Jun 8, 2020 · We introduce an efficient deep tiger detector, which consists of the convnet channel adaptation method and an improved tiger detection method ...
An Amur Tiger Detector based on YOLOv3. Contribute to RunchenWei/YOLO-mini-tiger development by creating an account on GitHub.
This study proposes a novel real-time monitoring model called WL-YOLO, which is designed for lightweight wildlife detection in complex forest environments.
Jun 11, 2020 · We introduce an efficient deep tiger detector, which consists of the convnet channel adaptation method and an improved tiger detection method ...
Request PDF | On Jun 8, 2020, Runchen Wei and others published YOLO-mini-tiger: Amur Tiger Detection | Find, read and cite all the research you need on ...
This paper proposes an individual recognition method for Amur tigers based on an improved InceptionResNetV2 model.
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This paper focuses on a novel framework that addresses Illumination variation and provides efficient tiger detection using EnlightenGAN and YOLOv8.
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This paper proposes a wildlife target detection algorithm based on improved YOLOv8n - YOLO-SAG, which aims to balance accuracy and speed.
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Apr 20, 2023 · This paper proposes a novel lightweight deep-learning network for detecting Amur tigers in mobile and resource-constrained environments.
Runchen Wei, Ning He, Ke Lu: YOLO-mini-tiger: Amur Tiger Detection. ICMR 2020: 517-524. a service of Schloss Dagstuhl - Leibniz Center for Informatics.