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- ArticleAçık Erişim2023IsVoNet8: A Proposed Deep Learning Model for Classification of Some Fish Species
Kaya, Volkan; Akgül, İsmail; Zencir Tanir, Özge
In the classification of fish, both knowledge and great effort are required to determine the characteristics of fish. Traditionally, however, manual classification of extrinsic characteristics of different fish species has been a difficult and time-consuming process due to their close resemblance to each other. Re-cently, deep learning methods used in the light of developments in the field of computer vision have facilitated the training of fish image classification models and the recognition of various fish species. In this study, a new convolutional neural network model classifying 8 different belonging to 6 families (Mulli-dae, Sparidae, Carangidae, Serranidae, Clupeidae, Salmonidae) fish species using deep learning methods was proposed. The species include Clupeonella cultriventris N., Sparus aurata L., Trachurus trachurus L., Mullus barbatus L., Pagrus major T & S., Dicentrarchus labrax L., Mullus surmuletus L. and Oncorhynchus mykiss W. The proposed model (IsVoNet8) is compared with the ResNet50, ResNet101 and VGG16 models. The success accuracies obtained as a result of the comparison are respectively; 98.62% in the IsVoNet8, 91.37% in the ResNet50 model, 86.12% in the ResNet101 model and 97.75% in the VGG16 model. However, it was obtained that the loss rates of ResNet50 0.3646, ResNet101 0.5811, VGG16 0.0696 and with the IsVoNet 0.0568. As a result, it has been observed that the IsVoNet classifies marine fish, which is widely consumed in Türkiye.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2016Density and biomass of fish populations in Kirmir stream of Sakarya river, Turkey; [Sakarya nehri’nin Kirmir çayı’ndaki balık populasyonlarının yoğunluğu ve biyoması]
Zencir Tanir, Özge; Korkmaz, A. Şeref
In this study, Zippin’s triple-catch removal method was used to estimate density and biomass of fish species in Kirmir Stream of Sakarya River, Central Anatolia Turkey. A total area of 1.5256 ha was sampled and 4167 fishes were caught using electrofishing between February 2007 and November 2007. A total of 9 fish species representing 2 families Cyprinidae and Cobitidae were recorded. Fish species identified are as follows: Chub (Leuciscus cephalus Linnaeus, 1758), barbel (Barbus plebelejus escherichi Heckel, 1843), Capoeta tinca Heckel, 1843, spirlin (Alburnoides bipunctatus Bloch, 1782), Capoeta capoeta sieboldi Steindachner, 1864, tirgis-nase (Chondrostoma regium Heckel, 1843), bleak (Alburnus orontis Sauvage, 1882), spined-loach (Cobitis taenia Linnaeus, 1758) and angora-loach (Noemacheilus angorae Steindachner, 1897). A. orontis was the most dominant species, constituting 1199 fish and 28.77% of the total fishes, followed by C. tinca (1173 fish and 28.15%), B. p. escherichi (584 fish and 14.01%), L. cephalus (454 fish and 10.90%), A. bipunctatus (322 fish and 7.73%), C. regium (245 fish and 5.88 %), N. angorae (107 fish and 2.57%) C. c. sieboldi (65 fish and 1.56%) and C. taenia (18 fish and 0.43%). The density and biomass values were estimated as 11456 fish ha-1 and 346.78 kg ha-1 in February 2007, 8982 fish ha-1 and 279.82 kg ha-1 in May 2007, 6320 fish ha-1 and 251.52 kg ha-1 in August 2007 and 2887 fish ha-1 and 168.87 kg ha-1 in November 2007, respectively. The lowest density and biomass values were observed in November 2007.
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