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- Factors Influencing the Adoption of Blockchain in the Construction Industry: A Hybrid Approach Using PLS-SEM and fsQCA82
This is one of the first empirical studies on blockchain adoption in the construction industry, which can aid organizations, policymakers, and project participants in making informed decisions regarding the adoption of blockchain.
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- RT-Grasp: Reasoning Tuning Robotic Grasping via Multi-modal Large Language Model17
This paper proposes Reasoning Tuning, a novel method that integrates a reasoning phase before prediction during prediction during training, leveraging the extensive prior knowledge and advanced reasoning abilities of LLMs to generate accurate numerical outputs like grasp poses that are context-aware and adaptable through conversations.
- Fast Face Sketch Synthesis via KD-Tree Search17
A simple yet effective fast face sketch synthesis method based on K dimensional-Tree (KD-Tree), which employs the idea of divide-and-conquer to learn the complex nonlinear mapping between facial photos and sketches.
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- Deep learning model with pathological knowledge for detection of colorectal neuroendocrine tumor14
This model effectively identifies NETs from CRCs, reducing unnecessary immunohistochemical tests and enhancing the precise treatment for patients with colorectal tumors, and enables researchers to investigate methods with high accuracy and low computational complexity, thereby advancing the application of artificial intelligence in clinical settings.
- SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions -- An EndoVis'24 Challenge13
The SegSTRONG-C challenge is introduced, calling for new paradigms that enhance universal robustness to unforeseen"corruptions" to facilitate richer applications in surgical data science and identifies practical approaches for enhancing model robustness.
- Crowd Counting using DMCNN6
A Dilated Multi-column Convolutional Neural Network architecture for crowd density estimation in still images improved from the MCNN model is proposed and the ground truth (density map) is generated based on the Perspective-Adaptive Gaussian Kernels which can better represent the heads of pedestrians.
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- FDCNet: Frontend-Backend Fusion Dilated Network Through Channel-Attention Mechanism4
A novel model to count crowds, named FDCNet: frontend-backend fusion dilated network through channel-attention mechanism that merges the frontend feature map with the backend feature map, achieving a fusion of various scale features without additional branches or extra subtasks.
- Research on full cycle evaluation of power grid projects based on rough set-multilevel extension theory2
This paper proposes a research method for the full-cycle evaluation of power grid projects based on rough set-multi-level extension theory and establishes a project evaluation index system involving multiple interests such as the environment and society.
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- Density-Based Manifold Collective Clustering for Coherent Motion Detection1
This study proposes the Density-based Manifold Collective Clustering approach to recognize both local and global coherent motion having arbitrary shapes and varying densities, and introduces a hierarchical collectiveness merging algorithm to fully characterize the global consistency.
- An Image Encryption Algorithm Based on Small Permutation Array Combining1
A method to generate a large permutation by combining several small permutations arrays is proposed by introducing a join operation to improve the permutation generating speed, where small permutation arrays are generated by one-dimensional chaotic map.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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