Research

Currently embarking on a PhD in Computer Science developing machine learning methods applicable for detection, classification and understanding of species behaviour from camera trap imagery.

Supervised by Dr Allan Tucker and Dr Chris Carbone at Brunel University London and the Institute of Zoology as part of the London NERC DTP.

Software

CamTrap Detector - Cross-Platform Desktop Application for detecting animals in camera trap images.
CamTrapML - Python package for processing Camera Trap imagery using machine learning.

Publications

Reasoning About Neural Network Activations: An Application in Spatial Animal Behaviour from Camera Trap Classifications
(2020) Evans, B.C., Tucker, A., Wearn, O.R., Carbone, C.
ECML PKDD 2020 Workshops. ECML PKDD 2020. Communications in Computer and Information Science, vol 1323. Springer, Cham.
Can CNN-based species classification generalise across variation in habitat within a camera trap survey?
(2023) Norman, D. L., Bischoff, P. H., Wearn, O. R., Ewers, R. M., Rowcliffe, J. M., Evans, B., Sethi, S., Chapman, P. M., & Freeman, R.
Methods in Ecology and Evolution.
Using an Instant Visual and Text Based Feedback Tool to Teach Path Finding Algorithms: A Concept
(2021) B. Nagaria, B. C. Evans, A. Mann and M. Arzoky
2021 Third International Workshop on Software Engineering Education for the Next Generation (SEENG).

Further details on research activity can be found on my academic profiles at London NERC DTP, Google Scholar and ResearchGate.