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
Smartphone region-wise image indoor localization using deep learning for indoor tourist attraction
Gabriel Toshio Hirokawa Higa, Rodrigo Stuqui Monzani, Jorge Fernando da Silva Cecatto, Maria Fernanda Balestieri Mariano de Souza, Vanessa Aparecida de Moraes Weber, Hemerson Pistori, Edson Takashi Matsubara
Exploring Challenges in Deep Learning of Single-Station Ground Motion Records
Ümit Mert Çağlar, Baris Yilmaz, Melek Türkmen, Erdem Akagündüz, Salih Tileylioglu
Enhancing Readmission Prediction with Deep Learning: Extracting Biomedical Concepts from Clinical Texts
Rasoul Samani, Mohammad Dehghani, Fahime Shahrokh
Temporal Decisions: Leveraging Temporal Correlation for Efficient Decisions in Early Exit Neural Networks
Max Sponner, Lorenzo Servadei, Bernd Waschneck, Robert Wille, Akash Kumar
Advancements in Continuous Glucose Monitoring: Integrating Deep Learning and ECG Signal
MohammadReza Hosseinzadehketilateh, Banafsheh Adami, Nima Karimian
Learn and Search: An Elegant Technique for Object Lookup using Contrastive Learning
Chandan Kumar, Jansel Herrera-Gerena, John Just, Matthew Darr, Ali Jannesari
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning
Fuseinin Mumuni, Alhassan Mumuni
Deep Learning Approaches for Human Action Recognition in Video Data
Yufei Xie
Leveraging Internal Representations of Model for Magnetic Image Classification
Adarsh N L, Arun P, Alok Porwal, Malcolm Aranha
Persian Slang Text Conversion to Formal and Deep Learning of Persian Short Texts on Social Media for Sentiment Classification
Mohsen Khazeni, Mohammad Heydari, Amir Albadvi
Deep learning for multi-label classification of coral conditions in the Indo-Pacific via underwater photogrammetry
Xinlei Shao, Hongruixuan Chen, Kirsty Magson, Jiaqi Wang, Jian Song, Jundong Chen, Jun Sasaki
Deep Learning based acoustic measurement approach for robotic applications on orthopedics
Bangyu Lan, Momen Abayazid, Nico Verdonschot, Stefano Stramigioli, Kenan Niu
Algorithmic progress in language models
Anson Ho, Tamay Besiroglu, Ege Erdil, David Owen, Robi Rahman, Zifan Carl Guo, David Atkinson, Neil Thompson, Jaime Sevilla
Hair and scalp disease detection using deep learning
Kavita Sultanpure, Bhairavi Shirsath, Bhakti Bhande, Harshada Sawai, Srushti Gawade, Suraj Samgir
A Deep Learning Method for Classification of Biophilic Artworks
Purna Kar, Jordan J. Bird, Yangang Xing, Alexander Sumich, Andrew Knight, Ahmad Lotfi, Benedict Carpenter van Barthold
Hybridized Convolutional Neural Networks and Long Short-Term Memory for Improved Alzheimer's Disease Diagnosis from MRI Scans
Maleka Khatun, Md Manowarul Islam, Habibur Rahman Rifat, Md. Shamim Bin Shahid, Md. Alamin Talukder, Md Ashraf Uddin
Continual Learning and Catastrophic Forgetting
Gido M. van de Ven, Nicholas Soures, Dhireesha Kudithipudi
RIS-empowered Topology Control for Distributed Learning in Urban Air Mobility
Kai Xiong, Rui Wang, Supeng Leng, Wenyang Che, Chongwen Huang, Chau Yuen