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
Q-MRS: A Deep Learning Framework for Quantitative Magnetic Resonance Spectra Analysis
Christopher J. Wu, Lawrence S. Kegeles, Jia Guo
A Deep Learning Approach to Localizing Multi-level Airway Collapse Based on Snoring Sounds
Ying-Chieh Hsu, Stanley Yung-Chuan Liu, Chao-Jung Huang, Chi-Wei Wu, Ren-Kai Cheng, Jane Yung-Jen Hsu, Shang-Ran Huang, Yuan-Ren Cheng, Fu-Shun Hsu
Latent Relationship Mining of Glaucoma Biomarkers: a TRI-LSTM based Deep Learning
Cheng Huang, Junhao Shen, Qiuyu Luo, Karanjit Kooner, Tsengdar Lee, Yishen Liu, Jia Zhang
Deep Learning to Predict Late-Onset Breast Cancer Metastasis: the Single Hyperparameter Grid Search (SHGS) Strategy for Meta Tuning Concerning Deep Feed-forward Neural Network
Yijun Zhou, Om Arora-Jain, Xia Jiang
On the effectiveness of smartphone IMU sensors and Deep Learning in the detection of cardiorespiratory conditions
Lorenzo Simone, Luca Miglior, Vincenzo Gervasi, Luca Moroni, Emanuele Vignali, Emanuele Gasparotti, Simona Celi
Ensuring Equitable Financial Decisions: Leveraging Counterfactual Fairness and Deep Learning for Bias
Saish Shinde
Time-Aware Face Anti-Spoofing with Rotation Invariant Local Binary Patterns and Deep Learning
Moritz Finke, Alexandra Dmitrienko
A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets
Assaf Shmuel, Oren Glickman, Teddy Lazebnik
Hybrid Deep Convolutional Neural Networks Combined with Autoencoders And Augmented Data To Predict The Look-Up Table 2006
Messaoud Djeddou, Aouatef Hellal, Ibrahim A. Hameed, Xingang Zhao, Djehad Al Dallal
Fire-Flyer AI-HPC: A Cost-Effective Software-Hardware Co-Design for Deep Learning
Wei An, Xiao Bi, Guanting Chen, Shanhuang Chen, Chengqi Deng, Honghui Ding, Kai Dong, Qiushi Du, Wenjun Gao, Kang Guan, Jianzhong Guo, Yongqiang Guo, Zhe Fu, Ying He, Panpan Huang, Jiashi Li, Wenfeng Liang, Xiaodong Liu, Xin Liu, Yiyuan Liu, Yuxuan Liu, Shanghao Lu, Xuan Lu, Xiaotao Nie, Tian Pei, Junjie Qiu, Hui Qu, Zehui Ren, Zhangli Sha, Xuecheng Su, Xiaowen Sun, Yixuan Tan, Minghui Tang, Shiyu Wang, Yaohui Wang, Yongji Wang, Ziwei Xie, Yiliang Xiong, Yanhong Xu, Shengfeng Ye, Shuiping Yu, Yukun Zha, Liyue Zhang, Haowei Zhang, Mingchuan Zhang, Wentao Zhang, Yichao Zhang, Chenggang Zhao, Yao Zhao, Shangyan Zhou, Shunfeng Zhou, Yuheng Zou
Evaluating the Visual Similarity of Southwest China's Ethnic Minority Brocade Based on Deep Learning
Shichen Liu, Huaxing Lu
HER2 and FISH Status Prediction in Breast Biopsy H&E-Stained Images Using Deep Learning
Ardhendu Sekhar, Vrinda Goel, Garima Jain, Abhijeet Patil, Ravi Kant Gupta, Tripti Bameta, Swapnil Rane, Amit Sethi
Lecture Notes on Linear Neural Networks: A Tale of Optimization and Generalization in Deep Learning
Nadav Cohen, Noam Razin
A systematic review: Deep learning-based methods for pneumonia region detection
Xinmei Xu
EUR-USD Exchange Rate Forecasting Based on Information Fusion with Large Language Models and Deep Learning Methods
Hongcheng Ding, Xuanze Zhao, Zixiao Jiang, Shamsul Nahar Abdullah, Deshinta Arrova Dewi
A New Era in Computational Pathology: A Survey on Foundation and Vision-Language Models
Dibaloke Chanda, Milan Aryal, Nasim Yahya Soltani, Masoud Ganji
Deep Learning for Lung Disease Classification Using Transfer Learning and a Customized CNN Architecture with Attention
Xiaoyi Liu, Zhou Yu, Lianghao Tan
Deep Learning at the Intersection: Certified Robustness as a Tool for 3D Vision
Gabriel Pérez S, Juan C. Pérez, Motasem Alfarra, Jesús Zarzar, Sara Rojas, Bernard Ghanem, Pablo Arbeláez
A Comparison of Deep Learning and Established Methods for Calf Behaviour Monitoring
Oshana Dissanayake, Lucile Riaboff, Sarah E. McPherson, Emer Kennedy, Pádraig Cunningham