Dr Hossein Malekmohamadi

Job: Senior Lecturer in Game Programming

Faculty: Computing, Engineering and Media

School/department: School of Computer Science and Informatics

Address: De Montfort University, The Gateway, Leicester, LE1 9BH, UK

T: +44 (0)116 250 6182

E: h.malekmohamadi@dmu.ac.uk


Research interests/expertise

  • Computer Vision
  • Machine Learning
  • Multimedia Signal Processing
  • Internet of Energgy (IoE)
  • Quality of Experience (QoE)

Areas of teaching

  • Computer graphics
  • Computer vision



Courses taught

  • Introduction to shader programming
  • Shader programming
  • Introduction to computer vision
  • Final year project coordinator
  • MSc project coordinator

Membership of professional associations and societies

Fellow of the Higher Education Academy

Recent research outputs

  • Analyzing Gas Data Using Deep Learning and 2-D Gramian Angular Fields. In IEEE Sensors Journal, vol. 23, no. 6, pp. 6109-6116, 15 March15, 2023, doi: 10.1109/JSEN.2023.3243149.
  • Novel domestic building energy consumption dataset: 1D timeseries and 2D Gramian Angular Fields representation. Data in Brief, p.108985.
  • Facilitating Deep Learning for Edge Computing: A Case Study on Data Classification. In 2022 IEEE Conference on Dependable and Secure Computing (DSC) (pp. 1-4). IEEE.
  • Lightweight Gramian Angular Field classification for edge internet of energy applications. Cluster Computing, pp.1-13.
  • Creating 3D Gramian Angular Field Representations for Higher Performance Energy Data Classification. In 2022 IEEE International Conference on Image Processing (ICIP) (pp. 3586-3590). IEEE.
  • Energy data lakes: An edge Internet of Energy approach. InEmerging Real-World Applications of Internet of Things 2022 Nov 24 (pp. 21-40). CRC Press.
  • Statistical Analysis of Electroencephalographic Signals in the Stimulation of Energy Data Visualizations. In Intelligent Computing: Proceedings of the 2022 Computing Conference, Volume 2 (pp. 504-519). Cham: Springer International Publishing.
  • Enhanced 3D Point Cloud Object Detection with Iterative Sampling and Clustering Algorithms. DOI: 10.5220/0010910600003124 In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP, pages 674-681 ISBN: 978-989-758-555-5; ISSN: 2184-4321
  • Pickpocketing Recognition in Still Images. In: Del Bimbo A. et al. (eds) Pattern Recognition. ICPR International Workshops and Challenges. ICPR 2021. Lecture Notes in Computer Science, vol 12664. Springer, Cham. https://doi.org/10.1007/978-3-030-68799-1_11
  • Vehicle detection and classification in difficult environmental conditions using deep learning. In Proceedings of SAI Intelligent Systems Conference (pp. 686-696). Springer, Cham.
  • Towards Semantic Segmentation Using Ratio Unpooling. In Proceedings of SAI Intelligent Systems Conference (pp. 111-123). Springer, Cham.
  • Surface Defect Detection Using YOLO Network. In Proceedings of SAI Intelligent Systems Conference (pp. 505-515). Springer, Cham.
  • Human Activity Identification in Smart Daily Environments. In Smart Assisted Living (pp. 91-118). Springer, Cham.
  • Improving a 3-D Convolutional Neural Network Model Reinvented from VGG16 with Batch Normalization. In 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) (pp. 45-50). IEEE.
  • Deep Learning Based Photometric Stereo from Many Images and Under Unknown Illumination. In 2018 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 785-790). IEEE.
  • Low-Cost Automatic Ambient Assisted Living System. In 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) (pp. 693-697). IEEE.
  • Automatic subjective quality estimation of 3D stereoscopic videos: NR-RR approach. In 2017 3DTV Conference: The True Vision-Capture, Transmission and Display of 3D Video (3DTV-CON) (pp. 1-4). IEEE.
  • Paper type classification based on a new 3D surface texture measure. Electronics letters50(8), pp.596-598.
  • A new reduced reference metric for color plus depth 3D video. Journal of Visual Communication and Image Representation, 25(3), pp.534-541.

Published patents

Paper classification based on three-dimensional characteristics. U.S. Patent 9,977,999.