Deep Learning

Deep learning, a subfield of machine learning, focuses on training artificial neural networks with multiple layers to extract complex patterns from data. Current research emphasizes improving model robustness against noisy or adversarial inputs, exploring efficient architectures like Vision Transformers and convolutional LSTMs for various tasks (e.g., image classification, time series forecasting), and integrating physics-informed approaches for enhanced interpretability and reliability. These advancements are significantly impacting diverse fields, from automated industrial inspection and medical image analysis to improved weather forecasting and more efficient content moderation systems.

Papers

May 23, 2024

Feature Fusion for Improved Classification: Combining Dempster-Shafer Theory and Multiple CNN Architectures
Ayyub Alzahem, Wadii Boulila, Maha Driss, Anis Koubaa
Deep Learning Pre Trained Feature Fusion Cifar 10 Dempster Shafer Theory Improved Classification
Neuroexplicit Diffusion Models for Inpainting of Optical Flow Fields
Tom Fischer, Pascal Peter, Joachim Weickert, Eddy Ilg
Deep Learning Convolutional Neural Network Diffusion Probabilistic Model Neural Diffusion GAN Baseline Optical Flow Field
Nuclear Norm Regularization for Deep Learning
Christopher Scarvelis, Justin Solomon
Deep Learning Large Matrix Jacobian Computation Nuclear Norm Regularization
Does context matter in digital pathology?
Paulina Tomaszewska, Mateusz Sperkowski, Przemysław Biecek
Deep Learning Artificial Intelligence Context Information Digital Pathology Contextual Information Artefact PARTICLE
Deep Learning Methods for Adjusting Global MFD Speed Estimations to Local Link Configurations
Zhixiong Jin, Dimitrios Tsitsokas, Nikolas Geroliminis, Ludovic Leclercq
Deep Learning World Event Traffic Management Macroscopic Model Speed Estimation
Advancements in Feature Extraction Recognition of Medical Imaging Systems Through Deep Learning Technique
Qishi Zhan, Dan Sun, Erdi Gao, Yuhan Ma, Yaxin Liang, Haowei Yang
Deep Learning Hyperspectral Image Feature Extraction Linear Classifier Discriminant Analysis Unsupervised Medical
Real Time Deep Learning Weapon Detection Techniques for Mitigating Lone Wolf Attacks
Kambhatla Akhila, Khaled R Ahmed
Deep Learning Object Detector R CNN Faster RCNN Weapon Detection
Deep Learning for Protein-Ligand Docking: Are We There Yet?
Alex Morehead, Nabin Giri, Jian Liu, Jianlin Cheng
Deep Learning Molecular Docking 3D Ligand

May 22, 2024

Animal Behavior Analysis Methods Using Deep Learning: A Survey
Edoardo Fazzari, Donato Romano, Fabrizio Falchi, Cesare Stefanini
Deep Learning Timely Survey Animal Behavior Psychological Trait Animal Datasets
CPE-Identifier: Automated CPE identification and CVE summaries annotation with Deep Learning and NLP
Wanyu Hu, Vrizlynn L. L. Thing
Deep Learning Natural Language Processing Common Vulnerability
Continual Learning in Medical Imaging: A Survey and Practical Analysis
Mohammad Areeb Qazi, Anees Ur Rehman Hashmi, Santosh Sanjeev, Ibrahim Almakky, Numan Saeed, Camila Gonzalez, Mohammad Yaqub
Deep Learning Timely Survey Continual LEArning Catastrophic Forgetting Theoretical Understanding Medical Imaging Medical Domain Practical Application
Machine learning for exoplanet detection in high-contrast spectroscopy Combining cross correlation maps and deep learning on medium-resolution integral-field spectra
Rakesh Nath-Ranga, Olivier Absil, Valentin Christiaens, Emily O. Garvin
Deep Learning Spectral Feature Exoplanet Candidate Spectroscopic Data Exoplanet Detection Spectral Spatial Dimension
Comparative Analysis of Hyperspectral Image Reconstruction Using Deep Learning for Agricultural and Biological Applications
Md. Toukir Ahmed, Arthur Villordon, Mohammed Kamruzzaman
Deep Learning Comparative Study Spectral Feature Hyperspectral Imaging Agricultural Domain Hyperspectral Image Reconstruction Biomedical Application

