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
Integrated feature analysis for deep learning interpretation and class activation maps
Yanli Li, Tahereh Hassanzadeh, Denis P. Shamonin, Monique Reijnierse, Annette H. M. van der Helm-van Mil, Berend C. Stoel
Coding for Intelligence from the Perspective of Category
Wenhan Yang, Zixuan Hu, Lilang Lin, Jiaying Liu, Ling-Yu Duan
Deep learning for automated detection of breast cancer in deep ultraviolet fluorescence images with diffusion probabilistic model
Sepehr Salem Ghahfarokhi, Tyrell To, Julie Jorns, Tina Yen, Bing Yu, Dong Hye Ye
A Closer Look at Deep Learning on Tabular Data
Han-Jia Ye, Si-Yang Liu, Hao-Run Cai, Qi-Le Zhou, De-Chuan Zhan
Assistive Image Annotation Systems with Deep Learning and Natural Language Capabilities: A Review
Moseli Mots'oehli
SemUV: Deep Learning based semantic manipulation over UV texture map of virtual human heads
Anirban Mukherjee, Venkat Suprabath Bitra, Vignesh Bondugula, Tarun Reddy Tallapureddy, Dinesh Babu Jayagopi
Extract More from Less: Efficient Fine-Grained Visual Recognition in Low-Data Regimes
Dmitry Demidov, Abduragim Shtanchaev, Mihail Mihaylov, Mohammad Almansoori
A Simple Attention-Based Mechanism for Bimodal Emotion Classification
Mazen Elabd, Sardar Jaf
VarteX: Enhancing Weather Forecast through Distributed Variable Representation
Ayumu Ueyama, Kazuhiko Kawamoto, Hiroshi Kera
Automated Web-Based Malaria Detection System with Machine Learning and Deep Learning Techniques
Abraham G Taye, Sador Yemane, Eshetu Negash, Yared Minwuyelet, Moges Abebe, Melkamu Hunegnaw Asmare
A look under the hood of the Interactive Deep Learning Enterprise (No-IDLE)
Daniel Sonntag, Michael Barz, Thiago GouvĂȘa
Improving Entity Recognition Using Ensembles of Deep Learning and Fine-tuned Large Language Models: A Case Study on Adverse Event Extraction from Multiple Sources
Yiming Li, Deepthi Viswaroopan, William He, Jianfu Li, Xu Zuo, Hua Xu, Cui Tao
Local Linear Recovery Guarantee of Deep Neural Networks at Overparameterization
Yaoyu Zhang, Leyang Zhang, Zhongwang Zhang, Zhiwei Bai
Virtual Mines -- Component-level recycling of printed circuit boards using deep learning
Muhammad Mohsin, Stefano Rovetta, Francesco Masulli, Alberto Cabri
The Progression of Transformers from Language to Vision to MOT: A Literature Review on Multi-Object Tracking with Transformers
Abhi Kamboj
Deep Learning for Prediction and Classifying the Dynamical behaviour of Piecewise Smooth Maps
Vismaya V S, Bharath V Nair, Sishu Shankar Muni