Guanyu Yang, Huazhong Shu, Christine Toumoulin, G.N. Han et al.
Legendre orthogonal moments have been widely used in the field of image analysis. Because their computation by a direct method is very time expensive, recent efforts have been devoted to the reduction of computational complexity. Nevertheless, the existing algorithms are mainly focused on binary ima...
Lv Tang Bo Li, Yijie Zhong, Shouhong Ding, Mofei Song
Aiming at discovering and locating most distinctive objects from visual scenes, salient object detection (SOD) plays an essential role in various computer vision systems. Coming to the era of high resolution, SOD methods are facing new challenges. The major limitation of previous methods is that the...
Haider Adnan Khan, Abdullah Al Helal, Khawza I. Ahmed
We present a framework for handwritten Bangla digit recognition using Sparse Representation Classifier. The classifier assumes that a test sample can be represented as a linear combination of the train samples from its native class. Hence, a test sample can be represented using a dictionary construc...
S.M. Sofiqul Islam, Shanto Rahman, Md. Mostafijur Rahman, Emon Kumar Dey et al.
Deep learning is a new era of machine learning research, where many layers of information processing stages are exploited for unsupervised feature learning. Using multiple levels of representation and abstraction, it helps a machine to understand about data (e.g., images, sound and text) more accura...
Shangzhen Luan, Baochang Zhang, Siyue Zhou, Chen Chen et al.
Steerable properties dominate the design of traditional filters, e.g., Gabor filters, and endow features the capability of dealing with spatial transformations. However, such excellent properties have not been well explored in the popular deep convolutional neural networks (DCNNs). In this paper, we...
Mohammad Muntasir Rahman, Yanhao Tan, Jian Xue, Ling Shao et al.
3D object detection in RGB-D images is a vast growing research area in computer vision. In this paper, we study the problems of amodal 3D object detection in RGB-D images and present an efficient 3D object detection system that can predict object location, size, and orientation. Unlike existing meth...
Xuelin Zhu, Jian K. Liu, Weijia Liu, Jiawei Ge et al.
Multi-label image classification refers to assigning a set of labels for an image. One of the main challenges of this task is how to effectively capture the correlation among labels. Existing studies on this issue mostly rely on the statistical label co-occurrence or semantic similarity of labels. H...
Md. Tanzib Hosain, Asif Zaman, Mushfiqur Rahman Abir, Shanjida Akter et al.
From pivotal roles in autonomous vehicles, healthcare diagnostics, and surveillance systems to seamlessly integrating with augmented reality, object detection algorithms stand as the cornerstone in unraveling the complexities of the visual world. Tracing the trajectory from conventional region-based...
Xu Yang, Chongyang Gao, Hanwang Zhang, Jianfei Cai
We propose an Auto-Parsing Network (APN) to discover and exploit the input data’s hidden tree structures for improving the effectiveness of the Transformer-based vision-language systems. Specifically, we impose a Probabilistic Graphical Model (PGM) parameterized by the attention operations on each s...
Moushumi Zaman Bonny, Mohammad Shorif Uddin
The method of joining images to make a panorama is known as image stitching. It is an enthusiastic research area in image processing and computer vision but still a challenging problem for panoramic images. A good number of researches had been carried out to develop different algorithms for image st...
Rafiatul Zannah, Mubtasim Bashar, Rahil Bin Mushfiq, Amitabha Chakrabarty et al.
The field of medical image analysis is in a constant state of evolution, particularly in the challenging tasks of segmenting organs, diseases, and abnormalities. Therefore, in the realm of dental disease diagnosis, image segmentation plays a crucial role in addressing the difficulties faced by denti...
Muhammad Mostafa Monowar, Md. Abdul Hamid, Abu Quwsar Ohi, Madini O. Alassafi et al.
Image retrieval techniques are becoming famous due to the vast availability of multimedia data. The present image retrieval system performs excellently on labeled data. However, often, data labeling becomes costly and sometimes impossible. Therefore, self-supervised and unsupervised learning strateg...
Marjia Sultana, Tasniya Ahmed, Partha Chakraborty, Mahmuda Khatun et al.
In the present era, the applications of computer vision is increasing day by day. Computer vision is related to the automatic recognition, exploration and extraction of the necessary information from a particular image or a group of image sets. This paper addresses the method to detect the desired o...
Md. Bipul Hossen, Zhongfu Ye, Amr Abdussalam, Md. Imran Hossain
Nafis Mustakim, Noushad Hossain, Mohammad Rahman, Nadimul Islam et al.
Human face recognition plays an important role in video surveillance, human-computer interface, personalizing different applications. In this paper, we present an approach to detect and identify a human face from the real-time video that tracks a face and compares it with stored data of known indivi...