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
Resource Allocation and Workload Scheduling for Large-Scale Distributed Deep Learning: A Survey
Feng Liang, Zhen Zhang, Haifeng Lu, Chengming Li, Victor C. M. Leung, Yanyi Guo, Xiping Hu
Deep Learning for Slum Mapping in Remote Sensing Images: A Meta-analysis and Review
Anjali Raj, Adway Mitra, Manjira Sinha
Enhancing Wearable based Real-Time Glucose Monitoring via Phasic Image Representation Learning based Deep Learning
Yidong Zhu, Nadia B Aimandi, Mohammad Arif Ul Alam
A Generic Layer Pruning Method for Signal Modulation Recognition Deep Learning Models
Yao Lu, Yutao Zhu, Yuqi Li, Dongwei Xu, Yun Lin, Qi Xuan, Xiaoniu Yang
Automated Pavement Cracks Detection and Classification Using Deep Learning
Selvia Nafaa, Hafsa Essam, Karim Ashour, Doaa Emad, Rana Mohamed, Mohammed Elhenawy, Huthaifa I. Ashqar, Abdallah A. Hassan, Taqwa I. Alhadidi
GemNet: Menu-Based, Strategy-Proof Multi-Bidder Auctions Through Deep Learning
Yanchen Jiang, David C. Parkes, Tonghan Wang
Deep Implicit Optimization for Robust and Flexible Image Registration
Rohit Jena, Pratik Chaudhari, James C. Gee
Minimizing Energy Costs in Deep Learning Model Training: The Gaussian Sampling Approach
Challapalli Phanindra Revanth, Sumohana S. Channappayya, C Krishna Mohan
Large-Scale Contextual Market Equilibrium Computation through Deep Learning
Yunxuan Ma, Yide Bian, Hao Xu, Weitao Yang, Jingshu Zhao, Zhijian Duan, Feng Wang, Xiaotie Deng
Developing, Analyzing, and Evaluating Vehicular Lane Keeping Algorithms Under Dynamic Lighting and Weather Conditions Using Electric Vehicles
Michael Khalfin, Jack Volgren, Matthew Jones, Luke LeGoullon, Joshua Siegel, Chan-Jin Chung
Cascading Unknown Detection with Known Classification for Open Set Recognition
Daniel Brignac, Abhijit Mahalanobis
Beyond Trend Following: Deep Learning for Market Trend Prediction
Fernando Berzal, Alberto Garcia
Black carbon plumes from gas flaring in North Africa identified from multi-spectral imagery with deep learning
Tuel Alexandre, Kerdreux Thomas, Thiry Louis
BD-SAT: High-resolution Land Use Land Cover Dataset & Benchmark Results for Developing Division: Dhaka, BD
Ovi Paul, Abu Bakar Siddik Nayem, Anis Sarker, Amin Ahsan Ali, M Ashraful Amin, AKM Mahbubur Rahman
General Distribution Learning: A theoretical framework for Deep Learning
Binchuan Qi
Injecting Undetectable Backdoors in Obfuscated Neural Networks and Language Models
Alkis Kalavasis, Amin Karbasi, Argyris Oikonomou, Katerina Sotiraki, Grigoris Velegkas, Manolis Zampetakis
Heart Sound Segmentation Using Deep Learning Techniques
Manas Madine
Deep Learning to Predict Glaucoma Progression using Structural Changes in the Eye
Sayan Mandal