCTCOVID: COVID-19 Detection from Chest X-Ray Images Using Compact Convolutional Transformers
Abdolreza Marefat, Mahdieh Marefat, Javad Hasannataj Joloudari, Mohammad Ali Nematollahi, Reza Lashgari
Transformer Based Medical Image Covid 19 Chest X Ray Image COVID 19 Detection Infected Individual Compact Convolutional Transformer

Compact Convolutional Transformer

Papers

Few-Shot Class Incremental Learning via Robust Transformer Approach

Enhancing MRI-Based Classification of Alzheimer's Disease with Explainable 3D Hybrid Compact Convolutional Transformers

More for Less: Compact Convolutional Transformers Enable Robust Medical Image Classification with Limited Data

Efficient Mixed-Type Wafer Defect Pattern Recognition Using Compact Deformable Convolutional Transformers

SPEAKER VGG CCT: Cross-corpus Speech Emotion Recognition with Speaker Embedding and Vision Transformers

CCTCOVID: COVID-19 Detection from Chest X-Ray Images Using Compact Convolutional Transformers