IEEE

Hierarchical Feature Fusion CNN: Fast Intra Prediction Mode Decision for VVC Screen Content Coding

Abstract: Versatile Video Coding (VVC) inherits Screen Content Coding (SCC) tools such as Intra Block Copy (IBC) and Palette mode (PLT) from High Efficiency Video Coding Screen Content Coding ...
IEEE

A Frequency Adaptive Vibration Analysis Method for Variable Speed Rotating RV Reducer

Abstract: Industrial robots commonly perform cyclic reciprocating motions during operation. The dynamic loads caused by frequent acceleration and deceleration make the RV reducers of the robots prone ...
IEEE

Pattern-Based Feature Extraction for Improved Deep Learning in Financial Time Series Classification

Abstract: In this paper, the authors introduce a novel feature extraction method based on pattern detection in financial data to enhance the performance of deep learning models for financial time ...
IEEE

MHAFF: Multihead Attention Feature Fusion of CNN and Transformer for Cattle Identification

Abstract: Convolutional neural networks (CNNs) have drawn researchers’ attention to identifying cattle using muzzle images. However, CNNs often fail to capture long-range dependencies within the ...
IEEE

Enhancing Soybean Disease Diagnosis using CNN-based Feature Extraction and Random Forest Classification

Abstract: Soybean plants are highly susceptible to various diseases, impacting crop yield and quality. Accurate and early detection of these diseases is essential for effective management and ...
IEEE

Neuroimaging Feature Extraction Meets Clinical Data Integration: A CNN-RF Hybrid for Parkinson’s Classification

Abstract: Parkinson is a multifactorial chronic neurodegenerative disease that needs proper diagnosis and especially at the early stages of the disease. This work aims to develop a new Hybrid CNN-RF ...
IEEE

SCFNet:A Swin-CNN Synergistic Fusion Network For Urban and Rural Water Extraction In Remote Sensing Images

Accurate monitoring of water resources is essential for disaster risk reduction and sustainable development amid global climate change. At present, various methods based on convolutional neural ...
IEEE

Hierarchical Feature Matching via Structure-Semantic Separation for Road Extraction

Abstract: Road information derived from remote sensing images is extensively utilized across various fields. Traditionally, road extraction methods relied predominantly on manually designed features, ...
IEEE

MFENet: A Multi-Feature Extraction Network for Enhanced Emotion Detection Using EEG and STFT

Abstract: Developing computationally efficient models for EEG-based emotion recognition is essential for enabling scalable and responsive brain-computer interface (BCI) systems. However, the inherent ...
IEEE

Gram–Schmidt Methods for Unsupervised Feature Extraction and Selection

Abstract: Feature extraction and selection in the presence of nonlinear dependencies among the data is a fundamental challenge in unsupervised learning. We propose using a Gram-Schmidt (GS) type ...
IEEE

FCTFANet: A Fused CNN-Transformer Feature Aggregator Network for Image Restoration

Abstract: Convolutional neural networks (CNNs) have been foundational in deep learning architectures for image processing, and recently, Transformer networks have emerged, bringing further ...
IEEE

A Hybrid Framework for Acute Lymphoblastic Leukemia Identification Utilizing VIT-CNN Fusion and Immunologically Inspired Deep Feature Selection

Abstract: Acute Lymphoblastic Leukemia (ALL) is a serious blood cancer characterized by the abnormal growth of progenitor white blood cells, which interferes with normal blood cell production. Early ...