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
Syn2Real Domain Generalization for Underwater Mine-like Object Detection Using Side-Scan Sonar
Aayush Agrawal, Aniruddh Sikdar, Rajini Makam, Suresh Sundaram, Suresh Kumar Besai, Mahesh Gopi
Unitary Multi-Margin BERT for Robust Natural Language Processing
Hao-Yuan Chang, Kang L. Wang
PND-Net: Plant Nutrition Deficiency and Disease Classification using Graph Convolutional Network
Asish Bera, Debotosh Bhattacharjee, Ondrej Krejcar
Game Theory Meets Statistical Mechanics in Deep Learning Design
Djamel Bouchaffra, Fayçal Ykhlef, Bilal Faye, Hanane Azzag, Mustapha Lebbah
nvTorchCam: An Open-source Library for Camera-Agnostic Differentiable Geometric Vision
Daniel Lichy, Hang Su, Abhishek Badki, Jan Kautz, Orazio Gallo
Leveraging Multi-Temporal Sentinel 1 and 2 Satellite Data for Leaf Area Index Estimation With Deep Learning
Clement Wang, Antoine Debouchage, Valentin Goldité, Aurélien Wery, Jules Salzinger
Development and Testing of a Wood Panels Bark Removal Equipment Based on Deep Learning
Rijun Wang, Guanghao Zhang, Hongyang Chen, Xinye Yu, Yesheng Chen, Fulong Liang, Xiangwei Mou, Bo Wang
Cross-Dataset Generalization in Deep Learning
Xuyu Zhang, Haofan Huang, Dawei Zhang, Songlin Zhuang, Shensheng Han, Puxiang Lai, Honglin Liu
Deep Learning Based XIoT Malware Analysis: A Comprehensive Survey, Taxonomy, and Research Challenges
Rami Darwish, Mahmoud Abdelsalam, Sajad Khorsandroo
What Does It Mean to Be a Transformer? Insights from a Theoretical Hessian Analysis
Weronika Ormaniec, Felix Dangel, Sidak Pal Singh
Data-Aware Training Quality Monitoring and Certification for Reliable Deep Learning
Farhang Yeganegi, Arian Eamaz, Mojtaba Soltanalian
Early Diagnoses of Acute Lymphoblastic Leukemia Using YOLOv8 and YOLOv11 Deep Learning Models
Alaa Awad, Mohamed Hegazy, Salah A. Aly
Feasibility Analysis of Federated Neural Networks for Explainable Detection of Atrial Fibrillation
Diogo Reis Santos, Andrea Protani, Lorenzo Giusti, Albert Sund Aillet, Pierpaolo Brutti, Luigi Serio
Do we need more complex representations for structure? A comparison of note duration representation for Music Transformers
Gabriel Souza, Flavio Figueiredo, Alexei Machado, Deborah Guimarães
Comparison of deep learning and conventional methods for disease onset prediction
Luis H. John, Chungsoo Kim, Jan A. Kors, Junhyuk Chang, Hannah Morgan-Cooper, Priya Desai, Chao Pang, Peter R. Rijnbeek, Jenna M. Reps, Egill A. Fridgeirsson
On Representation of 3D Rotation in the Context of Deep Learning
Viktória Pravdová, Lukáš Gajdošech, Hassan Ali, Viktor Kocur
Detecting Unforeseen Data Properties with Diffusion Autoencoder Embeddings using Spine MRI data
Robert Graf, Florian Hunecke, Soeren Pohl, Matan Atad, Hendrik Moeller, Sophie Starck, Thomas Kroencke, Stefanie Bette, Fabian Bamberg, Tobias Pischon, Thoralf Niendorf, Carsten Schmidt, Johannes C. Paetzold, Daniel Rueckert, Jan S Kirschke
Performance Evaluation of Deep Learning and Transformer Models Using Multimodal Data for Breast Cancer Classification
Sadam Hussain, Mansoor Ali, Usman Naseem, Beatriz Alejandra Bosques Palomo, Mario Alexis Monsivais Molina, Jorge Alberto Garza Abdala, Daly Betzabeth Avendano Avalos, Servando Cardona-Huerta, T. Aaron Gulliver, Jose Gerardo Tamez Pena
Innovative Deep Learning Techniques for Obstacle Recognition: A Comparative Study of Modern Detection Algorithms
Santiago Pérez, Camila Gómez, Matías Rodríguez