Customized deep neural network model for autonomous and efficient surveillance of wildlife in national parks

Maheswari, M.; Josephine, M.S.; Jeyabalaraja, V.

doi:10.1016/j.compeleceng.2022.107913

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…Some researchers have focused on developing object detection methods for multiple animals. For example, a multi-animal object detection model was constructed by combining convolutional neural networks, achieving higher accuracy [16]. Another study utilized a two-stage model and an optimized multi-scale attention mechanism to make the model more sensitive to small objects, achieving high accuracy on the Animal-80 dataset [17].…”

Section: Introductionmentioning

confidence: 99%

RTAD: A Real-Time Animal Object Detection Model Based on a Large Selective Kernel and Channel Pruning

Liu,

Fan,

Zhao

et al. 2023

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Animal resources are significant to human survival and development and the ecosystem balance. Automated multi-animal object detection is critical in animal research and conservation and ecosystem monitoring. The objective is to design a model that mitigates the challenges posed by the large number of parameters and computations in existing animal object detection methods. We developed a backbone network with enhanced representative capabilities to pursue this goal. This network combines the foundational structure of the Transformer model with the Large Selective Kernel (LSK) module, known for its wide receptive field. To further reduce the number of parameters and computations, we incorporated a channel pruning technique based on Fisher information to eliminate channels of lower importance. With the help of the advantages of the above designs, a real-time animal object detection model based on a Large Selective Kernel and channel pruning (RTAD) was built. The model was evaluated using a public animal dataset, AP-10K, which included 50 annotated categories. The results demonstrated that our model has almost half the parameters of YOLOv8-s yet surpasses it by 6.2 AP. Our model provides a new solution for real-time animal object detection.

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Section: Introductionmentioning

confidence: 99%

RTAD: A Real-Time Animal Object Detection Model Based on a Large Selective Kernel and Channel Pruning

Liu,

Fan,

Zhao

et al. 2023

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A systematic literature review: Trends and current state of research on Bengal tiger (Panthera tigris tigris), 2010–2022

Maharjan,

Maraseni,

Allen

et al. 2024

Biodivers Conserv

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Tigers are one of the most recognized and charismatic predator on earth, yet their habitats have declined, their numbers are low, and substantial threats to their survival persist. Although, tiger conservation is high priority globally and tigers are generally considered well studied, there has been no comprehensive global assessment of tiger-related publications aimed at identifying trends, assessing their status and pinpointing research gaps. Utilizing PRISMA framework, we conducted an extensive search across multiple databases, including Scopus, Web of Science, and ScienceDirect, to gather research related to Bengal tigers. Following thorough screening, we selected and evaluated 491 articles published between 2010 and 2022 to address these issues. The results show that publications on Bengal tigers have steadily on rise, with an average of 40 papers/year within this period. We found that most research was focused on the theme of tiger biology. Information on leopards and dholes was also frequently associated with tiger research. The highest number of lead authors originated from India (n = 192), where most research was also conducted. Authors from USA (n = 111) and UK (n = 38) were the next most productive, even though tigers are not found in or anywhere near these countries. We demonstrate that there is only limited amount of transboundary research, and that relatively little tiger research is conducted in the forests beyond protected areas. Similarly, very important but the least studied themes ─Poaching, Population and Socio-culture dimension should be the priority of future research efforts. Additionally, research on tourism, economic aspects and technological inputs are essential for the sustainable conservation of Bengal tigers.

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A Review on Animal Detection and Classification using Computer Vision Techniques: Scope for Future Enhancement to Application

Balakrishna

Dhanushree

2023

2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)

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Customized deep neural network model for autonomous and efficient surveillance of wildlife in national parks

Cited by 3 publications

References 7 publications

RTAD: A Real-Time Animal Object Detection Model Based on a Large Selective Kernel and Channel Pruning

RTAD: A Real-Time Animal Object Detection Model Based on a Large Selective Kernel and Channel Pruning

A systematic literature review: Trends and current state of research on Bengal tiger (Panthera tigris tigris), 2010–2022

A Review on Animal Detection and Classification using Computer Vision Techniques: Scope for Future Enhancement to Application

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