Jul 9, 2023 · We try to construct a highly efficient deep neural network architectures for iris detection based on the experience and technology of small target detection.
Jul 23, 2023 · The results shown that YOLO NFPEM with three PEP modules cascaded achieves the best AP for iris of ~ 91.37% higher than YOLO Nano (~83.99%), ...
Our experimental results on an NVIDIA Jetson Nano embedded board show that this “light-weight” method is effective for counting the passing-through pigs, in ...
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Apr 25, 2024 · Xiangyu Ge, Chao Yin, Qian-Xiang Zhou, Tianqing Zhou, Fang Zhang, Zongrui Yang, Bingyuan Fan: YOLO NFPEM: A More Accurate Iris Detector.
With the rapid development of deep learning, iris recognition methods based on deep learning are constantly being proposed. These methods generally consist of ...
The fine-tuned model from YOLO object detector yielded real-time location with high accuracy, overcoming problems such as noise, eyelids, eyelashes and ...
Missing: NFPEM: | Show results with:NFPEM:
Dec 16, 2022 · Experiment results show that iris-detection accuracy can reach 99.83% with this modified YOLO v4 model, which is higher than that of a ...
Missing: NFPEM: | Show results with:NFPEM:
YOLO NFPEM: A More Accurate Iris Detector. HCI (41) (2023). Yue Wang, Hongjuan Wang, Fang Zhang, Xuxin Li · FDA-CDM : Data Augmentation Framework for ...
YOLO NFPEM: A More Accurate Iris Detector (book chapter). In Artificial Intelligence in HCI. Ge, Xiangyu | Yin, Chao | Zhou, Qianxiang | Zhou, Tianqing ...
YOLO NFPEM: A More Accurate Iris Detector. Iris detection remains vital ... L-FPN R-CNN: An Accurate Detector for Detecting Bird Nests in Aerial Power Tower ...