This book constitutes the proceedings of the Joint IAPR International Workshops on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2024, which took place in Venice, Italy, during September 9-11, 2024.The 19 full papers presented in this volume were carefully reviewed and selected from 27 submissions.

.- A Differentiable Approximation of the Graph Edit Distance. .- Learning Graph Similarity by Counting Holes in Simplicial Complexes. .- Community-Hop: Enhancing Node Classification through Community Preference. .- Spatio-Temporal Graph Neural Networks for Water Temperature Modeling. .- Enhancing IoT Network Security with Graph Neural Networks for Node Anomaly Detection. .- LSTM Networks and Graph Neural Networks for Predicting Events of Hypoglycemia. .- Evaluation metrics in Saliency Maps applied to Graph Regression. .- LESI-GNN: an Interpretable Graph Neural Network based on Local Structures Embedding. .- Mixture of Variational Graph Autoencoders. .- Multimodality Calibration in 3D Multi Input-Multi Output Network for Dementia Diagnosis with Incomplete Acquisitions. .- Multi-modal Medical Images Classification Using Meta-learning Algorithms. .- From semantic segmentation of natural images to medical image segmentation using ViT-based architectures. .- Chronic Wound Segmentation and Measurement Using Semi-Supervised Hierarchical Convolutional Neural Networks. .- ZIRACLE: Zero-shot composed Image Retrieval with Advanced Component-Level Emphasis. .- Improving Object Detector Performance on Low-Quality Images using Histogram Matching and Model Stacking. .- Comparing Learning Methods to Enhance Decision-Making in Simulated Curling. .- An empirical characterization of the stability of Isolation Forest results. .- Automated Classification of Android Games using Word Embeddings. .- An interesting property of Random Forest distances with respect to the curse of dimensionality.

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