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 ...
IEEE

Explainable Brain Tumor Classification using CNN and GradCAM

Abstract: One of the most critical neurological conditions is Brain tumors, timely and correct diagnosis is needed for effective treatment. Advances in neuroimaging technology such as MRI, limitations ...

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

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification BEIJING, Feb.06, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the ...
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

Brightness-Enhanced Gastrointestinal Endoscopy Image Classification Using CNN-Based Diagnostic Model

Abstract: This study proposes a framework based on a Cycle-Consistent Generative Adversarial Network (CycleGAN) to improve the image brightness and visual continuity of gastrointestinal (GI) ...
IEEE

S2CaT: Spatial-Spectral-based CNN and Transformer Network for Hyperspectral Image Classification

Abstract: Recent advancements in the field of hyperspectral image (HSI) analysis have highlighted the potential of hybrid architectures that integrate convolutional neural networks (CNNs) with ...
IEEE

An Optimized Multimodal Deep Learning Framework for Sentiment Classification using CNN-BiLSTM with FastText and GloVe Embeddings

Abstract: Multimodal Sentiment Analysis (MSA) is an advanced artificial intelligence technique that integrates text and image data to improve sentiment awareness, especially in practical scenarios ...
IEEE

Enhancing Lung Cancer Classification Using CNN and SVM Methods

As one of the most common and deadly types of cancer in the world, lung cancer continues to pose a serious threat to both healthcare systems and researchers. The prognosis of lung cancer patients ...