IEEE

EffiSegNet: Gastrointestinal Polyp Segmentation through a Pre-Trained EfficientNet-based Network with a Simplified Decoder

Abstract: This work introduces EffiSegNet, a novel segmentation framework leveraging transfer learning with a pre-trained Convolutional Neural Network (CNN) classifier as its backbone. Deviating from ...
IEEE

Brain Tumor Detection Using Convolutional Neural Network

Abstract: One of the most significant and difficult issues in medical image processing is brain tumor segmentation (BTS) as human classification might cause improper diagnosis and prognosis.
IEEE

Multiagent Sensor Integration and Knowledge Distillation System for Real-Time Autonomous Vehicle Navigation

Abstract: This article introduces a comprehensive multiagent prototype system designed to enhance the autonomous navigation capabilities of vehicles by incorporating numerous sensors and components.
IEEE

Enhancing Fault Detection and Classification in Wind Farm Power Generation Using Convolutional Neural Networks (CNN) by Leveraging LVRT Embedded in Numerical Relays

Abstract: Real-time fault detection and classification are important for power system stability and resilience of the power grid to minimize downtime and prevent cascading failures. Numerical relays ...
IEEE

Comparative Analysis of SVM and CNN Classifiers for EEG Signal Classification in Response to Different Auditory Stimuli

Abstract: This study aims to classify brainwave patterns using electroencephalogram (EEG) signals in response to various auditory stimuli, specifically Quran recitation, participants’ favorite music, ...
IEEE

Hybrid CNN-Ensemble Framework for Robust Floral Species Recognition

Abstract: This study introduces a sophisticated floral identification system based on Deep Learning and Machine Learning to improve species classification accuracy. The system combines VGG16 CNN for ...
IEEE

Ensemble Learning for Wafer Defect Pattern Classification in the Semiconductor Industry

Abstract: During semiconductor manufacturing, wafer defect patterns emerge in an uncontrolled environment, making immediate recognition challenging. To enhance the classification accuracy in pattern ...
IEEE

Comparison of Finger Motion Classifiers With Respect to Number and Location of Tactile Sensors

Abstract: This study investigates the performance of AI classifiers in classifying motions of individual fingers for prosthetic hand using a varying number of tactile sensors. Specifically, we compare ...