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
Deep learning assisted high resolution microscopy image processing for phase segmentation in functional composite materials
Ganesh Raghavendran (1), Bing Han (1), Fortune Adekogbe (4), Shuang Bai (2), Bingyu Lu (1), William Wu (5), Minghao Zhang (1), Ying Shirley Meng (1 and 3) ((1) Department of NanoEngineering-University of California San Diego, (2) Department of NanoEngineering-University of California San Diego (3) Pritzker School of Molecular Engineering-University of Chicago, (4) Department of Chemical and Petroleum Engineering-University of Lagos, (5) Del Norte High School)
A Real Benchmark Swell Noise Dataset for Performing Seismic Data Denoising via Deep Learning
Pablo M. Barros, Roosevelt de L. Sardinha, Giovanny A. M. Arboleda, Lessandro de S. S. Valente, Isabelle R. V. de Melo, Albino Aveleda, André Bulcão, Sergio L. Netto, Alexandre G. Evsukoff
Anti-biofouling Lensless Camera System with Deep Learning based Image Reconstruction
Naoki Ide, Tomohiro Kawahara, Hiroshi Ueno, Daiki Yanagidaira, Susumu Takatsuka
Deep learning for action spotting in association football videos
Silvio Giancola, Anthony Cioppa, Bernard Ghanem, Marc Van Droogenbroeck
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Unveiling AI's Potential Through Tools, Techniques, and Applications
Pohsun Feng, Ziqian Bi, Yizhu Wen, Xuanhe Pan, Benji Peng, Ming Liu, Jiawei Xu, Keyu Chen, Junyu Liu, Caitlyn Heqi Yin, Sen Zhang, Jinlang Wang, Qian Niu, Ming Li, Tianyang Wang
Drone Stereo Vision for Radiata Pine Branch Detection and Distance Measurement: Utilizing Deep Learning and YOLO Integration
Yida Lin, Bing Xue, Mengjie Zhang, Sam Schofield, Richard Green
TikGuard: A Deep Learning Transformer-Based Solution for Detecting Unsuitable TikTok Content for Kids
Mazen Balat, Mahmoud Essam Gabr, Hend Bakr, Ahmed B. Zaky
GaNDLF-Synth: A Framework to Democratize Generative AI for (Bio)Medical Imaging
Sarthak Pati, Szymon Mazurek, Spyridon Bakas
Multi-Scale Convolutional LSTM with Transfer Learning for Anomaly Detection in Cellular Networks
Nooruddin Noonari, Daniel Corujo, Rui L. Aguiar, Francisco J. Ferrao
Forecasting Disease Progression with Parallel Hyperplanes in Longitudinal Retinal OCT
Arunava Chakravarty, Taha Emre, Dmitrii Lachinov, Antoine Rivail, Hendrik Scholl, Lars Fritsche, Sobha Sivaprasad, Daniel Rueckert, Andrew Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunović
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Object-Oriented Programming
Ming Li, Ziqian Bi, Tianyang Wang, Keyu Chen, Jiawei Xu, Qian Niu, Junyu Liu, Benji Peng, Sen Zhang, Xuanhe Pan, Jinlang Wang, Pohsun Feng, Caitlyn Heqi Yin, Yizhu Wen, Ming Liu
Counter-Current Learning: A Biologically Plausible Dual Network Approach for Deep Learning
Chia-Hsiang Kao, Bharath Hariharan
GameLabel-10K: Collecting Image Preference Data Through Mobile Game Crowdsourcing
Jonathan Zhou
Efficient Quality Control of Whole Slide Pathology Images with Human-in-the-loop Training
Abhijeet Patil, Harsh Diwakar, Jay Sawant, Nikhil Cherian Kurian, Subhash Yadav, Swapnil Rane, Tripti Bameta, Amit Sethi
Finetuning YOLOv9 for Vehicle Detection: Deep Learning for Intelligent Transportation Systems in Dhaka, Bangladesh
Shahriar Ahmad Fahim
Differential privacy for protecting patient data in speech disorder detection using deep learning
Soroosh Tayebi Arasteh, Mahshad Lotfinia, Paula Andrea Perez-Toro, Tomas Arias-Vergara, Juan Rafael Orozco-Arroyave, Maria Schuster, Andreas Maier, Seung Hee Yang
State-of-the-Art Periorbital Distance Prediction and Disease Classification Using Periorbital Features
George R. Nahass, Ghasem Yazdanpanah, Madison Cheung, Alex Palacios, Jeffery Peterson, Kevin Heinze, Sasha Hubschman, Chad A. Purnell, Pete Setabutr, Ann Q. Tran, Darvin Yi
Enhancing Crime Scene Investigations through Virtual Reality and Deep Learning Techniques
Antonino Zappalà (1), Luca Guarnera (1), Vincenzo Rinaldi (2), Salvatore Livatino (3), Sebastiano Battiato (1) ((1) University of Catania, (2) University of Dundee, (3) University of Hertfordshire)