Is this you? Claim this profile to correct it, add a bio and choose the work people see first.
Claim this profileWorks38 from public data
- 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.
- 59
- 31
- 23
- 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.
- 15
- 14
- 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.
- 4
- 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.
- Towards Robust Algorithms for Surgical Phase Recognition via Digital Twin Representation2
This work presents a DT representation-based framework for SPR from videos that employs vision foundation models with reliable low-level scene understanding to craft DT representation and finds that using DT representation as an augmentation to the raw input can significantly improve model robustness.
- 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.
- 2
- 1
- 1
- 1
- 1
- 1
- Crowd Counting in Images via DSMCNN1
This work proposes a Dilated Stacked Multi-column Convolutional Neural Network architecture for crowd density estimation in still single images that is composed of three columns of convolutional layers with sharing layers.
- 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.
- –
- –
- –
- –
- –
- –
- –
- –
- Research on Evaluation and Mechanism of Power Grid Reserve Project Based on Matter Element Model–
This paper constructs an evaluation index system for reserve projects considering policy, safety, and benefits, and proposes an evaluation method for power grid reserve projects based on the matter-element model.
- –
- Low-Complexity Modeling for Visual Data: Representations and Algorithms–
A new formulation for cone preserving dimensionality reduction is introduced, which leverages tools from sparse and low-rank decomposition to reduce the complexity, while controlling the approximation error with respect to the original cone.
- –
- –
- Construction and Management of a High Performance Rocks PC Cluster–
The method and procedure for building a high performance PC cluster by using the Rocks operation system and the advantage of Sun Grid Engine in the managing and submitting jobs was shown by several examples of running the popular first principle software package ABINIT and VASP.
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.
Report an error
Wrong papers, two people merged into one, or a profile that should not be here? Tell us and we will fix or hide it.