A Comparative Study of Faster R-CNN Models for Anomaly Detection in 2019 AI City Challenge. - Linu Shine; Anitha Edison; C. V. Jiji (CVPR Workshops, 2019)

Real-Time Traffic Sign Recognition using YOLOv3 based Detector. - Shehan P. Rajendran; Linu Shine; R. Pradeep; Sajith Vijayaraghavan (ICCCNT, 2019)

Vision Based Advanced Driver Assistance System Using Deep Learning. - Bhadra Varma; Sibin Sam; Linu Shine (ICCCNT, 2019)

Fractional Data Distillation Model for Anomaly Detection in Traffic Videos. - Linu Shine; Vaishnav M. A; C. V. Jiji (CVPR Workshops, 2020)

VisDrone-MOT2020: The Vision Meets Drone Multiple Object Tracking Challenge Results. - Heng Fan 001; Dawei Du; Longyin Wen; Pengfei Zhu 001; Qinghua Hu; Haibin Ling; Mubarak Shah; Junwen Pan; Arne Schumann; Bin Dong 006; Daniel Stadler; Duo Xu; et al. (ECCV Workshops (4), 2020)

Automated detection of helmet on motorcyclists from traffic surveillance videos: a comparative analysis using hand-crafted features and CNN. - Linu Shine; C. Victor Jiji (Multim. Tools Appl., 2020)

Comparative Analysis of Two Stage and Single Stage Detectors for Anomaly Detection. - Linu Shine; C. V. Jiji (ICCCNT, 2021)

An Efficient 3D CNN Framework with Attention Mechanisms for Alzheimer's Disease Classification. - Athena George; Bejoy Abraham; Neetha George; Linu Shine; Sivakumar Ramachandran (Comput. Syst. Sci. Eng., 2023)

Refine3DNet: Scaling Precision in 3D Object Reconstruction from Multi-View RGB Images using Attention✱. - Ajith Balakrishnan; Sreeja S; Linu Shine (ICVGIP, 2024)

A two-stage CNN model for the classification and severity analysis of retinal and choroidal diseases in OCT images. - Neetha George; Linu Shine; Ambily N; Bejoy Abraham; Sivakumar Ramachandran (Int. J. Intell. Networks, 2024)