News-Medical.Net

CNN-based system improves lung nodule detection and classification

Lung cancer remains the leading cause of cancer-related mortality worldwide. Early detection of pulmonary nodules is crucial for timely diagnosis and effective treatment.
EurekAlert!

Enhanced Pulmonary Nodule Detection and Classification Using Artificial Intelligence on LIDC-IDRI Data (IMAGE)

The proposed CNN-based system demonstrates the feasibility and robustness of deep learning for automatic lung nodule detection and classification. Despite strong results, the study acknowledges ...
Mirage News

AI Boosts Lung Nodule Detection, Classification on LIDC Data

Lung cancer remains the leading cause of cancer-related mortality worldwide. Early detection of pulmonary nodules is crucial for timely diagnosis and ...

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

Optimizing Acne Diagnosis: A CNN-SVM Hybrid Framework for Accurate Classification of Acne Lesions

Abstract: A good study on the classification of acne focused on three types including nodules, blackheads, and papules. The results were excellent on all categories of the model; regarding nodules, ...
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 ...
IEEE

Comparative CNN-Based Models for Histopathological Image Analysis: A Study on Breast Cancer Identification

Abstract: In place of the low accuracy computer-aided diagnostic (CAD) systems created using conventional methods, deep learning-based breast cancer diagnosis has drawn a lot of attention.
IEEE

Multi-Scale Samples Transformer for Hyperspectral Image Classification

Abstract: Hyperspectral image (HSI) captures hundreds of narrow bands, offering abundant spatial and spectral information across various application domains. In recent years, deep learning techniques ...
IEEE

Hybrid Quantum-Classical Convolutional Neural Network (HQC-CNN) for Apple Leaf Disease Classification

Abstract: Reduced crop losses and guaranteeing agricultural productivity depend on the early and accurate detection of plant diseases. This work offers a Hybrid Quantum-Classical HQC-CNN, or ...
IEEE

Cross-Scene Hyperspectral Image Classification via Bidirectional Mamba and Domain Mixing Network

Abstract: To overcome the challenges posed by domain shift in hyperspectral image (HSI) classification, methods based on domain adaptation (DA) have been widely used. Currently, most HSI DA methods ...
Digital Trends

You can now use Gemini’s Thinking model without worrying about Pro model limits

Google has quietly reworked Gemini‘s usage limits, splitting the shared pool and boosting the individual caps for the Thinking and Pro models. At launch, both models had the same daily quota, meaning ...