Physics World

Hybrid deep-learning model eases brachytherapy planning

The BCTVNet neural network provides accurate and rapid target volume delineation for cervical cancer brachytherapy ...

Researchers co-develop new deep learning platform to advance precision medicine

Researchers from Marshall University and the University of Missouri have developed G2PDeep, an innovative web-based platform ...
Scientific Research Publishing

Applying Deep Learning Techniques for Automated Analysis and Interpretation of Financial Statements ()

Multimodal Learning, Deep Learning, Financial Statement Analysis, LSTM, FinBERT, Financial Text Mining, Automated ...
IEEE

Ensemble Deep Learning Models for Enhanced Brain Tumor Classification by Leveraging ResNet50 and EfficientNet-B7 on High-Resolution MRI Images

Abstract: Brain tumors are among the most significant and challenging medical conditions because of their sometimes-fatal outcomes and complexity of treatment options. Early, exact detection of brain ...
Bulletin of the Atomic ScientistsOpinion

Division begets division in the age of algorithmic classification

The online information landscape, driven in large part by social media, rewards engagement and is curated by classification ...
TMCnet

WiMi Studies Hybrid Quantum-Classical Learning Architecture for Multi-Class Image Classification

In this architecture, the training process adopts a joint optimization mechanism based on classical cross-entropy loss. WiMi treats the measurement probability distribution output by the quantum ...

Lingyun Lai Enhances Data Security Evaluation with Deep Learning and Hierarchical Analytical Frameworks

Research combining deep learning methodologies with Analytic Hierarchy Process establishes comprehensive frameworks for data security risk ...
IEEE

Evaluating Pretrained Deep Learning Models for Image Classification Against Individual and Ensemble Adversarial Attacks

Abstract: The robustness of Deep Neural Networks (DNNs) against adversarial attacks is an important topic in the area of deep learning. To fully investigate the robustness of DNNs, this study examines ...