This paper introduces a new multi-modal model based on the Transformer architecture and tensor product fusion strategy, combining BERT's text vectors and ViT's image vectors to classify students psychological ...
详细信息
This paper proposes a new ant colony optimization for multi-Label Correlation-Based Feature Selection (ACO-ML-CFS). This ACO performs a global search within the space of candidate features to identify an optimal subse...
详细信息
The task of rotation object detection poses significant challenges in the field of computer vision due to difficulties in accurately separating objects from complex backgrounds and extracting features from small targe...
详细信息
ISBN:
(纸本)9798350386783;9798350386776
The task of rotation object detection poses significant challenges in the field of computer vision due to difficulties in accurately separating objects from complex backgrounds and extracting features from small targets. In recent years, Transformer has emerged as a prominent technique in computer vision, featuring self-attention mechanisms capable of extracting target features. We propose a multi-scale Feature Self-Attention Module based on Transformer, abbreviated as the ks module. We integrate this proposed module into the backbone and neck of the algorithm, a method less explored in the domain of Transformer-based improvements for rotation object detection. This approach combines Transformer's TransformerBlock and Feed-Forward Network (FFN) to hierarchically extract multi-scale features of remote sensing objects in complex environments, thereby achieving improved detection accuracy. Experimental results on popular datasets such as DOTA and HRSC2016 demonstrate that our proposed R3Det-ks outperforms current state-of-the-art methods in remote sensing imagery object detection.
Task scheduling, which is important in cloud computing, is one of the most challenging issues in this area. Hence, an efficient and reliable task scheduling approach is needed to produce more efficient resource employ...
详细信息
The emergence of Large Language Models and their deployment in systems such as ChatGPT are poised to have a major impact on STEM education, particularly computerscience. These generative large language models can pro...
详细信息
ISBN:
(纸本)9783031530210;9783031530227
The emergence of Large Language Models and their deployment in systems such as ChatGPT are poised to have a major impact on STEM education, particularly computerscience. These generative large language models can produce program code as well as human language output. This has potentially serious implications for computerscience programs and pedagogy. This work provides a qualitative assessment sample code generated by ChatGPT, as an example of an LLM explores implications for computing pedagogy.. ..
To address the critical challenge of pupil segmentation accuracy in medical image analysis, this paper proposes an innovative pupil segmentation method based on an enhanced TransUNet deep neural network. The proposed ...
详细信息
The Dynamic Resource Allocation multi-Objective Optimization Algorithm (MOEA/D-DRA) is a method for solving multi-objective optimization problems (MOPs). This algorithm enhances the performance of the original MOEA/D ...
详细信息
A new parallel file system and multi-core processor-based dynamic multimedia encryption method is presented in this study. multimedia encryption efficiency and security were the main goals, addressing massive data set...
详细信息
Organisations are flooded with enormous amounts of data from many sources in the big data era. Effective query processing strategies are crucial for deriving significant insights and guiding well-informed judgements. ...
详细信息
In computerscience, cultural assumptions are embedded in programming languages and problem prompts. This paper investigates the impact of cultural assumptions on internationalcomputerscience students in the US. By ...
详细信息
ISBN:
(纸本)9798400706264
In computerscience, cultural assumptions are embedded in programming languages and problem prompts. This paper investigates the impact of cultural assumptions on internationalcomputerscience students in the US. By performing thematic analysis on semistructured interviews with 12 international graduate students at North Carolina State University, the authors found six main themes. Analyzing these themes provided insight into what barriers international students face and how they can be alleviated. By shedding light on this topic, the authors hope to inform computerscience educators and researchers on the importance of creating inclusive and culturally relevant learning environments that accommodate the needs of diverse students.
暂无评论