Publications

@article{saikia_colour_2021,

title = {Colour Neural Descriptors for Instance Retrieval Using CNN Features and Colour Models},

author = {Surajit Saikia and Laura Fernández-Robles and Eduardo Fidalgo and Enrique Alegre},

url = {https://ieeexplore.ieee.org/abstract/document/9344701},

year  = {2021},

date = {2021-01-01},

journal = {IEEE Access},

volume = {9},

pages = {23218–23234},

abstract = {This paper presents color neural descriptors for image retrieval, using CNN features from different color spaces without fine-tuning. An object detector enhances feature extraction, and a stride-based query expansion improves multi-view retrieval. The method achieves state-of-the-art results on multiple datasets.},

note = {Publisher: IEEE},

keywords = {CNN Features, Color Descriptors, deep learning, Image Retrieval, Object Detection},

pubstate = {published},

tppubtype = {article}

}

@article{saikia_object_2017,

title = {Object detection for crime scene evidence analysis using deep learning},

author = {Surajit Saikia and Eduardo Fidalgo and Enrique Alegre and Laura Fernández-Robles},

url = {https://link.springer.com/chapter/10.1007/978-3-319-68548-9_2},

year  = {2017},

date = {2017-01-01},

journal = {Image Analysis and Processing-ICIAP 2017: 19th International Conference, Catania, Italy, September 11-15, 2017, Proceedings, Part II 19},

pages = {14–24},

abstract = {This paper introduces a real-time object detection system based on Faster R-CNN for surveillance and crime scene analysis. Tested on ImageNet and Karina datasets, it achieved 74.33% accuracy, detecting objects in 0.12 seconds per image using an Nvidia-TitanX GPU.},

note = {Publisher: Springer International Publishing},

keywords = {fster R-CNN, Object Detection, Real-time system, surveillance},

pubstate = {published},

tppubtype = {article}

}