Yuan Liu, Lin Ma, Yifeng Zhang, Wei Liu et al.
Temporal action proposal generation is an important task, aiming to localize the video segments containing human actions in an untrimmed video. In this paper, we propose a multi-granularity generator (MGG) to perform the temporal action proposal from different granularity perspectives, relying on th...
Zhaofan Qiu, Ting Yao, Chong‐Wah Ngo, Xinmei Tian et al.
Convolutional Neural Networks (CNN) have been regarded as a powerful class of models for visual recognition problems. Nevertheless, the convolutional filters in these networks are local operations while ignoring the large-range dependency. Such drawback becomes even worse particularly for video reco...
Nadeem Ahmed, Jahir Ibna Rafiq, Md. Rashedul Islam
Human activity recognition (HAR) techniques are playing a significant role in monitoring the daily activities of human life such as elderly care, investigation activities, healthcare, sports, and smart homes. Smartphones incorporated with varieties of motion sensors like accelerometers and gyroscope...
Prajoy Podder, Tanvir Zaman Khan, Mamdudul Haque Khan, Mezbahur Rahman
In the emerging field of medical image processing, computer vision, pattern recognition and other digital signal processing applications, window technique is vastly used. A window function is a mathematical function that is zero-valued outside of some chosen interval. When another function is multip...
Mohaimenul Azam Khan Raiaan, Sadman Sakib, Nur Mohammad Fahad, Abdullah Al Mamun et al.
Convolutional Neural Network (CNN) is a prevalent topic in deep learning (DL) research for their architectural advantages. CNN relies heavily on hyperparameter configurations, and manually tuning these hyperparameters can be time-consuming for researchers, therefore we need efficient optimization te...
Mohammad Mahmudul Alam, Mohammad Tariqul Islam
A complete blood cell count is an important test in medical diagnosis to evaluate overall health condition. Traditionally blood cells are counted manually using haemocytometer along with other laboratory equipment's and chemical compounds, which is a time-consuming and tedious task. In this work, th...
Iqbal H. Sarker, Mohammed Moshiul Hoque, Md. Kafil Uddin, Tawfeeq Alsanoosy
Artificial intelligence (AI) techniques have grown rapidly in recent years in the context of computing with smart mobile phones that typically allows the devices to function in an intelligent manner. Popular AI techniques include machine learning and deep learning methods, natural language processin...
S. M. Masud Karim, Md. Saifur Rahman, Md. Ismail Hossain
This paper introduces a best approach for Least Significant Bit (LSB) based on image steganography that enhances the existing LSB substitution techniques to improve the security level of hidden information. It is a new approach to substitute LSB of RGB true color image. The new security conception h...
Shakil Ahmed
Abstract Augmented reality (AR) and virtual reality (VR), a kingdom-of-the-art technology for superimposing information onto the real world, have recently started to have an effect on our everyday lives. In addition, AR and VR have shown a great contribution to advanced construction management in re...
K. M. Faizullah Fuhad, Jannat Ferdousey Tuba, Md. Rabiul Ali Sarker, Sifat Momen et al.
Malaria is a life-threatening disease that is spread by the Plasmodium parasites. It is detected by trained microscopists who analyze microscopic blood smear images. Modern deep learning techniques may be used to do this analysis automatically. The need for the trained personnel can be greatly reduc...
Chang Chen, Zhiwei Xiong, Xinmei Tian, Zheng-Jun Zha et al.
Existing methods for single image super-resolution (SR) are typically evaluated with synthetic degradation models such as bicubic or Gaussian downsampling. In this paper, we investigate SR from the perspective of camera lenses, named as CameraSR, which aims to alleviate the intrinsic tradeoff betwee...
Md. Arafat Hossain, Israt Ferdous
Kai Su, Dongdong Yu, Zhenqi Xu, Xin Geng et al.
Multi-person pose estimation is an important but challenging problem in computer vision. Although current approaches have achieved significant progress by fusing the multi-scale feature maps, they pay little attention to enhancing the channel-wise and spatial information of the feature maps. In this...
Niloy Sikder, Abdullah-Al Nahid
In Artificial Intelligence, Human Activity Recognition (HAR) refers to the capability of machines to identify various activities performed by the users. The knowledge acquired from these recognition systems is integrated into many applications where the associated device uses it to identify actions ...
Md. Abdul Awal, Sheikh Shanawaz Mostafa, Mohiuddin Ahmad, M. A. Rashid