Search Results - computer learning and pattern recognition::evolution computing

A Concatenational Graph Evolution Aging Model by Suo, Jinli, Chen, Xilin, Shan, Shiguang, Gao, Wen, Dai, Qionghai

“…Modeling the long-term face aging process is of great importance for face recognition and animation, but there is a lack of sufficient long-term face aging sequences for model learning…”
Get full text

Opportunistic sensing for inferring in-the-wild human contexts based on activity pattern recognition using smart computing by Ehatisham-ul-Haq, Muhammad, Azam, Muhammad Awais

“…In recent years, with the evolution of internet-of-things and smart sensing technologies, sensor-based physical activity recognition has gained substantial prominence, and numerous research works…”
Get full text

CHSPAM: a multi-domain model for sequential pattern discovery and monitoring in contexts histories by Dupont, Daniel, Barbosa, Jorge Luis Victória, Alves, Bruno Mota

“… The article proposes a model, called CHSPAM, that allows the discovery of sequential patterns in contexts histories databases and keeps track of these patterns to monitor their evolution over time…”
Get full text

Q-learning enhanced differential evolution for feature selection in high-dimensional medical data analysis by Huang, Chenliang, Wang, Mingjing, Asghar, Heidari Ali, Wang, Zhilin, Chen, Huiling

“… In this study, we propose a hybrid optimization algorithm named QDEHHO, where Differential Evolution (DE…”
Get full text

Seismic-driven neural intelligence coupled with hybrid evolution strategy for accurate intrusion detection in cloud-IoT systems by Saravanan, T., Pugalenthi, R.

“… In addition, most existing deep learning models and hybrid models are plagued with fixed feature engineering, poor parameter tuning, and poor contextual pattern recognition, all of which…”
Get full text

D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features by Bai, Xuyang, Luo, Zixin, Zhou, Lei, Fu, Hongbo, Quan, Long, Tai, Chiew-Lan

“… Despite the fast evolution of learning-based 3D feature descriptors, little attention has been drawn to the learning of 3D feature detectors, even less for a joint learning of the two tasks…”
Get full text

Computer Vision and Pattern Recognition for the Analysis of 2D/3D Remote Sensing Data in Geoscience: A Survey by Savelonas, Michalis A., Veinidis, Christos N., Bartsokas, Theodoros K.

“…Historically, geoscience has been a prominent domain for applications of computer vision and pattern recognition…”
Get full text

Adaptive mobile activity recognition system with evolving data streams by Abdallah, Zahraa Said, Gaber, Mohamed Medhat, Srinivasan, Bala, Krishnaswamy, Shonali

“…s sensor rich mobile phones. Supervised learning with static models has been applied pervasively for mobile activity recognition…”
Get full text

The YOLO Framework: A Comprehensive Review of Evolution, Applications, and Benchmarks in Object Detection by Ali, Momina Liaqat, Zhang, Zhou

“… The review traces the evolution of YOLO variants, highlighting key architectural improvements, performance benchmarks, and applications in domains such as healthcare, autonomous vehicles, and robotics…”
Get full text

Diagnosis of skin diseases in the era of deep learning and mobile technology by Goceri, Evgin

“…Efficient methods developed with deep learning in the last ten years have provided objectivity and high accuracy in the diagnosis of skin diseases…”
Get full text

Pattern recognition of topologically associating domains using deep learning by Yang, Jhen Yuan, Chang, Jia-Ming

“… During evolution, these are conserved based on checking synteny block cross species. Are there common TAD patterns across species or cell lines…”
Get full text

Online Detection of Action Start via Soft Computing for Smart City by Wang, Tian, Chen, Yang, Lv, Hongqiang, Teng, Jing, Snoussi, Hichem, Tao, Fei

“… With video surveillance technologies of soft computing, such as image processing, computer vision, and pattern recognition combined with cloud computing, the construction of smart cities…”
Get full text

Learning Situation Models in a Smart Home by Brdiczka, O., Crowley, J.L., Reignier, P.

“… learning of situation representations, and evolution of a predefined situation model with feedback…”
Get full text

Design and Augmentation of a Deep Learning Based Vehicle Detection Model for Low Light Intensity Conditions by Vishwakarma, Pramod Kumar, Jain, Nitin

“… This study aims to meet the urgent requirement for enhanced vehicle detection in low light circumstances by developing and enhancing a deep learning-based model…”
Get full text

An unsupervised statistical representation learning method for human activity recognition by Abdi, Mohammad Foad, BabaAli, Bagher, Momeni, Saleh

“… Consequently, sensor-based Human Activity Recognition (HAR) has emerged as a significant research area in the fields of ubiquitous computing and wearable computing…”
Get full text

Extending XCS with Cyclic Graphs for Scalability on Complex Boolean Problems by Iqbal, Muhammad, Browne, Will N, Zhang, Mengjie

“…A main research direction in the field of evolutionary machine learning is to develop a scalable classifier system to solve high-dimensional problems…”
Get more information

The Evolution of Cloud through SJF-ML Hybrid Scheduling by Vijay Lahande, Prathamesh

“… The four categories include: SJF-CA, SJF-ELA, SJF-PM, and SJF-RA. The developed SJF-ML algorithms by the author perform pattern recognition of the tasks that are to be computed, to improve decision-making during task computations in the cloud…”
Get full text

EIGEN: Ecologically-Inspired GENetic Approach for Neural Network Structure Searching From Scratch by Ren, Jian, Li, Zhe, Yang, Jianchao, Xu, Ning, Yang, Tianbao, Foran, David J.

“…Designing the structure of neural networks is considered one of the most challenging tasks in deep learning, especially when there is few prior knowledge about the task domain…”
Get full text

Deep Learning for Generic Object Detection: A Survey by Liu, Li, Ouyang, Wanli, Wang, Xiaogang, Fieguth, Paul, Chen, Jie, Liu, Xinwang, Pietikäinen, Matti

“… Given this period of rapid evolution, the goal of this paper is to provide a comprehensive survey of the recent achievements in this field brought about by deep learning techniques…”
Get full text

How evolution learns to generalise: Using the principles of learning theory to understand the evolution of developmental organisation by Kouvaris, Kostas, Clune, Jeff, Kounios, Loizos, Brede, Markus, Watson, Richard A.

“…One of the most intriguing questions in evolution is how organisms exhibit suitable phenotypic variation to rapidly adapt in novel selective environments…”
Get full text