Latest Articles for Deep Neural Networks

FlexCHarts adapts search spaces for deep neural networks to improve efficiency and performance.

Exploring strategies to enhance machine learning models against harmful data attacks.

A look at RGD's impact on model performance and generalization.

This article discusses techniques for achieving accuracy and privacy in machine learning models.

A new method improves cell annotation in single-cell genomics.

Improving voice clarity through effective echo cancellation techniques and machine learning.

ReDy optimizes deep learning efficiency through dynamic quantization, reducing energy use.

A deep look at supervised contrastive loss and its impact on deep neural networks.

A method to find and fix errors in DNN model conversion.

Exploring how finite-time Lyapunov exponents reveal network sensitivity to input changes.

Introducing LWALM for effective pedestrian attribute recognition on resource-limited devices.

Research introduces efficient models for predicting ship orientation using deep learning techniques.

AIMC enhances efficiency in deep neural networks by processing data within memory.

Examining how BadNets exploit spam filters through backdoor tactics.

PLiNIO simplifies deep neural network optimization for mobile and edge devices.

Researchers explore defenses against harmful backdoor attacks on machine learning models.

A new method enhances solutions for complex multi-scale problems using neural networks.

This study compares methods for handling high-cardinality categorical variables in machine learning.

Innovative methods improve training efficiency in deep neural networks.

Using deep neural networks to analyze heat conduction data and identify potential functions.

A new approach improves deep learning models for nonparametric regression using adversarial training.

A novel method enhances DNN performance for real-world applications.

Examining the importance and techniques of route prediction in delivery services.

Advancements in DNNs aim to improve IoT device efficiency.

This article discusses STT-MRAM's benefits and challenges for deep neural networks.

A new layer enhances DNNs' resistance to subtle input changes.

A focus on trustworthiness in AI systems for reliable 6G communications.

Jade improves video quality through user feedback and adaptive streaming techniques.

Combining DNNs and SNNs with homomorphic encryption to ensure data privacy.

CLLD enhances lane detection under tough conditions using self-supervised learning.

Examining how model compression affects defenses against adversarial attacks.

A study introduces a model to improve identification of fake fingerprints.

Introducing a balanced approach to prune deep neural networks effectively.

A look at challenges and solutions in breast cancer screening methods.

LEAP improves adversarial testing for natural language processing software.

Research highlights the improvements AI can bring to hearing aids in noisy settings.

This method improves the classification of medical images using graph neural networks.

A look at methods for analyzing large spatial datasets and their challenges.

A look at strategies to improve DNN performance in real-time applications.

New method tackles overexposure issues in everyday video recording using deep learning.