Deep Learning System

Deep learning systems are complex computational models designed to learn patterns from data, achieving high accuracy in various tasks like image recognition, natural language processing, and signal analysis. Current research emphasizes improving efficiency (reducing energy consumption), addressing biases in training data and model outputs, and enhancing interpretability to build trust and enable verification. These advancements are crucial for deploying deep learning reliably in safety-critical applications and mitigating potential societal impacts stemming from algorithmic bias, while also improving the efficiency and sustainability of these powerful tools.

Papers

March 5, 2023

Discrepancies among Pre-trained Deep Neural Networks: A New Threat to Model Zoo Reliability
Diego Montes, Pongpatapee Peerapatanapokin, Jeff Schultz, Chengjun Gun, Wenxin Jiang, James C. Davis
Deep Neural Network Deep Learning System DNN Architecture Task Discrepancy Model Zoo Pre Trained Deep Neural Network Model Reliability New Threat

March 2, 2023

Analyzing Effects of Fake Training Data on the Performance of Deep Learning Systems
Pratinav Seth, Akshat Bhandari, Kumud Lakara
Generative Adversarial Network Deep Learning Model Synthetic Data System Performance Deep Learning System

December 12, 2022

Siamese Neural Networks for Skin Cancer Classification and New Class Detection using Clinical and Dermoscopic Image Datasets
Michael Luke Battle, Amir Atapour-Abarghouei, Andrew Stephen McGough
Siamese Network Deep Learning System Skin Cancer Dermoscopic Image Clinical Language Skin Cancer Classification Class Detection

November 28, 2022

RAMP: A Flat Nanosecond Optical Network and MPI Operations for Distributed Deep Learning Systems
Alessandro Ottino, Joshua Benjamin, Georgios Zervas
Deep Learning System Optical Network Network Architecture Exascale Computing Diffractive Optical Network Connected Reconfiguration

October 31, 2022

minoHealth.ai: A Clinical Evaluation Of Deep Learning Systems For the Diagnosis of Pleural Effusion and Cardiomegaly In Ghana, Vietnam and the United States of America
Darlington Akogo, Benjamin Dabo Sarkodie, Issah Abubakari Samori, Bashiru Babatunde Jimah, Dorothea Akosua Anim, Yaw Boateng Mensah
Artificial Intelligence Chest X Ray Image Medical AI Deep Learning System Pneumothorax Segmentation Accurate Diagnosis Clinical Assessment Cardiomegaly Detection

October 23, 2022

O-type Stars Stellar Parameter Estimation Using Recurrent Neural Networks
Miguel Flores R., Luis J. Corral, Celia R. Fierro-Santillán, Silvana G. Navarro
Recurrent Neural Network Deep Learning System Stellar Parameter Stellar Spectrum

October 22, 2022

Diversity-Promoting Ensemble for Medical Image Segmentation
Mariana-Iuliana Georgescu, Radu Tudor Ionescu, Andreea-Iuliana Miron
Medical Image Segmentation Diverse Ensemble U Net Deep Learning System Gastrointestinal Tract Ensemble LLM Approach

October 17, 2022

How many radiographs are needed to re-train a deep learning system for object detection?
Raniere Silva, Khizar Hayat, Christopher M Riggs, Michael Doube
Chest X Ray Deep Learning System Computer Vision Application Shoulder Radiograph

September 21, 2022

Review On Deep Learning Technique For Underwater Object Detection
Radhwan Adnan Dakhil, Ali Retha Hasoon Khayeat
Deep Learning Narrative Review Underwater Environment Deep Learning System Underwater Object Detection Underwater Target

August 26, 2022

Concept-Based Techniques for "Musicologist-friendly" Explanations in a Deep Music Classifier
Francesco Foscarin, Katharina Hoedt, Verena Praher, Arthur Flexer, Gerhard Widmer
Line by Line Explanation Barzilai Borwein Technique Deep Learning System Symbolic Music Post Hoc Explanation Music Understanding Musical Data

August 20, 2022

A Domain Generalization Approach for Out-Of-Distribution 12-lead ECG Classification with Convolutional Neural Networks
Aristotelis Ballas, Christos Diou
Convolutional Neural Network Deep Neural Network Domain Generalization Deep Learning System ECG Datasets Biosignal Classification

August 18, 2022

Resisting Adversarial Attacks in Deep Neural Networks using Diverse Decision Boundaries
Manaar Alam, Shubhajit Datta, Debdeep Mukhopadhyay, Arijit Mondal, Partha Pratim Chakrabarti
Deep Neural Network Adversarial Attack Adversarial Example Adversarial Perturbation Decision Boundary Deep Learning System Ensemble Defense

