IEEE

A Real-Time AI-Driven Surgical Monitoring Platform Using Robotics, 3D Convolutional Neural Networks (3D-CNNs), and Bayesian Optimization for Enhanced Precision

Abstract: In this work proposed an AI powered surgical monitoring platform to enhance robotic precision-made using 3DCNNs and Bayesian optimization. For example, real time tracking of tools and tissue ...
Tech Xplore

VFF-Net algorithm provides promising alternative to backpropagation for AI training

Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn ...
IEEE

An SAGPSO-CNN Approach for Supervised Fault Classification in MVdc Shipboard Power Systems

Abstract: All-electric ships (AESs) utilizing medium-voltage dc (MVdc) shipboard power systems (SPSs) rely on a limited number of generators to supply power to propulsion units and onboard loads. To ...
IEEE

Deep Learning-Based Classification of Coconut Leaf Diseases Using Optimized CNN Models

Abstract: Leaf diseases of coconut severely affect the yield and quality of the crops. Early detection is imperative for any control measures to be effective. Here, an approach on the deep ...
IEEE

Hybrid DL Classification Model Based on CNN and Transformer for Pap Smear Cells

Abstract: Cervical cancer is a leading cause of cancer-related deaths among women, with early detection via Pap smear screening significantly reducing mortality. However, traditional analysis is ...
IEEE

Guiding the Classification of Hepatocellular Carcinoma on 3D CT-Scans Using Deep and Handcrafted Radiological Features

Abstract: Hepatocellular carcinoma is the most spread primary liver cancer across the world (~80% of the liver tumors). The gold standard for HCC diagnosis is liver biopsy. However, in the clinical ...