IEEE

Comparative Analysis of Machine Learning and Deep Learning Models for Land Use Classification: On UC Merced Dataset

Abstract: The UC Merced (UCM) land use dataset is a widely adopted benchmark for evaluating aerial image classification algorithms. This paper presents a comparative performance analysis of prominent ...
IEEE

A Fully Automated SPICE-Compatible Netlist Extraction From Image Using Deep Learning and Image Preprocessing Techniques

Abstract: This paper presents an automated framework for generating SPICE compatible netlists from both printed and hand-drawn circuit diagrams. The system combines advanced image preprocessing, deep ...
IEEE

An Improved Image Preprocessing Method for Defect Detection in Distribution Lines

Abstract: In this paper, we propose an improved image preprocessing method to address the challenges of low resolution, cluttered backgrounds, and susceptibility to lighting, occlusion, and weather ...
IEEE

Hybrid Integration of CNN and Kolmogorov–Arnold Networks for Multispectral Image Super-Resolution

Abstract: This letter proposes KAN-based multispectral image super-resolution method (KMSR), a novel deep learning framework for multispectral image (MSI) super-resolution (SR) that integrates ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
IEEE

Data-Driven Multi-keV Virtual Monoenergetic Images Generation from Single-Energy CT Guided by Image-Domain Material Decomposition

Abstract: Virtual monoenergetic images (VMIs), reconstructed from dual-energy CT (DECT) by capturing photon attenuation data at two distinct energy levels, can reduce beam-hardening artifacts and ...
Frontiers

A Hybrid CNN-LSTM approach for multi-step discharge forecasting with satellite data

The final, formatted version of the article will be published soon. An innovative hybrid forecasting model was developed to predict hourly river discharges up to 24 hours in advance. The proposed ...
IEEE

Preprocessing Methods for Memristive Reservoir Computing for Image Recognition

Abstract: Reservoir computing (RC) has attracted attention as an efficient recurrent neural network architecture due to its simplified training, requiring only its last perceptron readout layer to be ...
IEEE

Optimizing 2D CNN Architectures for Tabular IoT Intrusion Data: A Comparative Study Using the BoT-IoT 2020 Dataset

Abstract: The increasing number of Internet-enabled devices has demonstrated the need to have accurate intrusion detection systems (IDSs). To address this, we adapt the structure of two-dimensional ...
IEEE

Efficient Time-Frequency Image Recovery Method For Incomplete Data of Micro-Motion Targets

Abstract: Traditional time-frequency (TF) analysis methods for micromotion targets face significant challenges, including low resolution, susceptibility to noise interference, and issues arising from ...
IEEE

Hybrid Attention Driven CNN-Mamba Multimodal Fusion Network for Remote Sensing Image Semantic Segmentation

Abstract: In recent years, the increase of multimodal image data has offered a broader prospect for multimodal semantic segmentation. However, the data heterogeneity between different modalities make ...
IEEE

Lightweight CNN and Transfer Learning Techniques for Robust Small-Image Classification

Abstract: This study investigates the efficiency vs. accuracy trade-offs of these two approaches using the Fashion-MNIST benchmark. The study examined five models: LeNet-5 and an efficient CNN trained ...