SN Computer Science

  2661-8907

  2662-995X

 

Cơ quản chủ quản:  SPRINGER

Lĩnh vực:
Computational Theory and MathematicsArtificial IntelligenceComputer Science ApplicationsComputer Science (miscellaneous)Computer Networks and CommunicationsComputer Graphics and Computer-Aided Design

Các bài báo tiêu biểu

Forecasting Models for Coronavirus Disease (COVID-19): A Survey of the State-of-the-Art
- 2020
Gitanjali R. Shinde, Asmita Balasaheb Kalamkar, Parikshit N. Mahalle, Nilanjan Dey, Jyotismita Chaki, Aboul Ella Hassanien
Breast Cancer Prediction: A Comparative Study Using Machine Learning Techniques
- 2020
Md. Milon Islam, Md. Rezwanul Haque, Hasib Iqbal, Muzamir Hasan, Mahmudul Hasan, Muhammad Nomani Kabir
Chest X-ray Classification Using Deep Learning for Automated COVID-19 Screening
- 2021
Ankita Shelke, Madhura Inamdar, Vruddhi Shah, Amanshu Tiwari, Aafiya Hussain, Talha Chafekar, Ninad Mehendale
Mitigating Metaphors: A Comprehensible Guide to Recent Nature-Inspired Algorithms
Tập 1 Số 1 - 2020
Michael A. Lones
Abstract

In recent years, a plethora of new metaheuristic algorithms have explored different sources of inspiration within the biological and natural worlds. This nature-inspired approach to algorithm design has been widely criticised. A notable issue is the tendency for authors to use terminology that is derived from the domain of inspiration, rather than the broader domains of metaheuristics and optimisation. This makes it difficult to both comprehend how these algorithms work and understand their relationships to other metaheuristics. This paper attempts to address this issue, at least to some extent, by providing accessible descriptions of the most cited nature-inspired algorithms published in the last 20 years. It also discusses commonalities between these algorithms and more classical nature-inspired metaheuristics such as evolutionary algorithms and particle swarm optimisation, and finishes with a discussion of future directions for the field.

Offline Signature Recognition Using Image Processing Techniques and Back Propagation Neuron Network System
- 2021
P. V. R. Sai Kiran, B. D. Parameshachari, J. Yashwanth, K. N. Bharath
Detection of Autism Spectrum Disorder in Children Using Machine Learning Techniques
- 2021
Kaushik Vakadkar, Diya Purkayastha, Deepa Krishnan
Driver Safety Development: Real-Time Driver Drowsiness Detection System Based on Convolutional Neural Network
Tập 1 Số 5 - 2020
Maryam Hashemi, Alireza Mirrashid, Ali Asghar Beheshti Shirazi
Historical Document Image Binarization: A Review
- 2020
Chris Tensmeyer, Tony Martinez
Literature Review on Transfer Learning for Human Activity Recognition Using Mobile and Wearable Devices with Environmental Technology
Tập 1 Số 2 - 2020
Netzahualcóyotl Hernández, Jens Lundström, Jesús Favela, Ian McChesney, Bert Arnrich
Robotics in Healthcare: A Survey
Tập 5 - Trang 1-19 - 2024
David Silvera-Tawil
Research and innovation in the area of robotics in healthcare has seen significant growth in recent years. Global trends indicate that patients are getting older and sicker, while demands in healthcare workers are increasing their chance of injury. Robotic technology has the potential to enable high levels of patient care, clinical productivity and safety for both patients and healthcare workers. This paper surveys the state-of-the-art in robotics in healthcare and well-being, with particular attention to the key barriers and enablers to the implementation of this technology in real-world settings. Desktop research was used to identify available and emerging robotic technology currently in use (or with potential use) in healthcare settings. Primary sources of information included: academic publications, international organisations, commercial websites and online news agencies. In this paper, applications of robots in healthcare were divided into five main areas: service, assistive, socially-assistive, teleoperated and interventional robots. The maturity and readiness of different products is still an open challenge, with service and interventional robots leading the way. Wide-spread adoption of robots is likely to happen as the cost of the technology reduces, and wide evidence of beneficial long-term impact is available. This manuscript identified the main drivers, challenges, opportunities and considerations for implementing robots in healthcare. We hope this manuscript will raise awareness about robotics in healthcare among a wider audience to maximise availability, quality, and acceptability this technology.