IEEE

Analyzing the Effectiveness of Ensemble Methods in Solving Multi-Class Classification Problems

Abstract: In this research work, ensemble methods for analyzing classification problems were analyzed. Currently, various methods and algorithms are proposed and implemented based on machine systems ...
IEEE

EG-VAN: A Global and Local Attention-Based Dual-Branch Ensemble Network With Advanced Color Balancing for Multi-Class Skin Cancer Recognition

Abstract: The accurate diagnosis of skin cancer remains challenging due to factors like intra-class variation and inter-class similarity in dermoscopic images. Despite their sophistication, existing ...
IEEE

Enumerating the K-Fold Configurations in Multi-Class Classification Problems

Abstract: K-fold cross-validation is a widely used tool for assessing classifier performance. The reproducibility crisis [6] faced by artificial intelligence partly results from the irreproducibility ...
IEEE

Multi Class Spectral Discriminative Convolutional Neural Network Towards Hyperspectral Image Classification of Crop Disease on Inclusion of Spectral Spatial Feature Fusion ...

Abstract: Crop diseases occurs due to bacterial, viral, parasitic and fungal infection leads to various challenges to farmer and agricultural based business as crop diseases effects the normal growth ...
IEEE

Attention-Enhanced Dual-Path CNN for Early Alzheimer’s Detection From Multi-Planar T1-Weighted MRI

Abstract: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder, and early detection is essential for effective clinical intervention. Previous deep learning approaches have achieved ...
IEEE

Adaptive Tracking Control of Nonlinear Multi-Agent Systems Subject to Multiple Constraints via Multi-Dimensional Taylor Network

Abstract: This paper investigates the adaptive tracking control problem for nonlinear multi-agent systems operating under simultaneous input saturation and output performance constraints. To address ...
IEEE

An Efficient Ensemble Deep Learning Comparative Study Based on Multi-Class Classifications of Brain Tumors Using Brain MRI Images

Abstract: Brain tumors are a severe health problem that requires accurate diagnosis and classification for optimal treatment. Magnetic resonance imaging (MRI) is a widely used technique for detecting ...
CBS News

At least 4 killed, 8 injured in "act of targeted violence" at Michigan church; suspect dead

Joe Buczek is manager of digital content and promotion at CBS Detroit. He previously worked at WWTV, the Grand Traverse Insider, the Leader and the Kalkaskian, the Oakland Press and the Morning Sun.
GitHub

VeloxSeg: Johnson-Lindenstrauss Lemma Guided Network for Efficient 3D Medical Segmentation

Overview of VeloxSeg. VeloxSeg employs an encoder-decoder architecture with Paired Window Attention (PWA) and Johnson-Lindenstrauss lemma-guided convolution (JLC) on the left, using 1x1 convolution as ...
IEEE

Design of a CNN Accelerator for Multitask EEG Signal Classification Based on RISC-V

Abstract: Electroencephalogram (EEG) has been widely employed in emotion recognition, seizure detection, and brain-computer interface applications. This article presents an elaborated RISC-V-based EEG ...
IEEE

Deep Learning for Multi-Class DDoS Detection in SDNs: A CNN-LSTM Based Approach

Abstract: Recently Distributed Denial of Service (DDoS) attacks have increased extensively, taking about 35% of all cyber threats among which the attack characteristic rises around 300% within the ...