IEEE

A Tree-Guided CNN for Image Super-Resolution

Abstract: Deep convolutional neural networks can extract more accurate structural information via deep architectures to obtain good performance in image super-resolution. However, it is not easy to ...
IEEE

Attention Integrated Residue CNN for Classification of DNA-Binding and RNA-Binding Proteins

Abstract: The classification of DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs) is essential for understanding molecular interactions and regulatory functions. However, the existing ...
IEEE

Hybrid CNN-Based Transfer Learning Enhances Brain Tumor Classification on MRI Images

Abstract: Brain tumors are among the deadliest diseases worldwide and require early and accurate diagnosis via Magnetic Resonance Imaging (MRI). Deep learning techniques, particularly convolutional ...
IEEE

Development of Robust CNN Architecture for Grading and Classification of Renal Cell Carcinoma Histology Images

Abstract: Kidney cancer is a commonly diagnosed cancer disease in recent years, and Renal Cell Carcinoma (RCC) is the most common kidney cancer responsible for 80% to 85% of all renal tumors. The ...
IEEE

Improving the Sound Classification Accuracy Using CNN-LSTM and MFCC with Audio Augmentation for Diagnosing Respiratory Disease

Abstract: Audio is vital information data for understanding various situations. A multitude of sound features can be explained by analysis through the audio signals. Numerous classification methods ...
IEEE

Fake Image Detection in Fake News Using Convolutional Neural Network (CNN)

Abstract: ’Fake news’ refers to false, inaccurate, or misleading information that spreads as real news. Fake news primarily aims to affect societies and individuals by spreading false or misleading ...
IEEE

FMCNN: Raw-Data Type Identification Using Feature Matrix and CNN

Abstract: This paper introduces FMCNN, a novel classification method that combines a two-dimensional feature matrix capturing raw data characteristics with a CNN-based classifier. Raw data are the ...
IEEE

Segmentation of Skin Lesions from Medical Images Using a Fusion of CNN and RNN Models

Abstract: The necessity for accurate detection of skin cancer has led to very significant advances in medical image analysis, mainly through the application of deep learning models. Detection of early ...
IEEE

Enhanced Lung Disease Classification Using CALMNet: A Hybrid CNN-LSTM-TimeDistributed Model for Respiratory Sound Analysis

Abstract: Lung diseases, such as asthma, pneumonia, and chronic obstructive pulmonary disease (COPD), pose considerable global health issues, making early diagnosis essential for effective treatment.
CNN

Scientist turns people’s mental images into text using ‘mind-captioning’ technology

A scientist in Japan has developed a technique that uses brain scans and artificial intelligence to turn a person’s mental images into accurate, descriptive sentences. While there has been progress in ...
aboutamazon

Project Kuiper is now Amazon Leo

Seven years ago, Amazon set out to design the most advanced satellite communications network ever built. Our vision was simple: There are still billions of people on the planet who lack high-speed ...