Abstract
Animal conservation is imperative, and technology can certainly assist in different ways. The extinction of endangered species like tigers and elephants has boosted the necessity for such efforts. Human–elephant collision (HEC) has been an active area of research for years. Apart from deforestation, the roads and rail tracks laid down through forest areas intervene a lot in wildlife. Collisions and tragedies are every day, especially in green belts in India and other Asian countries. Therefore, it is crucial to develop vision-based, automated, warning-generating systems to identify the animal/elephant near-site. In the proposed work, different deep learning-based models are proposed to identify elephants in image/video. Several convolutional neural network (CNN)-based models and three transfer learning (TL)-based models, i.e., ResNet50, MobileNet, Inception V3, have been experimented with and tuned for elephant detection. All the models are tested on a synthesized dataset having about 4200 images built using two public datasets, i.e., ELPephant and RailSem19. Two accurate CNN and transfer learning-based models are presented in detail. These highly accurate and precise models can alarm the trains and generate warning signals on site. The proposed CNN and inception network demonstrated high accuracy of 99.53% and 99.91%, respectively, and are remarkable in identifying elephants and hence preventing HEC. The same model can be trained for other animals for their preservation in similar scenarios.
Highlights
Animal mortality is becoming a major concern day by day in the whole world as it is disturbing ecological balance and in certain cases, even the species are being endangered
Animal gait identification model Haar-like feature extraction with Adaboost Classifier based model A robust method to track animals and determine their motion pattern Two-step classification system using LBP-Adaboost followed by HOG-SVM Classifier Animal detection and collision avoidance system using Computer Vision Automatically identifying, counting, and describing wild animals in camera-trap images with Deep Learning Image identification using an edge detection algorithm Automated tool for animal detection in camera trap images Animal detection using a series of images under complex shooting conditions
This paper aims to employ CNN and transfer learning for efficient detection of elephants in different positions on rail tracks so that alert systems can be implemented
Summary
Animal mortality is becoming a major concern day by day in the whole world as it is disturbing ecological balance and in certain cases, even the species are being endangered. In India, human life is intrinsically entangled with the big animal Elephant. Whether it is culture, mythology, or the Hindu custom, Elephant plays a very major role and is considered as a sacred animal besides the symbol of intellectual strength. Due to a lot of human intervention into the habitats of these, it is an endangered species now. Due to a lot of human intervention into the habitats of these, it is an endangered species Whether it is the costly ivory tusk of the mammal or the deforestation by the greedy human beings, at the receiving end are the gigantic mammal's Elephants [1,2]
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