International Conference on Computer and Knowledge Engineering

Home / 13th International Conference on Computer and Knowledge Engineering

Capturing Local and Global Features in Medical Images by Using Ensemble CNN-Transformer

Authors :

Javad Mirzapour Kaleybar¹ Hooman Saadat² Hooman Khaloo³

1- Department of Computer Engineering, University College of Nabi Akram, Tabriz, Iran 2- Department of Electrical Engineering, Qazvin Branch, Iran 3- School of Technology Sharif University, Tehran, Iran

Keywords :

Medical Image Analysis،Transformer،Convolutional Neural Network،Deep Learning

Abstract :

This research paper addresses the challenges associated with traffic sign detection in self-driving vehicles and driver assistance systems. The development of reliable and highly accurate algorithms is crucial for the widespread adoption of traffic sign recognition and detection (TSRD) in diverse real-life scenarios. However, this task is complicated by suboptimal traffic images affected by factors such as camera movement, adverse weather conditions, and inadequate lighting. This study specifically focuses on traffic sign detection methods and introduces the application of the Transformer model, particularly the Vision Transformer variants, to tackle this task. The Transformer's attention mechanism, originally designed for natural language processing, offers improved parallel efficiency. Vision Transformers have demonstrated success in various domains, including autonomous driving, object detection, healthcare, and defense-related applications. To enhance the efficiency of the Transformer model, the research proposes a novel strategy that integrates a locality inductive bias and a transformer module. This includes the introduction of the Efficient Convolution Block and the Local Transformer Block, which effectively capture short-term and long-term dependency information, thereby improving both detection speed and accuracy. Experimental evaluations demonstrate the significant advancements achieved by this approach, particularly when applied to the German Traffic Sign Detection dataset.

Papers List

List of archived papers

Automating Theory of Mind Assessment with a LLaMA-3-Powered Chatbot: Enhancing Faux Pas Detection in Autism

Avisa Fallah - Ali Keramati - Mohammad Ali Nazari - Fatemeh Sadat Mirfazeli

A Formalism for Specifying Capability-based Task Allocation in MAS

Samaneh HoseinDoost - Bahman Zamani - Afsaneh Fatemi

Real-time Implementation of Fuzzy Visual Servoing for a Delta Robot via Shape and Color Detection

Nooshin Najafian - Alireza Ashrafi Majd - Abbas Ansaroudi - Sahar Aghazadeh - Manizheh Zakeri - Mohammad-Reza Sayyed Noorani

A 2D-CNN Architecture for Improving the Classification Accuracy of an Electronic Nose with Different Sensor Positions

Hannaneh Mahdavi - Reza Goldoust - Saeideh Rahbarpour

T-Rank: Graph Data Analytics for Urban Traffic Modeling

Alireza Safarpour - Iman Gholampour - Amirhossain Aghazadeh Fard - Seyed Mohammad Karbasi

Pruning and Mixed Precision Techniques for Accelerating Neural Network

Mahsa Zahedi - Mohammad Sediq Abazari Bozhgani - Abdorreza Savadi

Using Deep Learning for Classification of Lung Cancer on CT Images in Ardabil Province

Mohammad Ali Javadzadeh Barzaki - Jafar Abdollahi - Mohammad Negaresh - Maryam Salimi - Hadi Zolfeghari - Mohsen Mohammadi - Asma Salmani - Rona Jannati - Firouz Amani

InfOnto: An ontology for fashion influencer marketing based on Instagram

Somaye Sultani - Mohsen Kahani

Automatic Infrared-Based Volume and Mass Estimation System for Agricultural Products

Seyed Muhammad Hossein Mousavi - S. Muhammad Hassan Mosavi

Crack Segmentation in Civil Structure Images Using a Deep Learning Based Multi-Classifier System

Mohammadreza Asadi - Seyedeh Sogand Hashemi - Mohammad Taghi Sadeghi