论文标题
使用机器视觉的假希尔萨鱼检测
Fake Hilsa Fish Detection Using Machine Vision
论文作者
论文摘要
希尔萨是孟加拉国的民族鱼。孟加拉国通过出口这种鱼来赚取很多外币。不幸的是，最近几天，一些不道德的商人正在出售伪造的希尔萨鱼来获利。沙丁鱼和撒丁岛是市场上销量最多的人。孟加拉国政府机构，即孟加拉国食品安全局说，这些假的希尔萨鱼含有高水平的镉和铅，对人类有害。在这项研究中，我们提出了一种可以轻松识别原始希尔萨鱼和假希尔萨鱼的方法。根据有关在线文献的研究，我们是第一个研究识别原始希尔萨鱼的研究。我们收集了16,000张原始和伪造的希尔萨鱼的图像。为了对这些图像进行分类，我们使用了几种基于深度学习的模型。然后，已经比较了他们之间的表现。在这些模型中，Densenet201的精度最高为97.02％。
Hilsa is the national fish of Bangladesh. Bangladesh is earning a lot of foreign currency by exporting this fish. Unfortunately, in recent days, some unscrupulous businessmen are selling fake Hilsa fishes to gain profit. The Sardines and Sardinella are the most sold in the market as Hilsa. The government agency of Bangladesh, namely Bangladesh Food Safety Authority said that these fake Hilsa fish contain high levels of cadmium and lead which are detrimental for humans. In this research, we have proposed a method that can readily identify original Hilsa fish and fake Hilsa fish. Based on the research available on online literature, we are the first to do research on identifying original Hilsa fish. We have collected more than 16,000 images of original and counterfeit Hilsa fish. To classify these images, we have used several deep learning-based models. Then, the performance has been compared between them. Among those models, DenseNet201 achieved the highest accuracy of 97.02%.
