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

April 2, 2024

Towards Leveraging AutoML for Sustainable Deep Learning: A Multi-Objective HPO Approach on Deep Shift Neural Networks
Leona Hennig, Tanja Tornede, Marius Lindauer
Deep Learning Hyperparameter Optimization Online autoML Multi Objective Hyperparameter Sustainable Deep Learning Bit Shift Network
Conjugate-Gradient-like Based Adaptive Moment Estimation Optimization Algorithm for Deep Learning
Jiawu Tian, Liwei Xu, Xiaowei Zhang, Yongqi Li
Deep Learning Vanilla Gradient Descent Adaptive Moment Estimation Adam V2 Second Order Moment

April 1, 2024

MosquitoFusion: A Multiclass Dataset for Real-Time Detection of Mosquitoes, Swarms, and Breeding Sites Using Deep Learning
Md. Faiyaz Abdullah Sayeedi, Fahim Hafiz, Md Ashiqur Rahman
Deep Learning Computer Vision Resilient Swarm Multi Class Real Time Detection Mosquito Detection
Information Plane Analysis Visualization in Deep Learning via Transfer Entropy
Adrian Moldovan, Angel Cataron, Razvan Andonie
Deep Learning Information Bottleneck Information Transfer Transfer Entropy
Automated HER2 Scoring in Breast Cancer Images Using Deep Learning and Pyramid Sampling
Sahan Yoruc Selcuk, Xilin Yang, Bijie Bai, Yijie Zhang, Yuzhu Li, Musa Aydin, Aras Firat Unal, Aditya Gomatam, Zhen Guo, Darrow Morgan Angus, Goren Kolodney, Karine Atlan, Tal Keidar Haran, Nir Pillar, Aydogan Ozcan
Deep Learning Virtual Immunohistochemistry Tissue Phenotyping Slice Sampling Breast Cancer Image Human Epidermal Growth Factor Receptor

March 31, 2024

Enhancing Bangla Fake News Detection Using Bidirectional Gated Recurrent Units and Deep Learning Techniques
Utsha Roy, Mst. Sazia Tahosin, Md. Mahedi Hassan, Taminul Islam, Fahim Imtiaz, Md Rezwane Sadik, Yassine Maleh, Rejwan Bin Sulaiman, Md. Simul Hasan Talukder
Deep Learning Deep Learning Model Long Short Term Memory Fake News Gated Recurrent Unit
Denoising Low-dose Images Using Deep Learning of Time Series Images
Yang Shao, Toshie Yaguchi, Toshiaki Tanigaki
Neural Network Deep Learning Time Series Low Dose Image Denoiser

March 30, 2024

Deep Learning with Parametric Lenses
Geoffrey S. H. Cruttwell, Bruno Gavranovic, Neil Ghani, Paul Wilson, Fabio Zanasi
Deep Learning Loss Function Gradient Descent Categorical Structure Softmax Cross Entropy
Going Forward-Forward in Distributed Deep Learning
Ege Aktemur, Ege Zorlutuna, Kaan Bilgili, Tacettin Emre Bok, Berrin Yanikoglu, Suha Orhun Mutluergil
Deep Learning Deep Neural Network Back Propagation Forward Pas

March 29, 2024

March 28, 2024

Using Deep Learning to Increase Eye-Tracking Robustness, Accuracy, and Precision in Virtual Reality
Kevin Barkevich, Reynold Bailey, Gabriel J. Diaz
Deep Learning Multidimensional Local Precision Rate Gaze Estimation Gaze Tracking
Improving Cancer Imaging Diagnosis with Bayesian Networks and Deep Learning: A Bayesian Deep Learning Approach
Pei Xi, Lin
Deep Learning Machine Learning Bayesian Network Bayesian Deep Learning Tumor Cell Bayesian Deep

March 27, 2024

Deep Learning for Robust and Explainable Models in Computer Vision
Mohammadreza Amirian
Deep Learning Native Robustness Computer Vision Deep Convolutional Neural Network Robust Version Vision Model Computer Vision Model Explainable Model
Transformers-based architectures for stroke segmentation: A review
Yalda Zafari-Ghadim, Essam A. Rashed, Mohamed Mabrok
Deep Learning Narrative Review Transformer Architecture Medical Image Analysis Architecture Perspective Stroke Segmentation
Artifact Reduction in 3D and 4D Cone-beam Computed Tomography Images with Deep Learning -- A Review
Mohammadreza Amirian, Daniel Barco, Ivo Herzig, Frank-Peter Schilling
Deep Learning Narrative Review 3D Content 4 Dimensional Cone Beam Computed Tomography Cone Beam Computed Tomography Image Artifact Reduction
BAM: Box Abstraction Monitors for Real-time OoD Detection in Object Detection
Changshun Wu, Weicheng He, Chih-Hong Cheng, Xiaowei Huang, Saddek Bensalem
Deep Learning Object Detection Distribution Detection R CNN Art Out of Distribution Detection Box Supervised
PIPNet3D: Interpretable Detection of Alzheimer in MRI Scans
Lisa Anita De Santi, Jörg Schlötterer, Michael Scheschenja, Joel Wessendorf, Meike Nauta, Vincenzo Positano, Christin Seifert
Deep Learning Alzheimer'S Disease Image Region MRI Scan Explainable Detection Biomarker Image

Deep Learning

Papers

Towards Leveraging AutoML for Sustainable Deep Learning: A Multi-Objective HPO Approach on Deep Shift Neural Networks

Conjugate-Gradient-like Based Adaptive Moment Estimation Optimization Algorithm for Deep Learning

MosquitoFusion: A Multiclass Dataset for Real-Time Detection of Mosquitoes, Swarms, and Breeding Sites Using Deep Learning

Information Plane Analysis Visualization in Deep Learning via Transfer Entropy

Automated HER2 Scoring in Breast Cancer Images Using Deep Learning and Pyramid Sampling

Enhancing Bangla Fake News Detection Using Bidirectional Gated Recurrent Units and Deep Learning Techniques

Denoising Low-dose Images Using Deep Learning of Time Series Images

Deep Learning with Parametric Lenses

Going Forward-Forward in Distributed Deep Learning

Bayesian Nonparametrics: An Alternative to Deep Learning

TDANet: A Novel Temporal Denoise Convolutional Neural Network With Attention for Fault Diagnosis

Using Images as Covariates: Measuring Curb Appeal with Deep Learning

Automated Identification and Segmentation of Hi Sources in CRAFTS Using Deep Learning Method

Using Deep Learning to Increase Eye-Tracking Robustness, Accuracy, and Precision in Virtual Reality

Improving Cancer Imaging Diagnosis with Bayesian Networks and Deep Learning: A Bayesian Deep Learning Approach

Deep Learning for Robust and Explainable Models in Computer Vision

Transformers-based architectures for stroke segmentation: A review

Artifact Reduction in 3D and 4D Cone-beam Computed Tomography Images with Deep Learning -- A Review

BAM: Box Abstraction Monitors for Real-time OoD Detection in Object Detection

PIPNet3D: Interpretable Detection of Alzheimer in MRI Scans