most citedChallenges in video based object detection in maritime scenario using computer vision

38 citations · 45 across the 8 of their papers we have counts for

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cs.CV20232 cited

Data-Efficient Training of CNNs and Transformers with Coresets: A Stability Perspective

Animesh Gupta, Irtiza Hasan, Dilip K. Prasad +1

Coreset selection is among the most effective ways to reduce the training time of CNNs, however, only limited is known on how the resultant models will behave under variations of t…

cs.CV2023

MABNet: Master Assistant Buddy Network with Hybrid Learning for Image Retrieval

Rohit Agarwal, Gyanendra Das, Saksham Aggarwal +2

Image retrieval has garnered growing interest in recent times. The current approaches are either supervised or self-supervised. These methods do not exploit the benefits of hybrid…

cs.CV20232 cited

Patch Gradient Descent: Training Neural Networks on Very Large Images

Deepak K. Gupta, Gowreesh Mago, Arnav Chavan +1

Traditional CNN models are trained and tested on relatively low resolution images (<300 px), and cannot be directly operated on large-scale images due to compute and memory constra…

cs.CV20162 cited

Video Processing from Electro-optical Sensors for Object Detection and Tracking in Maritime Environment: A Survey

D. K. Prasad, D. Rajan, L. Rachmawati +2

We present a survey on maritime object detection and tracking approaches, which are essential for the development of a navigational system for autonomous ships. The electro-optical…

cs.CV201638 cited

Challenges in video based object detection in maritime scenario using computer vision

D. K. Prasad, C. K. Prasath, D. Rajan +3

This paper discusses the technical challenges in maritime image processing and machine vision problems for video streams generated by cameras. Even well documented problems of hori…