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
Semantic Inference-Based Deep Learning and Modeling for Earth Observation: Cognitive Semantic Augmentation Satellite Networks
Hong-fu Chou, Vu Nguyen Ha, Prabhu Thiruvasagam, Thanh-Dung Le, Geoffrey Eappen, Ti Ti Nguyen, Luis M. Garces-Socarras, Jorge L. Gonzalez-Rios, Juan Carlos Merlano-Duncan, Symeon Chatzinotas
VARADE: a Variational-based AutoRegressive model for Anomaly Detection on the Edge
Alessio Mascolini, Sebastiano Gaiardelli, Francesco Ponzio, Nicola Dall'Ora, Enrico Macii, Sara Vinco, Santa Di Cataldo, Franco Fummi
Investigation of Time-Frequency Feature Combinations with Histogram Layer Time Delay Neural Networks
Amirmohammad Mohammadi, Iren'e Masabarakiza, Ethan Barnes, Davelle Carreiro, Alexandra Van Dine, Joshua Peeples
Deep Learning-Based Channel Squeeze U-Structure for Lung Nodule Detection and Segmentation
Mingxiu Sui, Jiacheng Hu, Tong Zhou, Zibo Liu, Likang Wen, Junliang Du
Morphological Detection and Classification of Microplastics and Nanoplastics Emerged from Consumer Products by Deep Learning
Hadi Rezvani, Navid Zarrabi, Ishaan Mehta, Christopher Kolios, Hussein Ali Jaafar, Cheng-Hao Kao, Sajad Saeedi, Nariman Yousefi
Recent Advances in Non-convex Smoothness Conditions and Applicability to Deep Linear Neural Networks
Vivak Patel, Christian Varner
Neural filtering for Neural Network-based Models of Dynamic Systems
Parham Oveissi, Turibius Rozario, Ankit Goel
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Tensorflow Pretrained Models
Keyu Chen, Ziqian Bi, Qian Niu, Junyu Liu, Benji Peng, Sen Zhang, Ming Liu, Ming Li, Xuanhe Pan, Jiawei Xu, Jinlang Wang, Pohsun Feng
A generalizable framework for unlocking missing reactions in genome-scale metabolic networks using deep learning
Xiaoyi Liu, Hongpeng Yang, Chengwei Ai, Ruihan Dong, Yijie Ding, Qianqian Yuan, Jijun Tang, Fei Guo
Deep Learning based Optical Image Super-Resolution via Generative Diffusion Models for Layerwise in-situ LPBF Monitoring
Francis Ogoke, Sumesh Kalambettu Suresh, Jesse Adamczyk, Dan Bolintineanu, Anthony Garland, Michael Heiden, Amir Barati Farimani
Explainable AI for Autism Diagnosis: Identifying Critical Brain Regions Using fMRI Data
Suryansh Vidya, Kush Gupta, Amir Aly, Andy Wills, Emmanuel Ifeachor, Rohit Shankar
Recognition of Harmful Phytoplankton from Microscopic Images using Deep Learning
Aymane Khaldi, Rohaifa Khaldi
Deep Learning-Based Detection of Referable Diabetic Retinopathy and Macular Edema Using Ultra-Widefield Fundus Imaging
Philippe Zhang, Pierre-Henri Conze, Mathieu Lamard, Gwenolé Quellec, Mostafa El Habib Daho
pyrtklib: An open-source package for tightly coupled deep learning and GNSS integration for positioning in urban canyons
Runzhi Hu, Penghui Xu, Yihan Zhong, Weisong Wen