Classification Code

Classification code research focuses on developing and improving algorithms and models to accurately assign data points to predefined categories. Current efforts concentrate on addressing challenges like imbalanced datasets, noisy data, and limited labeled data through techniques such as self-supervised pre-training, robust loss functions, and the application of diverse architectures including convolutional neural networks (CNNs), transformers, and novel approaches like Mamba. These advancements have significant implications across various fields, improving accuracy and efficiency in applications ranging from medical image analysis and bioacoustic monitoring to cybersecurity threat detection and scientific literature organization.

Papers

June 9, 2022

DeepVerge: Classification of Roadside Verge Biodiversity and Conservation Potential
Andrew Perrett, Charlie Barnes, Mark Schofield, Lan Qie, Petra Bosilj, James M. Brown
Classification Code Biodiversity Loss Endangered Specie Wildlife Fence

June 8, 2022

Classification of Stochastic Processes with Topological Data Analysis
İsmail Güzel, Atabey Kaygun
Machine Learning Classification Code Time Series Topological Data Analysis Topological Feature Stochastic Process Balanced Sampling

June 6, 2022

Topological Optimized Convolutional Visual Recurrent Network for Brain Tumor Segmentation and Classification
Dhananjay Joshi, Kapil Kumar Nagwanshi, Nitin S. Choubey, Naveen Singh Rajput
Classification Code Deep Convolutional Neural Network Brain Tumor Segmentation Topological Feature Brain Tumor Convolutional Recurrent Neural Network

June 4, 2022

Classification at the Accuracy Limit -- Facing the Problem of Data Ambiguity
Claus Metzner, Achim Schilling, Maximilian Traxdorf, Konstantin Tziridis, Holger Schulze, Patrick Krauss
Classification Code Back Propagation Right Problem Classification Problem Classification Accuracy Accuracy Constraint Ambiguous Data

June 2, 2022

June 1, 2022

Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models
Kaiyue Wen, Jiaye Teng, Jingzhao Zhang
Deep Learning Model Classification Code Supervised ImageNet Large Model ResNet Based Benign Overfitting ImageNet Accuracy

May 31, 2022

May 30, 2022

May 29, 2022

Saliency Map Based Data Augmentation
Jalal Al-afandi, Bálint Magyar, András Horváth
Neural Network Data Augmentation Classification Code Saliency Map Classification Task

May 28, 2022

Optimal Decision Diagrams for Classification
Alexandre M. Florio, Pedro Martins, Maximilian Schiffer, Thiago Serra, Thibaut Vidal
Classification Code Decision Tree Decision Diagram Mathematical Programming

May 27, 2022

May 26, 2022

Unequal Covariance Awareness for Fisher Discriminant Analysis and Its Variants in Classification
Thu Nguyen, Quang M. Le, Son N. T. Tu, Binh T. Nguyen
Classification Code Covariance Matrix Natural Language Oriented Variant Quadratic Discriminant Analysis Fisher Information Metric Cross Covariance

Classification Code

Papers

DeepVerge: Classification of Roadside Verge Biodiversity and Conservation Potential

Classification of Stochastic Processes with Topological Data Analysis

Topological Optimized Convolutional Visual Recurrent Network for Brain Tumor Segmentation and Classification

Classification at the Accuracy Limit -- Facing the Problem of Data Ambiguity

Rashomon Capacity: A Metric for Predictive Multiplicity in Classification

A Deep Learning Network for the Classification of Intracardiac Electrograms in Atrial Tachycardia

Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models

Classification of EEG Motor Imagery Using Deep Learning for Brain-Computer Interface Systems

AI-based automated Meibomian gland segmentation, classification and reflection correction in infrared Meibography

Pseudo-Data based Self-Supervised Federated Learning for Classification of Histopathological Images

Zero-Shot and Few-Shot Learning for Lung Cancer Multi-Label Classification using Vision Transformer

Going Beyond One-Hot Encoding in Classification: Can Human Uncertainty Improve Model Performance?

Saliency Map Based Data Augmentation

Optimal Decision Diagrams for Classification

LiVeR: Lightweight Vehicle Detection and Classification in Real-Time

Classification of COVID-19 Patients with their Severity Level from Chest CT Scans using Transfer Learning

Unequal Covariance Awareness for Fisher Discriminant Analysis and Its Variants in Classification

Machine learning method for return direction forecasting of Exchange Traded Funds using classification and regression models

COVID-19 Severity Classification on Chest X-ray Images

Augmentation-induced Consistency Regularization for Classification