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Found 14 papers, 2 papers with code
Deep Learning Approaches in Pavement Distress Identification: A Review
This paper presents a comprehensive review of recent advancements in image processing and deep learning techniques for pavement distress detection and classification, a critical aspect in modern pavement management systems.
MLGCN: An Ultra Efficient Graph Convolution Neural Model For 3D Point Cloud Analysis
To address these limitations we introduce a novel Multi-level Graph Convolution Neural (MLGCN) model, which uses Graph Neural Networks (GNN) blocks to extract features from 3D point clouds at specific locality levels.
A Triplet-loss Dilated Residual Network for High-Resolution Representation Learning in Image Retrieval
Content-based image retrieval is the process of retrieving a subset of images from an extensive image gallery based on visual contents, such as color, shape or spatial relations, and texture.
Contour Completion using Deep Structural Priors
We introduce an iterative process that completes an incomplete image and we propose novel measures that guide this to find regions it needs to complete.
D-CryptO: Deep learning-based analysis of colon organoid morphology from brightfield images
With D-CryptO, subtle variations in how colon organoids responded to the different chemotherapeutic drugs were detected, which suggest potentially distinct mechanisms of action.
Deep Learning Approaches on Image Captioning: A Review
Image captioning is a research area of immense importance, aiming to generate natural language descriptions for visual content in the form of still images.
SMGRL: Scalable Multi-resolution Graph Representation Learning
The resulting multi-resolution embeddings can be aggregated to yield high-quality node embeddings that capture both long- and short-range dependencies.
Multiple Sclerosis Lesions Segmentation using Attention-Based CNNs in FLAIR Images
Experimental results illustrate that the proposed approach significantly surpasses existing methods in terms of Dice similarity and Absolute Volume Difference while the proposed method use just one modality (FLAIR) to segment the lesions.
Medial Spectral Coordinates for 3D Shape Analysis
In recent years there has been a resurgence of interest in our community in the shape analysis of 3D objects represented by surface meshes, their voxelized interiors, or surface point clouds.
A Nonparametric Bayesian Model for Sparse Dynamic Multigraphs
As the availability and importance of temporal interaction data--such as email communication--increases, it becomes increasingly important to understand the underlying structure that underpins these interactions.
A Matrix Factorization Model for Hellinger-based Trust Management in Social Internet of Things
We model the SIoT with a flexible bipartite graph (containing two sets of nodes: service providers and service requestors), then build a social network among the service requestor nodes, using the Hellinger distance.
Compressive Closeness in Networks
In such algorithms, a node is allowed only to have local interactions with its immediate neighbors.
Sequential Edge Clustering in Temporal Multigraphs
Interaction graphs, such as those recording emails between individuals or transactions between institutions, tend to be sparse yet structured, and often grow in an unbounded manner.
Extracting Implicit Social Relation for Social Recommendation Techniques in User Rating Prediction
Hence, we build our method, called Hell-TrustSVD, on top of the state-of-the-art social recommendation technique to incorporate both the extracted implicit social relations and ratings given by users on the prediction of items for an active user.