May 21, 2024

Improving Earth-like planet detection in radial velocity using deep learning
Yinan Zhao, Xavier Dumusque, Michael Cretignier, Andrew Collier Cameron, David W. Latham, Mercedes López-Morales, Michel Mayor, Alessandro Sozzetti, Rosario Cosentino, Isidro Gómez-Vargas, Francesco Pepe, Stephane Udry
Deep Learning Planetary Transit Exoplanet Detection Radial Velocity Detection Limit
Multiple Realizability and the Rise of Deep Learning
Sam Whitman McGrath, Jacob Russin
Deep Learning Deep Learning Model Cognitive Science Higher Order Multiple Realizability
Towards Retrieval-Augmented Architectures for Image Captioning
Sara Sarto, Marcella Cornia, Lorenzo Baraldi, Alessandro Nicolosi, Rita Cucchiara
Deep Learning Large Corpus Image Captioning Retrieval Augmented Audio Captioning
Blind Separation of Vibration Sources using Deep Learning and Deconvolution
Igor Makienko, Michael Grebshtein, Eli Gildish
Deep Learning Image Deconvolution Vibration Signal Transfer Function
Model Free Prediction with Uncertainty Assessment
Yuling Jiao, Lican Kang, Jin Liu, Heng Peng, Heng Zuo
Deep Learning Uncertainty Estimation Conditional Diffusion Model Nonparametric Regression Confidence Region Conditional Mean

May 20, 2024

Vulnerability Detection in C/C++ Code with Deep Learning
Zhen Huang, Amy Aumpansub
Deep Learning Vulnerability Detection Software Vulnerability Vulnerable Code C++ Implementation C Program Vulnerability Pattern
Large-Scale Multi-Center CT and MRI Segmentation of Pancreas with Deep Learning
Zheyuan Zhang, Elif Keles, Gorkem Durak, Yavuz Taktak, Onkar Susladkar, Vandan Gorade, Debesh Jha, Asli C. Ormeci, Alpay Medetalibeyoglu, Lanhong Yao, Bin Wang, Ilkin Sevgi Isler, Linkai Peng, Hongyi Pan, Camila Lopes Vendrami, Amir Bourhani, Yury Velichko, Boqing Gong, Concetto Spampinato, Ayis Pyrros, Pallavi Tiwari, Derk C. F. Klatte, Megan Engels, Sanne Hoogenboom, Candice W. Bolan, Emil Agarunov, Nassier Harfouch, Chenchan Huang, Marco J. Bruno, Ivo Schoots, Rajesh N. Keswani, Frank H. Miller, Tamas Gonda, Cemal Yazici, Temel Tirkes, Baris Turkbey, Michael B. Wallace, Ulas Bagci
Deep Learning MRI Data Fetal Liver Magnetic Resonance Imaging Segmentation Pancreas Segmentation

Deep Learning

Papers

Feature Fusion for Improved Classification: Combining Dempster-Shafer Theory and Multiple CNN Architectures

Neuroexplicit Diffusion Models for Inpainting of Optical Flow Fields

Nuclear Norm Regularization for Deep Learning

Does context matter in digital pathology?

Deep Learning Methods for Adjusting Global MFD Speed Estimations to Local Link Configurations

Advancements in Feature Extraction Recognition of Medical Imaging Systems Through Deep Learning Technique

Real Time Deep Learning Weapon Detection Techniques for Mitigating Lone Wolf Attacks

Deep Learning for Protein-Ligand Docking: Are We There Yet?

Animal Behavior Analysis Methods Using Deep Learning: A Survey

CPE-Identifier: Automated CPE identification and CVE summaries annotation with Deep Learning and NLP

Continual Learning in Medical Imaging: A Survey and Practical Analysis

Machine learning for exoplanet detection in high-contrast spectroscopy Combining cross correlation maps and deep learning on medium-resolution integral-field spectra

Comparative Analysis of Hyperspectral Image Reconstruction Using Deep Learning for Agricultural and Biological Applications

Improving Earth-like planet detection in radial velocity using deep learning

Multiple Realizability and the Rise of Deep Learning

Towards Retrieval-Augmented Architectures for Image Captioning

Blind Separation of Vibration Sources using Deep Learning and Deconvolution

Model Free Prediction with Uncertainty Assessment

Vulnerability Detection in C/C++ Code with Deep Learning

Large-Scale Multi-Center CT and MRI Segmentation of Pancreas with Deep Learning