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 ...
IEEE

Multilevel Multimodal CNN–Transformer Fusion Network for Land Use and Land Cover Classification

Abstract: In remote sensing (RS), convolutional neural networks (CNNs) are well-recognized for their spatial–spectral feature extraction capabilities, whereas vision transformers (ViTs), which ...
IEEE

SV-RCNN: Robust Structural-Encoded Voxel Features for 3D Object Detection on Sparse Point Clouds

Abstract: 3D object detection in LiDAR point clouds faces significant challenges in sparse point clouds and unfamiliar environments. Existing methods often rely on simple multi-layer perceptrons or ...
IEEE

FG3DFormer: Fine-Grained 3D Shape Classification Based on Vision Transformer

Abstract: Fine-grained 3D shape classification (FGSC) remains challenging due to the difficulty of adaptively capturing global structure differences and subtle inter-class distinctions. This paper ...
IEEE

Swish-Cardioid CV-CNN: A Novel Complex-Valued Activation Framework for PolSAR Terrain Classification

Abstract: Activation functions are pivotal in complex-valued convolutional neural networks (CV-CNNs) as they govern the nonlinear learning of amplitude–phase relationships in polarimetric synthetic ...
IEEE

Custom Lightweight CNN and Data-Efficient Models for Efficient and Fast Convergence in Lung Cancer Classification

Abstract: Considering that lung cancer is the primary cause of cancer-related death across the globe, there are significant differences in patient outcomes as well as the subsequent clinical ...
IEEE

Efficient Document Classification Using Fused CNN-SVM Model

Abstract: Storing massive amounts of data in physical form, issuing and printing documents, then filing them is impractical, inefficient, and antiquated, for those reasons, organizations have ...