IEEE

A Novel Transformer-CNN Hybrid Deep Learning Architecture for Robust Broad-Coverage Diagnosis of Eye Diseases on Color Fundus Images

Abstract: We present a novel and robust deep-learning architecture that takes into account the pathological characteristics of eye diseases on color fundus images. The proposed hybrid architecture is ...
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

Few-Shot Learning Based on Multilevel Contrast for Cross-Domain Hyperspectral Image Classification

Abstract: Recently, domain adaptation techniques have been introduced for cross-domain few-shot hyperspectral image (HSI) classification tasks, but effectively aligning the source and target domains ...
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 ...
IEEE

A Robust Hybrid CNN+ViT Framework for Breast Cancer Classification Using Mammogram Images

Abstract: Breast cancer is the most frequent type of cancer largely experienced by women currently, although it could happen to men also. It appears when abnormal breast tissue cells grow rapidly and ...
IEEE

Analysis of Image Classification using CNN and ANN

Abstract: This assignment investigates the usage of (CNN) and synthetic neural networks (ANN) for picture classification. We compare the overall performance of these strategies for my part and ...
KRDO

Jay Jones will become Virginia’s next attorney general, CNN projects, overcoming disclosure of violent text messages

(CNN) — Democrat Jay Jones will win the race to become Virginia’s next attorney general, CNN’s Decision Desk projects, overcoming the disclosure of text messages in which he suggested a former ...
IEEE

Lightweight Deep Learning Model for Breast Cancer Malignancy Prediction Using CNN on Embedded Edge Devices

Accurate diagnosis of breast cancer in a timely manner will be a key step to have the right treatment. This study suggests a minimalistic CNN architecture for malignancy prediction intended to be ...
IEEE

Dual-Branch Residual CNN-LSTM Model for Emotion Classification using PPG and GSR

Abstract: Emotion recognition using bio-signals such as photoplethysmography (PPG) and galvanic skin response (GSR) is a practical and efficient approach compared to other bio-signals like EEG and EMG ...