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

July 2, 2024

Joint Segmentation and Image Reconstruction with Error Prediction in Photoacoustic Imaging using Deep Learning
Ruibo Shang, Geoffrey P. Luke, Matthew O'Donnell
Deep Learning Image Reconstruction Hybrid Neural Network Photoacoustic Imaging Joint Segmentation Bayesian Convolutional Error Prediction
Deep Learning Based Apparent Diffusion Coefficient Map Generation from Multi-parametric MR Images for Patients with Diffuse Gliomas
Zach Eidex, Mojtaba Safari, Jacob Wynne, Richard L. J. Qiu, Tonghe Wang, David Viar Hernandez, Hui-Kuo Shu, Hui Mao, Xiaofeng Yang
Deep Learning Magnetic Resonance Imaging Patient Friendly Language ViT Model Diffuse Glioma Residual Transformer Diffusion Coefficient
CALICO: Confident Active Learning with Integrated Calibration
Lorenzo S. Querol, Hajime Nagahara, Hideaki Hayashi
Deep Learning Active Learning Uncertainty Based Active Learning Integrated Calibration

July 1, 2024

Empirical Tests of Optimization Assumptions in Deep Learning
Hoang Tran, Qinzi Zhang, Ashok Cutkosky
Deep Learning Convergence Guarantee Optimization Algorithm Optimization Performance
Scalable Nested Optimization for Deep Learning
Jonathan Lorraine
Deep Learning Generative Adversarial Network Optimization Purpose Hyperparameter Optimization Practical Deep
Neurovascular Segmentation in sOCT with Deep Learning and Synthetic Training Data
Etienne Chollet, Yaël Balbastre, Chiara Mauri, Caroline Magnain, Bruce Fischl, Hui Wang
Deep Learning Optical Coherence Tomography Synthetic Training Data Vascular Network MM Soc
Integrated feature analysis for deep learning interpretation and class activation maps
Yanli Li, Tahereh Hassanzadeh, Denis P. Shamonin, Monique Reijnierse, Annette H. M. van der Helm-van Mil, Berend C. Stoel
Deep Learning Feature Selection Class Activation Abstract Interpretation Feature Distribution Feature Mining Feature Decomposition
Coding for Intelligence from the Perspective of Category
Wenhan Yang, Zixuan Hu, Lilang Lin, Jiaying Liu, Ling-Yu Duan
Deep Learning Strong Generalization Visual Perspective Cognitive Intelligence Category Shift Model Learning Novel Encoding Description Length
Deep learning for automated detection of breast cancer in deep ultraviolet fluorescence images with diffusion probabilistic model
Sepehr Salem Ghahfarokhi, Tyrell To, Julie Jorns, Tina Yen, Bing Yu, Dong Hye Ye
Deep Learning Data Detection Probabilistic Model Breast Cancer Breast Cancer Detection Breast Cancer Classification Fluorescence Spectroscopy
A Closer Look at Deep Learning Methods on Tabular Datasets
Han-Jia Ye, Si-Yang Liu, Hao-Run Cai, Qi-Le Zhou, De-Chuan Zhan
Deep Learning Tabular Data Glance Annotation Tabular Datasets Tabular Deep Learning Tabular Benchmark

June 30, 2024

BADM: Batch ADMM for Deep Learning
Ouya Wang, Shenglong Zhou, Geoffrey Ye Li
Deep Learning Data Driven Stochastic Gradient Faster Convergence ADMM Algorithm Alternating Direction Method of Multiplier
Analysis of Modern Computer Vision Models for Blood Cell Classification
Alexander Kim, Ryan Kim
Deep Learning Convolutional Neural Network General Analysis Blood Cell Classification

June 29, 2024

Science-Informed Deep Learning (ScIDL) With Applications to Wireless Communications
Atefeh Termehchi, Ekram Hossain, Isaac Woungang
Deep Learning Financial Application

June 28, 2024

Assistive Image Annotation Systems with Deep Learning and Natural Language Capabilities: A Review
Moseli Mots'oehli
Deep Learning Natural Language Narrative Review Image Annotation Efficient Annotation Semantic Image Semi Automatic Annotation
SemUV: Deep Learning based semantic manipulation over UV texture map of virtual human heads
Anirban Mukherjee, Venkat Suprabath Bitra, Vignesh Bondugula, Tarun Reddy Tallapureddy, Dinesh Babu Jayagopi
Deep Learning StyleGAN Latent 3D Human Head Appearance Editing UV Texture
Extract More from Less: Efficient Fine-Grained Visual Recognition in Low-Data Regimes
Dmitry Demidov, Abduragim Shtanchaev, Mihail Mihaylov, Mohammad Almansoori
Deep Learning Fine Grained Fine Grained Image Classification Chaotic Regime Intra Class Variation Fine Grained Visual Recognition
A Simple Attention-Based Mechanism for Bimodal Emotion Classification
Mazen Elabd, Sardar Jaf
Deep Learning Deep Learning Model Attention Mechanism Modal Attention
VarteX: Enhancing Weather Forecast through Distributed Variable Representation
Ayumu Ueyama, Kazuhiko Kawamoto, Hiroshi Kera
Deep Learning Numerical Weather Prediction Weather Forecasting Weather Variable Distributed Representation

June 27, 2024

Automated Web-Based Malaria Detection System with Machine Learning and Deep Learning Techniques
Abraham G Taye, Sador Yemane, Eshetu Negash, Yared Minwuyelet, Moges Abebe, Melkamu Hunegnaw Asmare
Deep Learning Machine Learning Traditional CNNs Malaria Detection
A look under the hood of the Interactive Deep Learning Enterprise (No-IDLE)
Daniel Sonntag, Michael Barz, Thiago Gouvêa
Deep Learning Glance Annotation Visual Prototype Multimodal Interaction Interactive Machine Learning Interactive Deep Learning

Deep Learning

Papers

Joint Segmentation and Image Reconstruction with Error Prediction in Photoacoustic Imaging using Deep Learning

Deep Learning Based Apparent Diffusion Coefficient Map Generation from Multi-parametric MR Images for Patients with Diffuse Gliomas

CALICO: Confident Active Learning with Integrated Calibration

Empirical Tests of Optimization Assumptions in Deep Learning

Scalable Nested Optimization for Deep Learning

Neurovascular Segmentation in sOCT with Deep Learning and Synthetic Training Data

Integrated feature analysis for deep learning interpretation and class activation maps

Coding for Intelligence from the Perspective of Category

Deep learning for automated detection of breast cancer in deep ultraviolet fluorescence images with diffusion probabilistic model

A Closer Look at Deep Learning Methods on Tabular Datasets

BADM: Batch ADMM for Deep Learning

Analysis of Modern Computer Vision Models for Blood Cell Classification

Science-Informed Deep Learning (ScIDL) With Applications to Wireless Communications

Assistive Image Annotation Systems with Deep Learning and Natural Language Capabilities: A Review

SemUV: Deep Learning based semantic manipulation over UV texture map of virtual human heads

Extract More from Less: Efficient Fine-Grained Visual Recognition in Low-Data Regimes

A Simple Attention-Based Mechanism for Bimodal Emotion Classification

VarteX: Enhancing Weather Forecast through Distributed Variable Representation

Automated Web-Based Malaria Detection System with Machine Learning and Deep Learning Techniques

A look under the hood of the Interactive Deep Learning Enterprise (No-IDLE)