Papers Deep Learning
“Deep Learning” 태그가 달린 논문 9,423편 · 필터 해제
Automatic Classification and Segmentation of Tunnel Cracks Based on Deep Learning and Visual Explanations
Tunnel lining crack is a crucial indicator of tunnels' safety status. Aiming to classify and segment tunnel cracks with enhanced accuracy and efficiency, this study proposes a two-step deep learning-based method. An auto…
Crack SegmentationDeep Learningimage-classificationImage ClassificationA Survey of Deep Learning for Geometry Problem Solving
Geometry problem solving is a key area of mathematical reasoning, which is widely involved in many important fields such as education, mathematical ability assessment of artificial intelligence, and multimodal ability as…
Deep LearningGeometry Problem SolvingMathematical ReasoningSurveyUncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning
Brain-computer interfaces (BCIs) turn brain signals into functionally useful output, but they are not always accurate. A good Machine Learning classifier should be able to indicate how confident it is about a given class…
Deep LearningMotor ImageryUncertainty QuantificationChat-Ghosting: A Comparative Study of Methods for Auto-Completion in Dialog Systems
Ghosting, the ability to predict a user's intended text input for inline query auto-completion, is an invaluable feature for modern search engines and chat interfaces, greatly enhancing user experience. By suggesting com…
Deep LearningDeep Learning Optimization of Two-State Pinching Antennas Systems
The evolution of wireless communication systems requires flexible, energy-efficient, and cost-effective antenna technologies. Pinching antennas (PAs), which can dynamically control electromagnetic wave propagation throug…
Deep LearningAXLearn: Modular Large Model Training on Heterogeneous Infrastructure
We design and implement AXLearn, a production deep learning system that facilitates scalable and high-performance training of large deep learning models. Compared to other state-of-the-art deep learning systems, AXLearn …
Deep LearningDetermination Of Structural Cracks Using Deep Learning Frameworks
Structural crack detection is a critical task for public safety as it helps in preventing potential structural failures that could endanger lives. Manual detection by inexperienced personnel can be slow, inconsistent, an…
Deep LearningGeneralized Adaptive Transfer Network: Enhancing Transfer Learning in Reinforcement Learning Across Domains
Transfer learning in Reinforcement Learning (RL) enables agents to leverage knowledge from source tasks to accelerate learning in target tasks. While prior work, such as the Attend, Adapt, and Transfer (A2T) framework, a…
Atari GamesChatbotComputational EfficiencyDeep Learning+6Crop Pest Classification Using Deep Learning Techniques: A Review
Insect pests continue to bring a serious threat to crop yields around the world, and traditional methods for monitoring them are often slow, manual, and difficult to scale. In recent years, deep learning has emerged as a…
Deep LearningTask-Agnostic Contrastive Pretraining for Relational Deep Learning
Relational Deep Learning (RDL) is an emerging paradigm that leverages Graph Neural Network principles to learn directly from relational databases by representing them as heterogeneous graphs. However, existing RDL models…
Deep LearningGraph Neural NetworkRepresentation LearningA Hierarchical Deep Learning Approach for Minority Instrument Detection
Identifying instrument activities within audio excerpts is vital in music information retrieval, with significant implications for music cataloging and discovery. Prior deep learning endeavors in musical instrument recog…
Deep LearningDiversityInformation RetrievalInstrument Recognition+1Comparative Analysis of Deep Learning Models for Crop Disease Detection: A Transfer Learning Approach
This research presents the development of an Artificial Intelligence (AI) - driven crop disease detection system designed to assist farmers in rural areas with limited resources. We aim to compare different deep learning…
Deep LearningManagementTransfer LearningPhysics-Guided Radiotherapy Treatment Planning with Deep Learning
Radiotherapy (RT) is a critical cancer treatment, with volumetric modulated arc therapy (VMAT) being a commonly used technique that enhances dose conformity by dynamically adjusting multileaf collimator (MLC) positions a…
ARCDeep LearningExploiting Efficiency Vulnerabilities in Dynamic Deep Learning Systems
The growing deployment of deep learning models in real-world environments has intensified the need for efficient inference under strict latency and resource constraints. To meet these demands, dynamic deep learning syste…
Deep LearningRelational Deep Learning: Challenges, Foundations and Next-Generation Architectures
Graph machine learning has led to a significant increase in the capabilities of models that learn on arbitrary graph-structured data and has been applied to molecules, social networks, recommendation systems, and transpo…
Deep LearningFeature EngineeringRecommendation SystemsEfficient Transformations in Deep Learning Convolutional Neural Networks
This study investigates the integration of signal processing transformations -- Fast Fourier Transform (FFT), Walsh-Hadamard Transform (WHT), and Discrete Cosine Transform (DCT) -- within the ResNet50 convolutional neura…
Computational EfficiencyDeep Learningimage-classificationImage ClassificationGeometric deep learning assists protein engineering. Opportunities and Challenges
Protein engineering is experiencing a paradigmatic shift through the integration of geometric deep learning into computational design workflows. While traditional strategies, such as rational design and directed evolutio…
Deep LearningProtein DesignFiber Signal Denoising Algorithm using Hybrid Deep Learning Networks
With the applicability of optical fiber-based distributed acoustic sensing (DAS) systems, effective signal processing and analysis approaches are needed to promote its popularization in the field of intelligent transport…
Deep LearningDenoisingvehicle detectionAccurate and scalable exchange-correlation with deep learning
Density Functional Theory (DFT) is the most widely used electronic structure method for predicting the properties of molecules and materials. Although DFT is, in principle, an exact reformulation of the Schr\"odinger equ…
Computational EfficiencyDeep LearningAcoustic scattering AI for non-invasive object classifications: A case study on hair assessment
This paper presents a novel non-invasive object classification approach using acoustic scattering, demonstrated through a case study on hair assessment. When an incident wave interacts with an object, it generates a scat…
ClassificationDeep LearningPrivacy PreservingSound Classification