Heliang Zheng, Jianlong Fu, Zheng-Jun Zha, Jiebo Luo
Learning subtle yet discriminative features (e.g., beak and eyes for a bird) plays a significant role in fine-grained image recognition. Existing attention-based approaches localize and amplify significant parts to learn fine-grained details, which often suffer from a limited number of parts and hea...
Rajib Kumar Halder, Mohammed Nasir Uddin, Md. Ashraf Uddin, Sunil Aryal et al.
Abstract The k-Nearest Neighbors (kNN) method, established in 1951, has since evolved into a pivotal tool in data mining, recommendation systems, and Internet of Things (IoT), among other areas. This paper presents a comprehensive review and performance analysis of modifications made to enhance the ...
Debesh Jha, Sharib Ali, Nikhil Kumar Tomar, Håvard D. Johansen et al.
Computer-aided detection, localisation, and segmentation methods can help improve colonoscopy procedures. Even though many methods have been built to tackle automatic detection and segmentation of polyps, benchmarking of state-of-the-art methods still remains an open problem. This is due to the incr...
Hongqing Zhu, M. Liu, Huazhong Shu, Hengliang Zhang et al.
Discrete orthogonal moments such as Tchebichef moments and Krawtchouk moments are more powerful in image representation than traditional continuous orthogonal moments. However, less work has been done for the summarisation of these discrete orthogonal moments. This study proposes two general forms w...
Yan Wang, Ling Yang, Xinzhan Liu, Pengfei Yan
High-precision and high-efficiency Semantic segmentation of high-resolution remote sensing images is a challenge. Existing models typically require a significant amount of training data to achieve good classification results and have numerous training parameters. A novel model called MST-DeepLabv3+ ...
Md Khaled Hasan, Md. Shamim Ahsan, Abdullah‐Al‐Mamun, S. H. Shah Newaz et al.
Face detection, which is an effortless task for humans, is complex to perform on machines. The recent veer proliferation of computational resources is paving the way for frantic advancement of face detection technology. Many astutely developed algorithms have been proposed to detect faces. However, ...
Christos Voudouris, Abdullah Alsheddy, Ahmad Alhindi
Abstract Guided local search (GLS) is a metaheuristic method proposed to solve combinatorial optimization problems. It is a high‐level strategy that applies an efficient penalty‐based approach to interact with the local improvement procedure. This interaction creates a process capable of escaping fr...
Md Farhan Ishmam, Md Sakib Hossain Shovon, M. F. Mridha, Nilanjan Dey
The multimodal task of Visual Question Answering (VQA) encompassing elements of Computer Vision (CV) and Natural Language Processing (NLP), aims to generate answers to questions on any visual input. Over time, the scope of VQA has expanded from datasets focusing on an extensive collection of natural...
Cathal Gurrin, Klaus Schoeffmann, Hideo Joho, Andreas Leibetseder et al.
The Lifelog Search Challenge (LSC) is an international content retrieval competition that evaluates search for personal lifelog data. At the LSC, content-based search is performed over a multi-modal dataset, continuously recorded by a lifelogger over 27 days, consisting of multimedia content, biomet...
Huazhong Shu, Hui Zhang, Beijing Chen, Pascal Haigron et al.
Discrete orthogonal moments have been recently introduced in the field of image analysis. It was shown that they have better image representation capability than the continuous orthogonal moments. One problem concerning the use of moments as feature descriptors is the high computational cost, which ...
Tommy W. S. Chow, M.K.M. Rahman
This paper proposes a new document retrieval (DR) and plagiarism detection (PD) system using multilayer self-organizing map (MLSOM). A document is modeled by a rich tree-structured representation, and a SOM-based system is used as a computationally effective solution. Instead of relying on keywords/...
Ting Xia, Hongqing Zhu, Huazhong Shu, Pascal Haigron et al.
A new set, to our knowledge, of orthogonal moment functions for describing images is proposed. It is based on the generalized pseudo-Zernike polynomials that are orthogonal on the unit circle. The generalized pseudo-Zernike polynomials are scaled to ensure numerical stability, and some properties ar...
Huazhong Shu, Limin Luo, Jean-louis Caatrieux
This first article was aimed at providing the basic formulations of moments, a classification, and an introductory bibliography. This first part presents a classification of moments, and, rather than entering into theoretical details, it sketches their different expressions. The companion articles w...
Beijing Chen, Huazhong Shu, Hui Zhang, Gouenou Coatrieux et al.
The derivation of moment invariants has been extensively investigated in the past decades. In this paper, we construct a set of invariants derived from Zernike moments which is simultaneously invariant to similarity transformation and to convolution with circularly symmetric point spread function (P...
Zubayer Kabir Eisham, Md. Monzurul Haque, Md. Samiur Rahman, Mirza Muntasir Nishat et al.
Multilevel image thresholding and image clustering, two extensively used image processing techniques, have sparked renewed interest in recent years due to their wide range of applications. The approach of yielding multiple threshold values for each color channel to generate clustered and segmented i...