Month: September 2025

:::info Authors: (1) Umberto Michieli, Samsung Research UK; (2) Jijoong Moon, Samsung Research Korea; (3) Daehyun Kim, Samsung Research Korea; (4) Mete Ozay, Samsung Research UK. ::: Table of Links Abstract and 1. Introduction Few-Shot Personalized Instance Recognition Object-Conditioned Bag of Instances Experimental Results Conclusion References ABSTRACT Nowadays, users demand for increased personalization of vision … Read more

Table of Links Abstract and I Introduction II. Literature Review III. Method of the Study IV. Result and Discussion V. Conclusion, Acknowledgment, and References IV. RESULT AND DISCUSSION For object detection, we employed the YOLOv5 model and YOLOv8 model by utilizing YOLOv5s and YOLOv8s pretrained models respectively. We primarily relied on precision, recall, F-score, and … Read more

Table of Links Abstract and I Introduction II. Literature Review III. Method of the Study IV. Result and Discussion V. Conclusion, Acknowledgment, and References III. METHODOLOGY OF THE STUDY In this experimental study, researchers conducted imaging of Artemia nauplii in various saltwater samples saturated with nanoparticles. The process involved capturing images of the nauplii under … Read more

:::info Authors: (1) Mahmudul Islam, Masum School of Computing and Information Sciences, Florida International University Miami, USA (mmasu004@fiu.edu); (2) Arif Sarwat, Department of Electrical and Computer Engineering, Florida International University Miami, USA (asarwat@fiu.edu); (3) Hugo Riggs,Department of Electrical and Computer Engineering, Florida International University Miami, USA (hrigg002@fiu.edu); (4) Alicia Boymelgreen, Department of Mechanical and Materials … Read more

:::info Authors: (1) Ivar Bjørgo Saksvik, Department of Mechanical, Electronic and Chemical Engineering Oslo Metropolitan University, Oslo, Norway (s309664@oslomet.no); (2) Alex Alcoce,r Department of Mechanical, Electronic and Chemical Engineering Oslo Metropolitan University, Oslo, Norway (alepen@oslomet.no); (3) Vahid Hassani, Department of Mechanical, Electronic and Chemical Engineering Oslo Metropolitan University, Oslo, Norway (vahidhas@oslomet.no). ::: Table of Links … Read more

Table of Links Abstract and I Introduction II. Materials and Methods III. Results and Discussions IV. Conclusion and References III. RESULTS AND DISCUSSIONS A. Generalized Model Firstly, we evaluated our model on four class breathing cycle using micro and macro metrics described in section II-B. To compare our results with traditionally used CNN architectures, we … Read more

Table of Links Abstract and I Introduction II. Materials and Methods III. Results and Discussions IV. Conclusion and References II. MATERIALS AND METHODS A. Dataset For this work we have used the International Conference on Biomedical and Health Informatics (ICBHI’17) scientific challenge respiratory sound database [39]. This is the largest publicly available respiratory sound database. … Read more

:::info Authors: (1) Jyotibdha Acharya (Student Member, IEEE), HealthTech NTU, Interdisciplinary Graduate Program, Nanyang Technological University, Singapore; (2) Arindam Basu (Senior Member, IEEE), School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. ::: Table of Links Abstract and I Introduction II. Materials and Methods III. Results and Discussions IV. Conclusion and References Abstract—The primary … Read more

Table of Links Abstract and 1. Introduction Related Work Preliminaries Proposed Method Experimental Setup Results and Analysis Discussion and Conclusion, and References A. The Connection Between Prefix-tuning and Hypernetwork B. Number of Tunable Parameters C. Input-output formats 6. Results and Analysis We design a series of experiments for pure language and V&L tasks on both … Read more

Table of Links Abstract and 1. Introduction Related Work Preliminaries Proposed Method Experimental Setup Results and Analysis Discussion and Conclusion, and References A. The Connection Between Prefix-tuning and Hypernetwork B. Number of Tunable Parameters C. Input-output formats 5. Experimental Setup 5.1. Datasets Our framework is evaluated on the GLUE benchmark (Wang et al., 2019b) in … Read more

Table of Links Abstract and 1. Introduction Related Work Preliminaries Proposed Method Experimental Setup Results and Analysis Discussion and Conclusion, and References A. The Connection Between Prefix-tuning and Hypernetwork B. Number of Tunable Parameters C. Input-output formats 2. Related Work In this section, we review recent research on parameter-efficient tuning for pure language and V&L … Read more

:::info Authors: (1) Zhengkun Zhang, with Equal contribution from Work is done at the internship of Noah’s Ark Lab, Huawei Technologies (2) Wenya Guo and TKLNDST, CS, Nankai University, China (yangzl@nankai.edu.cn); (3) Xiaojun Meng, with Equal contribution from Noah’s Ark Lab, Huawei Technologies; (4) Yasheng Wang, Noah’s Ark Lab, Huawei Technologies; (5) Yadao Wang, Noah’s … Read more