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

January 14, 2024

Beyond Traditional Approaches: Multi-Task Network for Breast Ultrasound Diagnosis
Dat T. Chung, Minh-Anh Dang, Mai-Anh Vu, Minh T. Nguyen, Thanh-Huy Nguyen, Vinh Q. Dinh
Deep Learning Convolutional Neural Network Segmentation Task Classification Task Breast Ultrasound Current Method Multi Task Network
A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative Models
Namjoon Suh, Guang Cheng
Neural Network Deep Learning Deep Neural Network Generative Model Generative Adversarial Network Average Approximation Training Dynamic Statistical Model Deep Learning Theory

January 13, 2024

Scalable and Efficient Methods for Uncertainty Estimation and Reduction in Deep Learning
Soyed Tuhin Ahmed
Deep Learning Variational Inference Uncertainty Estimation Bayesian Neural Network Potential Scalability Constructive Reduction Efficient Method Resistive Memory
Empowering Medical Imaging with Artificial Intelligence: A Review of Machine Learning Approaches for the Detection, and Segmentation of COVID-19 Using Radiographic and Tomographic Images
Sayed Amir Mousavi Mobarakeh, Kamran Kazemi, Ardalan Aarabi, Habibollah Danyal
Deep Learning Machine Learning Data Detection Segmentation Based Approach Medical Imaging Imaging Technique COVID 19 Diagnosis Tomographic Image

January 12, 2024

Deep Learning With DAGs
Sourabh Balgi, Adel Daoud, Jose M. Peña, Geoffrey T. Wodtke, Jesse Zhou
Deep Learning Causal Inference Causal Effect Causal Relationship Directed Acyclic Graph Parametric Causal Graphical Normalizing Flow
SeizNet: An AI-enabled Implantable Sensor Network System for Seizure Prediction
Ali Saeizadeh, Douglas Schonholtz, Daniel Uvaydov, Raffaele Guida, Emrecan Demirors, Pedram Johari, Jorge M. Jimenez, Joseph S. Neimat, Tommaso Melodia
Deep Learning Seizure Prediction
Domain Adaptation for Time series Transformers using One-step fine-tuning
Subina Khanal, Seshu Tirupathi, Giulio Zizzo, Ambrish Rawat, Torben Bach Pedersen
Deep Learning Domain Adaptation Deep Learning Model Fine Tuning Time Series Pre Trained Model Time Series Transformer Model

January 11, 2024

Time Series Forecasting of HIV/AIDS in the Philippines Using Deep Learning: Does COVID-19 Epidemic Matter?
Sales G. Aribe, Bobby D. Gerardo, Ruji P. Medina
Deep Learning Covid 19 Time Series Forecasting
The Role of Deep Learning in Advancing Proactive Cybersecurity Measures for Smart Grid Networks: A Survey
Nima Abdi, Abdullatif Albaseer, Mohamed Abdallah
Deep Learning Timely Survey Integral Role Smart Grid Active Defense Proactive Cyber Defense
Knowledge Translation: A New Pathway for Model Compression
Wujie Sun, Defang Chen, Jiawei Chen, Yan Feng, Chun Chen, Can Wang
Deep Learning Training Data Knowledge Based Model Compression New Pathway
Self Expanding Convolutional Neural Networks
Blaise Appolinary, Alex Deaconu, Sophia Yang, Qingze, Li
Deep Learning Convolutional Neural Network Deep Convolutional Neural Network Self Information CNN Performance Sustainable Deep Learning
Deep Learning Meets Mechanism Design: Key Results and Some Novel Applications
V. Udaya Sankar, Vishisht Srihari Rao, Y. Narahari
Deep Learning Key Result Functional Mechanism Mechanism Design Novel Application Incentive Compatibility
Face-GPS: A Comprehensive Technique for Quantifying Facial Muscle Dynamics in Videos
Juni Kim, Zhikang Dong, Pawel Polak
Deep Learning Gameplay Video Facial Motion Surface Electromyography Facial Analysis Spectral Analysis Facial Muscle