August 11, 2022

Gaussian Process Surrogate Models for Neural Networks
Michael Y. Li, Erin Grant, Thomas L. Griffiths
Neural Network Gaussian Process Surrogate Model Deep Learning System

August 7, 2022

An example of use of Variational Methods in Quantum Machine Learning
Marco Simonetti, Damiano Perri, Osvaldo Gervasi
Quantum Machine Learning Greater Public Use Quantum Neural Network Variational Method Deep Learning System Hybrid Deep Learning Single Example Quantum Computation Lunar Surface

June 28, 2022

Learning Symmetric Rules with SATNet
Sangho Lim, Eun-Gyeol Oh, Hongseok Yang
Deep Learning System Parameter Learning Logical Puzzle

May 31, 2022

Hide and Seek: on the Stealthiness of Attacks against Deep Learning Systems
Zeyan Liu, Fengjun Li, Jingqiang Lin, Zhu Li, Bo Luo
Adversarial Sample New Attack Deep Learning System Digital STEALTH Metric Image Quality Metric

May 27, 2022

Comparison of Deep Learning Segmentation and Multigrader-annotated Mandibular Canals of Multicenter CBCT scans
Jorma Järnstedt, Jaakko Sahlsten, Joel Jaskari, Kimmo Kaski, Helena Mehtonen, Ziyuan Lin, Ari Hietanen, Osku Sundqvist, Vesa Varjonen, Vesa Mattila, Sangsom Prapayasotok, Sakarat Nalampang
Consistent Comparison Deep Learning System Cone Beam Computed Tomography Mandibular Canal

May 11, 2022

Performance of a deep learning system for detection of referable diabetic retinopathy in real clinical settings
Verónica Sánchez-Gutiérrez, Paula Hernández-Martínez, Francisco J. Muñoz-Negrete, Jonne Engelberts, Allison M. Luger, Mark J. J. P. van Grinsven
Data Detection System Performance Deep Learning System Real World Clinical Color Fundus

April 29, 2022

Tailored Uncertainty Estimation for Deep Learning Systems
Joachim Sicking, Maram Akila, Jan David Schneider, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel
Uncertainty Quantification High Uncertainty Anticipation Uncertainty Estimation Deep Learning System Uncertainty Estimation Method Estimation Performance

March 30, 2022

Mind the gap: Challenges of deep learning approaches to Theory of Mind
Jaan Aru, Aqeel Labash, Oriol Corcoll, Raul Vicente
Deep Learning Technical Challenge Theoretical Understanding Human Mind Deep Learning System

Deep Learning System

Papers

Discrepancies among Pre-trained Deep Neural Networks: A New Threat to Model Zoo Reliability

Analyzing Effects of Fake Training Data on the Performance of Deep Learning Systems

Siamese Neural Networks for Skin Cancer Classification and New Class Detection using Clinical and Dermoscopic Image Datasets

RAMP: A Flat Nanosecond Optical Network and MPI Operations for Distributed Deep Learning Systems

minoHealth.ai: A Clinical Evaluation Of Deep Learning Systems For the Diagnosis of Pleural Effusion and Cardiomegaly In Ghana, Vietnam and the United States of America

O-type Stars Stellar Parameter Estimation Using Recurrent Neural Networks

Diversity-Promoting Ensemble for Medical Image Segmentation

How many radiographs are needed to re-train a deep learning system for object detection?

Review On Deep Learning Technique For Underwater Object Detection

Concept-Based Techniques for "Musicologist-friendly" Explanations in a Deep Music Classifier

A Domain Generalization Approach for Out-Of-Distribution 12-lead ECG Classification with Convolutional Neural Networks

Resisting Adversarial Attacks in Deep Neural Networks using Diverse Decision Boundaries

Gaussian Process Surrogate Models for Neural Networks

An example of use of Variational Methods in Quantum Machine Learning

Learning Symmetric Rules with SATNet

Hide and Seek: on the Stealthiness of Attacks against Deep Learning Systems

Comparison of Deep Learning Segmentation and Multigrader-annotated Mandibular Canals of Multicenter CBCT scans

Performance of a deep learning system for detection of referable diabetic retinopathy in real clinical settings

Tailored Uncertainty Estimation for Deep Learning Systems

Mind the gap: Challenges of deep learning approaches to Theory of Mind