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
SMART-Vision: Survey of Modern Action Recognition Techniques in Vision
Ali K. AlShami, Ryan Rabinowitz, Khang Lam, Yousra Shleibik, Melkamu Mersha, Terrance Boult, Jugal Kalita
Advanced deep architecture pruning using single filter performance
Yarden Tzach, Yuval Meir, Ronit D. Gross, Ofek Tevet, Ella Koresh, Ido Kanter
Growth strategies for arbitrary DAG neural architectures
Stella Douka (LISN, TAU), Manon Verbockhaven (LISN, TAU), Théo Rudkiewicz (ENS Paris Saclay, LISN, TAU), Stéphane Rivaud (LISN, TAU), François P Landes (LISN, TAU), Sylvain Chevallier (LISN, TAU), Guillaume Charpiat (LISN, TAU)
Deep Learning Based Segmentation of Blood Vessels from H&E Stained Oesophageal Adenocarcinoma Whole-Slide Images
Jiaqi Lv, Stefan S Antonowicz, Shan E Ahmed Raza
Early Detection and Classification of Breast Cancer Using Deep Learning Techniques
Mst. Mumtahina Labonno, D.M. Asadujjaman, Md. Mahfujur Rahman, Abdullah Tamim, Mst. Jannatul Ferdous, Rafi Muttaki Mahi
Fast-RF-Shimming: Accelerate RF Shimming in 7T MRI using Deep Learning
Zhengyi Lu, Hao Liang, Ming Lu, Xiao Wang, Xinqiang Yan, Yuankai Huo
Aggrotech: Leveraging Deep Learning for Sustainable Tomato Disease Management
MD Mehraz Hosen, Md. Hasibul Islam
A Survey on Memory-Efficient Large-Scale Model Training in AI for Science
Kaiyuan Tian, Linbo Qiao, Baihui Liu, Gongqingjian Jiang, Dongsheng Li
Data-driven Detection and Evaluation of Damages in Concrete Structures: Using Deep Learning and Computer Vision
Saeid Ataei, Saeed Adibnazari, Seyyed Taghi Ataei
Utilising Deep Learning to Elicit Expert Uncertainty
Julia R. Falconer, Eibe Frank, Devon L. L. Polaschek, Chaitanya Joshi
Disharmony: Forensics using Reverse Lighting Harmonization
Philip Wootaek Shin, Jack Sampson, Vijaykrishnan Narayanan, Andres Marquez, Mahantesh Halappanavar
Author-Specific Linguistic Patterns Unveiled: A Deep Learning Study on Word Class Distributions
Patrick Krauss, Achim Schilling
Deep Learning for Early Alzheimer Disease Detection with MRI Scans
Mohammad Rafsan, Tamer Oraby, Upal Roy, Sanjeev Kumar, Hansapani Rodrigo
Dendritic Localized Learning: Toward Biologically Plausible Algorithm
Changze Lv, Jingwen Xu, Yiyang Lu, Xiaohua Wang, Zhenghua Wang, Zhibo Xu, Di Yu, Xin Du, Xiaoqing Zheng, Xuanjing Huang
Using Domain Knowledge with Deep Learning to Solve Applied Inverse Problems
Qinyi Tian, Winston Lindqwister, Manolis Veveakis, Laura E. Dalton
Coded Deep Learning: Framework and Algorithm
En-hui Yang, Shayan Mohajer Hamidi
LLM-Based Routing in Mixture of Experts: A Novel Framework for Trading
Kuan-Ming Liu (1), Ming-Chih Lo (2) ((1) National Chengchi University, College of Commerce, (2) National Yang Ming Chiao Tung University, College of Computer Science)
Multimodal Marvels of Deep Learning in Medical Diagnosis: A Comprehensive Review of COVID-19 Detection
Md Shofiqul Islama, Khondokar Fida Hasanc, Hasibul Hossain Shajeebd, Humayan Kabir Ranae, Md Saifur Rahmand, Md Munirul Hasanb, AKM Azadf, Ibrahim Abdullahg, Mohammad Ali Moni
Physics-informed deep learning for infectious disease forecasting
Ying Qian, Éric Marty, Avranil Basu, Eamon B. O'Dea, Xianqiao Wang, Spencer Fox, Pejman Rohani, John M. Drake, He Li