January 10, 2024

A Deep Learning Approach Towards Student Performance Prediction in Online Courses: Challenges Based on a Global Perspective
Abdallah Moubayed, MohammadNoor Injadat, Nouh Alhindawi, Ghassan Samara, Sara Abuasal, Raed Alazaidah
Deep Learning Machine Learning Deep Learning Model Technical Challenge Online Learning Deep Learning Approach Global Context Student Performance Prediction Online Training
Standardizing Your Training Process for Human Activity Recognition Models: A Comprehensive Review in the Tunable Factors
Yiran Huang, Haibin Zhao, Yexu Zhou, Till Riedel, Michael Beigl
Deep Learning Activity Recognition Model Training Comprehensive Review Deep Learning Based Training Method HAR Datasets Tunable Slack Mechanism
Modelling Species Distributions with Deep Learning to Predict Plant Extinction Risk and Assess Climate Change Impacts
Joaquim Estopinan, Pierre Bonnet, Maximilien Servajean, François Munoz, Alexis Joly
Deep Learning Specie Distribution Extinction Risk Climate Change Impact
Detecting Brain Tumors through Multimodal Neural Networks
Antonio Curci, Andrea Esposito
Deep Learning Artificial Intelligence Multimodal Model Brain Tumor Brain Tumor Detection Multimodal Neural
Application of Deep Learning in Blind Motion Deblurring: Current Status and Future Prospects
Yawen Xiang, Heng Zhou, Chengyang Li, Fangwei Sun, Zhongbo Li, Yongqiang Xie
Deep Learning Application Proficiency Video Deblurring Motion Blur Current State Non Blind

January 9, 2024

Benchmark Analysis of Various Pre-trained Deep Learning Models on ASSIRA Cats and Dogs Dataset
Galib Muhammad Shahriar Himel, Md. Masudul Islam
Deep Learning Pre Trained Model Image Classification Benchmark Study Pre Trained Convolutional Neural Network Dog Dataset
Fine-Grained Embedding Dimension Optimization During Training for Recommender Systems
Qinyi Luo, Penghan Wang, Wei Zhang, Fan Lai, Jiachen Mao, Xiaohan Wei, Jun Song, Wei-Yu Tsai, Shuai Yang, Yuxi Hu, Xuehai Qian
Deep Learning Fine Grained Training Data Recommender System Jina Embeddings

Deep Learning

Papers

Beyond Traditional Approaches: Multi-Task Network for Breast Ultrasound Diagnosis

A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative Models

Scalable and Efficient Methods for Uncertainty Estimation and Reduction in Deep Learning

Empowering Medical Imaging with Artificial Intelligence: A Review of Machine Learning Approaches for the Detection, and Segmentation of COVID-19 Using Radiographic and Tomographic Images

Deep Learning With DAGs

SeizNet: An AI-enabled Implantable Sensor Network System for Seizure Prediction

Domain Adaptation for Time series Transformers using One-step fine-tuning

Time Series Forecasting of HIV/AIDS in the Philippines Using Deep Learning: Does COVID-19 Epidemic Matter?

The Role of Deep Learning in Advancing Proactive Cybersecurity Measures for Smart Grid Networks: A Survey

Knowledge Translation: A New Pathway for Model Compression

Self Expanding Convolutional Neural Networks

Deep Learning Meets Mechanism Design: Key Results and Some Novel Applications

Face-GPS: A Comprehensive Technique for Quantifying Facial Muscle Dynamics in Videos

A Deep Learning Approach Towards Student Performance Prediction in Online Courses: Challenges Based on a Global Perspective

Standardizing Your Training Process for Human Activity Recognition Models: A Comprehensive Review in the Tunable Factors

Modelling Species Distributions with Deep Learning to Predict Plant Extinction Risk and Assess Climate Change Impacts

Detecting Brain Tumors through Multimodal Neural Networks

Application of Deep Learning in Blind Motion Deblurring: Current Status and Future Prospects

Benchmark Analysis of Various Pre-trained Deep Learning Models on ASSIRA Cats and Dogs Dataset

Fine-Grained Embedding Dimension Optimization During Training for Recommender Systems